Cost of Sunlight Analysis-2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "01d79ba5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# !pip install altair"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b7353c74",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install vega"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a7023626",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import pandas as pd\n",
    "import altair as alt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7496e28c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbec566b",
   "metadata": {},
   "source": [
    "# Reading in JSON Search Results from localize.city \n",
    "\n",
    "I focused only on available listings in and around Prospect Park, Brooklyn NYC and only 1 bedroom/studio apartments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "988e9900",
   "metadata": {},
   "outputs": [],
   "source": [
    "def json_to_dict(filepath):\n",
    "    with open(filepath, 'r') as file:\n",
    "        data = json.load(file)\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "134e128c",
   "metadata": {},
   "outputs": [],
   "source": [
    "filepaths = [\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page1.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page2.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page3.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page4.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page5.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page6.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page7.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page8.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json//brooklyn_prospect_listing_result_page9.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page10.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page11.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page12.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page13.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page14.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page15.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page16.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page17.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page18.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page19.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page20.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page21.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page22.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page23.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page24.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page25.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page26.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page27.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page28.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page29.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page30.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page31.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page32.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page33.json', \n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page34.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page35.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page36.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page37.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page38.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page39.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page40.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page41.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page42.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page43.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page44.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page45.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page46.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page47.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page48.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page49.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page50.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page51.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page52.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page53.json',\n",
    "    '/Users/ligeaalexander/Desktop/Developer/Project-3/search result json/brooklyn_prospect_listing_result_page54.json']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6827e786",
   "metadata": {},
   "outputs": [],
   "source": [
    "dictionaries = [json_to_dict(filepath) for filepath in filepaths]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "40d64a29",
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(type(dictionaries))\n",
    "# print(type(dictionaries[0]))\n",
    "# print(dictionaries[0].keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d3ba523c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# dictionaries[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2674b5da",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # listing = []\n",
    "\n",
    "# for i, dict in enumerate(dictionaries):\n",
    "# #     print(f\"Page {i+1}, {[id['id']for id in dict['data']['searchResult']['poi']]}\")\n",
    "#     print(len([id['id']for id in dict['data']['searchResult']['poi']]))\n",
    "#     print([id['id']for id in dict['data']['searchResult']['poi']])\n",
    "#     print('------')\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "246099c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(dictionaries[0]['data']['searchResult'].keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "962d9718",
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(dictionaries[0]['data']['searchResult']['poi'][0].keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b304372e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# print(dictionaries[0]['data']['searchResult']['poi'][0]['insights']['insights'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "14a07d80",
   "metadata": {},
   "outputs": [],
   "source": [
    "# for dict in dictionaries:\n",
    "# #     print(dict['data']['searchResult']['poi'])\n",
    "#     for id in dict['data']['searchResult']['poi']:\n",
    "# #         print(id['id'])\n",
    "#         for i in id['insights']['insights']:\n",
    "# #             print(i['category'])\n",
    "#             if i['category'] == 'naturalLight':\n",
    "#                 print([i['tradeoff']])\n",
    "#                 print('----')\n",
    "#             else:\n",
    "#                 None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "20fea656",
   "metadata": {},
   "outputs": [],
   "source": [
    "# for dict in dictionaries:\n",
    "# #     print(dict['data']['searchResult']['poi'])\n",
    "#     for id in dict['data']['searchResult']['poi']:\n",
    "# #         print(id['id'])\n",
    "#         for i in id['insights']['insights']:\n",
    "# #             print(i['category'])\n",
    "#             if i['category'] == 'naturalLight':\n",
    "#                 print(id['id'])\n",
    "# #                 print(id['price'])\n",
    "#                 print(id['beds'])\n",
    "#                 print(i['tradeoff']['value'] + f\" and the rent is {id['price']}\")\n",
    "# #             elif i['category'] != 'naturalLight' :\n",
    "# #                 print(f\"No light info for {id['id']}, rent = {id['price']}\")\n",
    "#         print(f\"No sunlight data available for {id['id']} and the rent is {id['price']}\")\n",
    "#     print('======')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "38051a10",
   "metadata": {},
   "outputs": [],
   "source": [
    "ids = []\n",
    "zipcode = []\n",
    "unit_number = []\n",
    "building_class =[]\n",
    "beds = []\n",
    "size = []\n",
    "rents = []\n",
    "light_cat = []\n",
    "lights = []\n",
    "\n",
    "for dictionary in dictionaries:\n",
    "    for id in dictionary['data']['searchResult']['poi']:\n",
    "        for insight in id['insights']['insights']:\n",
    "            if insight['category'] == 'naturalLight':\n",
    "                ids.append(id['id'])\n",
    "                zipcode.append(id['addressDetails']['zipcode'])\n",
    "                unit_number.append(id['addressDetails']['unitNumber'])\n",
    "                building_class.append(id['buildingClass'])\n",
    "                beds.append(id['beds'])\n",
    "                size.append(id['area'])\n",
    "                rents.append(id['price'])\n",
    "                light_cat.append(insight['tradeoff']['value'])\n",
    "                lights.append(insight['tradeoff']['value'] + f\" and the rent is {id['price']}\")\n",
    "        if len(id['insights']['insights']) == 0 or all(insight['category'] != 'naturalLight' for insight in id['insights']['insights']):\n",
    "            ids.append(id['id'])\n",
    "            zipcode.append(id['addressDetails']['zipcode'])\n",
    "            unit_number.append(id['addressDetails']['unitNumber'])\n",
    "            building_class.append(id['buildingClass'])\n",
    "            beds.append(id['beds'])\n",
    "            size.append(id['area'])\n",
    "            rents.append(id['price'])\n",
    "            light_cat.append(f\"No sunlight\")\n",
    "            lights.append(f\"No sunlight data available and the rent is {id['price']}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f494b25",
   "metadata": {},
   "source": [
    "## Pre-processing apartment listings with sun exposure details"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "cc55f744",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = {\n",
    "    'listing_path': ids,\n",
    "    'location': zipcode,\n",
    "    'unit_number': unit_number,\n",
    "    'building_class': building_class,\n",
    "    'beds': beds,\n",
    "    'size':size,\n",
    "    'rent': rents,\n",
    "    'sun_exposure_cat': light_cat,\n",
    "    'sun_exposure': lights\n",
    "}\n",
    "\n",
    "df_sun_exposure = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b57cf208",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9630"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure.size.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6eae2346",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>listing_path</th>\n",
       "      <th>location</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>l-2g3vm2ptsq8i</td>\n",
       "      <td>11225</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3726</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 3726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>l-2in0401r3l0j</td>\n",
       "      <td>11215</td>\n",
       "      <td>1B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>l-hrd2dhl7etdr</td>\n",
       "      <td>11225</td>\n",
       "      <td>6A</td>\n",
       "      <td>condo</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2043.0</td>\n",
       "      <td>11500</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 11500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>l-dgbncnljpk2t</td>\n",
       "      <td>11217</td>\n",
       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>m-22ir9qbmgt2p</td>\n",
       "      <td>11225</td>\n",
       "      <td>3E</td>\n",
       "      <td>multi-family</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9999.0</td>\n",
       "      <td>3300</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 3300</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     listing_path location unit_number building_class  beds    size   rent  \\\n",
       "0  l-2g3vm2ptsq8i    11225           2    rental unit   3.0     NaN   3726   \n",
       "1  l-2in0401r3l0j    11215          1B    rental unit   2.0     NaN   4500   \n",
       "2  l-hrd2dhl7etdr    11225          6A          condo   4.0  2043.0  11500   \n",
       "3  l-dgbncnljpk2t    11217          B2    rental unit   3.0   900.0   4750   \n",
       "4  m-22ir9qbmgt2p    11225          3E   multi-family   3.0  9999.0   3300   \n",
       "\n",
       "  sun_exposure_cat                                      sun_exposure  \n",
       "0      No sunlight   No sunlight data available and the rent is 3726  \n",
       "1      No sunlight   No sunlight data available and the rent is 4500  \n",
       "2      No sunlight  No sunlight data available and the rent is 11500  \n",
       "3      No sunlight   No sunlight data available and the rent is 4750  \n",
       "4      No sunlight   No sunlight data available and the rent is 3300  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "978d99e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No sunlight                                626\n",
       "Limited natural light                      204\n",
       "Moderate natural light                      91\n",
       "This apartment has limited sunlight         76\n",
       "Bright & sun drenched                       32\n",
       "This apartment has moderate sunlight        24\n",
       "This apartment is bright & sun-drenched     17\n",
       "Name: sun_exposure_cat, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure.sun_exposure_cat.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dc8fc373",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "building_class\n",
       "brownstone                        1\n",
       "co-op                            36\n",
       "condo                           142\n",
       "condop                            1\n",
       "mixed-use single-family home      4\n",
       "mixed-use three-family home       8\n",
       "mixed-use two-family home        16\n",
       "multi-family                     66\n",
       "multifamily                     496\n",
       "rental unit                     230\n",
       "single-family home               12\n",
       "three-family home                34\n",
       "two-family home                  22\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_sun_exposure\n",
    "     .groupby('building_class')\n",
    "     .size()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1b6071a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sun_exposure = df_sun_exposure[df_sun_exposure['building_class']=='rental unit']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d0e09555",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No sunlight                                184\n",
       "This apartment has limited sunlight         26\n",
       "This apartment has moderate sunlight        12\n",
       "This apartment is bright & sun-drenched      8\n",
       "Name: sun_exposure_cat, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure.sun_exposure_cat.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f1ecb9df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>listing_path</th>\n",
       "      <th>location</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>l-803776tr5607</td>\n",
       "      <td>11201</td>\n",
       "      <td>6M</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>3450</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 3450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>l-vrqgvtdthnm3</td>\n",
       "      <td>11201</td>\n",
       "      <td>10G</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>756.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 4700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>l-vabqa5dm04h2</td>\n",
       "      <td>11201</td>\n",
       "      <td>1C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>2550</td>\n",
       "      <td>This apartment has limited sunlight</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>l-n8oo4au52hda</td>\n",
       "      <td>11201</td>\n",
       "      <td>1A</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>4250</td>\n",
       "      <td>This apartment has limited sunlight</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>l-p12e1cru4a0l</td>\n",
       "      <td>11201</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>757</th>\n",
       "      <td>l-metf0tnqb3oa</td>\n",
       "      <td>11238</td>\n",
       "      <td>6B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\n",
       "      <td>l-v22eed67chvl</td>\n",
       "      <td>11238</td>\n",
       "      <td>501</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>606</th>\n",
       "      <td>l-7g46vji1nit8</td>\n",
       "      <td>11238</td>\n",
       "      <td>2K</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270</th>\n",
       "      <td>l-lnn5usqallek</td>\n",
       "      <td>11238</td>\n",
       "      <td>2002</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4300</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 4300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>l-42o619vk51bj</td>\n",
       "      <td>11238</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800</td>\n",
       "      <td>No sunlight</td>\n",
       "      <td>No sunlight data available and the rent is 2800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>230 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       listing_path location unit_number building_class  beds    size  rent  \\\n",
       "496  l-803776tr5607    11201          6M    rental unit   0.0   457.0  3450   \n",
       "497  l-vrqgvtdthnm3    11201         10G    rental unit   1.0   756.0  4700   \n",
       "428  l-vabqa5dm04h2    11201          1C    rental unit   1.0   525.0  2550   \n",
       "403  l-n8oo4au52hda    11201          1A    rental unit   3.0  1250.0  4250   \n",
       "445  l-p12e1cru4a0l    11201           1    rental unit   1.0     NaN  4200   \n",
       "..              ...      ...         ...            ...   ...     ...   ...   \n",
       "757  l-metf0tnqb3oa    11238          6B    rental unit   2.0     NaN  4000   \n",
       "782  l-v22eed67chvl    11238         501    rental unit   2.0     NaN  4200   \n",
       "606  l-7g46vji1nit8    11238          2K    rental unit   1.0     NaN  4200   \n",
       "270  l-lnn5usqallek    11238        2002    rental unit   1.0     NaN  4300   \n",
       "255  l-42o619vk51bj    11238          1F    rental unit   0.0     NaN  2800   \n",
       "\n",
       "                        sun_exposure_cat  \\\n",
       "496                          No sunlight   \n",
       "497                          No sunlight   \n",
       "428  This apartment has limited sunlight   \n",
       "403  This apartment has limited sunlight   \n",
       "445                          No sunlight   \n",
       "..                                   ...   \n",
       "757                          No sunlight   \n",
       "782                          No sunlight   \n",
       "606                          No sunlight   \n",
       "270                          No sunlight   \n",
       "255                          No sunlight   \n",
       "\n",
       "                                          sun_exposure  \n",
       "496    No sunlight data available and the rent is 3450  \n",
       "497    No sunlight data available and the rent is 4700  \n",
       "428  This apartment has limited sunlight and the re...  \n",
       "403  This apartment has limited sunlight and the re...  \n",
       "445    No sunlight data available and the rent is 4200  \n",
       "..                                                 ...  \n",
       "757    No sunlight data available and the rent is 4000  \n",
       "782    No sunlight data available and the rent is 4200  \n",
       "606    No sunlight data available and the rent is 4200  \n",
       "270    No sunlight data available and the rent is 4300  \n",
       "255    No sunlight data available and the rent is 2800  \n",
       "\n",
       "[230 rows x 9 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure.sort_values(by = 'rent',ascending =False).sort_values(by = 'location',ascending =True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b8c73b51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "listing_path         object\n",
       "location             object\n",
       "unit_number          object\n",
       "building_class       object\n",
       "beds                float64\n",
       "size                float64\n",
       "rent                  int64\n",
       "sun_exposure_cat     object\n",
       "sun_exposure         object\n",
       "dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d3b0ffa5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No sunlight\n",
      "This apartment has moderate sunlight\n",
      "This apartment has limited sunlight\n",
      "This apartment is bright & sun-drenched\n"
     ]
    }
   ],
   "source": [
    "unique_values = df_sun_exposure['sun_exposure_cat'].unique()\n",
    "\n",
    "# Print the unique values\n",
    "for value in unique_values:\n",
    "    print(value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ce33ff9b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0            No sunlight data\n",
      "1            No sunlight data\n",
      "3            No sunlight data\n",
      "199         Moderate sunlight\n",
      "200          No sunlight data\n",
      "                ...          \n",
      "1041         No sunlight data\n",
      "1043         No sunlight data\n",
      "1062         No sunlight data\n",
      "1067    Limited natural light\n",
      "1068         No sunlight data\n",
      "Name: sun_exposure_cat, Length: 230, dtype: object\n"
     ]
    }
   ],
   "source": [
    "label_mapping = {\n",
    "    'No sunlight': 'No sunlight data',\n",
    "    'nan':'No sunlight data',\n",
    "    'Limited natural light': 'Limited natural light',\n",
    "    'This apartment has limited sunlight': 'Limited natural light',\n",
    "    'This apartment has moderate sunlight': 'Moderate sunlight',\n",
    "    'Moderate natural light':'Moderate sunlight',\n",
    "    'Bright & sun drenched':'Bright & sun drenched',\n",
    "    'This apartment is bright & sun-drenched':'Bright & sun drenched'\n",
    "    \n",
    "}\n",
    "\n",
    "# Update the values in the column using the map() method\n",
    "df_sun_exposure['sun_exposure_cat'] = df_sun_exposure['sun_exposure_cat'].map(label_mapping)\n",
    "\n",
    "# The values in the 'your_column_name' column will be updated with the new labels\n",
    "\n",
    "# Example: Printing the updated column\n",
    "print(df_sun_exposure['sun_exposure_cat'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "020a3e06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>listing_path</th>\n",
       "      <th>location</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>l-2g3vm2ptsq8i</td>\n",
       "      <td>11225</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3726</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>l-2in0401r3l0j</td>\n",
       "      <td>11215</td>\n",
       "      <td>1B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>l-dgbncnljpk2t</td>\n",
       "      <td>11217</td>\n",
       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1041</th>\n",
       "      <td>l-f280460qpan0</td>\n",
       "      <td>11221</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1066.0</td>\n",
       "      <td>4150</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1043</th>\n",
       "      <td>l-21m12jnumbm4</td>\n",
       "      <td>11221</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3678</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1062</th>\n",
       "      <td>l-iqp310aocqdd</td>\n",
       "      <td>11213</td>\n",
       "      <td>4F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3250</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1067</th>\n",
       "      <td>l-7g7gkgl3ak4i</td>\n",
       "      <td>11213</td>\n",
       "      <td>2B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>2850</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1068</th>\n",
       "      <td>l-1s265npkj314</td>\n",
       "      <td>11213</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4250</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>230 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        listing_path location unit_number building_class  beds    size  rent  \\\n",
       "0     l-2g3vm2ptsq8i    11225           2    rental unit   3.0     NaN  3726   \n",
       "1     l-2in0401r3l0j    11215          1B    rental unit   2.0     NaN  4500   \n",
       "3     l-dgbncnljpk2t    11217          B2    rental unit   3.0   900.0  4750   \n",
       "199   l-k5pmp1c6dcau    11215           3    rental unit   1.0     NaN  3750   \n",
       "200   l-ok0278ecbrpc    11217         312    rental unit   1.0     NaN  4000   \n",
       "...              ...      ...         ...            ...   ...     ...   ...   \n",
       "1041  l-f280460qpan0    11221          1R    rental unit   1.0  1066.0  4150   \n",
       "1043  l-21m12jnumbm4    11221           2    rental unit   3.0     NaN  3678   \n",
       "1062  l-iqp310aocqdd    11213          4F    rental unit   3.0     NaN  3250   \n",
       "1067  l-7g7gkgl3ak4i    11213          2B    rental unit   1.0   600.0  2850   \n",
       "1068  l-1s265npkj314    11213           2    rental unit   3.0     NaN  4250   \n",
       "\n",
       "           sun_exposure_cat                                       sun_exposure  \n",
       "0          No sunlight data    No sunlight data available and the rent is 3726  \n",
       "1          No sunlight data    No sunlight data available and the rent is 4500  \n",
       "3          No sunlight data    No sunlight data available and the rent is 4750  \n",
       "199       Moderate sunlight  This apartment has moderate sunlight and the r...  \n",
       "200        No sunlight data    No sunlight data available and the rent is 4000  \n",
       "...                     ...                                                ...  \n",
       "1041       No sunlight data    No sunlight data available and the rent is 4150  \n",
       "1043       No sunlight data    No sunlight data available and the rent is 3678  \n",
       "1062       No sunlight data    No sunlight data available and the rent is 3250  \n",
       "1067  Limited natural light  This apartment has limited sunlight and the re...  \n",
       "1068       No sunlight data    No sunlight data available and the rent is 4250  \n",
       "\n",
       "[230 rows x 9 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "98e48765",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sun_exposure['floor'] = df_sun_exposure['unit_number'].apply(lambda x: re.findall(r'\\d', x)[0] if re.findall(r'\\d', x) else None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "91002aef",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>listing_path</th>\n",
       "      <th>location</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>floor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>l-2g3vm2ptsq8i</td>\n",
       "      <td>11225</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3726</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3726</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>l-2in0401r3l0j</td>\n",
       "      <td>11215</td>\n",
       "      <td>1B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>l-dgbncnljpk2t</td>\n",
       "      <td>11217</td>\n",
       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1041</th>\n",
       "      <td>l-f280460qpan0</td>\n",
       "      <td>11221</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1066.0</td>\n",
       "      <td>4150</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1043</th>\n",
       "      <td>l-21m12jnumbm4</td>\n",
       "      <td>11221</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3678</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3678</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1062</th>\n",
       "      <td>l-iqp310aocqdd</td>\n",
       "      <td>11213</td>\n",
       "      <td>4F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3250</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3250</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1067</th>\n",
       "      <td>l-7g7gkgl3ak4i</td>\n",
       "      <td>11213</td>\n",
       "      <td>2B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>2850</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1068</th>\n",
       "      <td>l-1s265npkj314</td>\n",
       "      <td>11213</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4250</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4250</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>230 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        listing_path location unit_number building_class  beds    size  rent  \\\n",
       "0     l-2g3vm2ptsq8i    11225           2    rental unit   3.0     NaN  3726   \n",
       "1     l-2in0401r3l0j    11215          1B    rental unit   2.0     NaN  4500   \n",
       "3     l-dgbncnljpk2t    11217          B2    rental unit   3.0   900.0  4750   \n",
       "199   l-k5pmp1c6dcau    11215           3    rental unit   1.0     NaN  3750   \n",
       "200   l-ok0278ecbrpc    11217         312    rental unit   1.0     NaN  4000   \n",
       "...              ...      ...         ...            ...   ...     ...   ...   \n",
       "1041  l-f280460qpan0    11221          1R    rental unit   1.0  1066.0  4150   \n",
       "1043  l-21m12jnumbm4    11221           2    rental unit   3.0     NaN  3678   \n",
       "1062  l-iqp310aocqdd    11213          4F    rental unit   3.0     NaN  3250   \n",
       "1067  l-7g7gkgl3ak4i    11213          2B    rental unit   1.0   600.0  2850   \n",
       "1068  l-1s265npkj314    11213           2    rental unit   3.0     NaN  4250   \n",
       "\n",
       "           sun_exposure_cat  \\\n",
       "0          No sunlight data   \n",
       "1          No sunlight data   \n",
       "3          No sunlight data   \n",
       "199       Moderate sunlight   \n",
       "200        No sunlight data   \n",
       "...                     ...   \n",
       "1041       No sunlight data   \n",
       "1043       No sunlight data   \n",
       "1062       No sunlight data   \n",
       "1067  Limited natural light   \n",
       "1068       No sunlight data   \n",
       "\n",
       "                                           sun_exposure floor  \n",
       "0       No sunlight data available and the rent is 3726     2  \n",
       "1       No sunlight data available and the rent is 4500     1  \n",
       "3       No sunlight data available and the rent is 4750     2  \n",
       "199   This apartment has moderate sunlight and the r...     3  \n",
       "200     No sunlight data available and the rent is 4000     3  \n",
       "...                                                 ...   ...  \n",
       "1041    No sunlight data available and the rent is 4150     1  \n",
       "1043    No sunlight data available and the rent is 3678     2  \n",
       "1062    No sunlight data available and the rent is 3250     4  \n",
       "1067  This apartment has limited sunlight and the re...     2  \n",
       "1068    No sunlight data available and the rent is 4250     2  \n",
       "\n",
       "[230 rows x 10 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "52d218a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sun_exposure.to_csv('bk_sun_exposure.csv', index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe44a0dc",
   "metadata": {},
   "source": [
    "# Pre-processing ACS Household Living Data from Census Reporter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0396ed97",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'release': {'id': 'acs2021_5yr', 'years': '2017-2021', 'name': 'ACS 2021 5-year'}, 'tables': {'B09021': {'title': 'Living Arrangements of Adults 18 Years and Over by Age', 'universe': 'Population 18 Years and Over in Households', 'denominator_column_id': 'B09021001', 'columns': {'B09021001': {'name': 'Total:', 'indent': 0}, 'B09021002': {'name': 'Lives alone', 'indent': 1}, 'B09021003': {'name': 'Householder living with spouse or spouse of householder', 'indent': 1}, 'B09021004': {'name': 'Householder living with unmarried partner or unmarried partner of householder', 'indent': 1}, 'B09021005': {'name': 'Child of householder', 'indent': 1}, 'B09021006': {'name': 'Other relatives', 'indent': 1}, 'B09021007': {'name': 'Other nonrelatives', 'indent': 1}, 'B09021008': {'name': '18 to 34 years:', 'indent': 1}, 'B09021009': {'name': 'Lives alone', 'indent': 2}, 'B09021010': {'name': 'Householder living with spouse or spouse of householder', 'indent': 2}, 'B09021011': {'name': 'Householder living with unmarried partner or unmarried partner of householder', 'indent': 2}, 'B09021012': {'name': 'Child of householder', 'indent': 2}, 'B09021013': {'name': 'Other relatives', 'indent': 2}, 'B09021014': {'name': 'Other nonrelatives', 'indent': 2}, 'B09021015': {'name': '35 to 64 years:', 'indent': 1}, 'B09021016': {'name': 'Lives alone', 'indent': 2}, 'B09021017': {'name': 'Householder living with spouse or spouse of householder', 'indent': 2}, 'B09021018': {'name': 'Householder living with unmarried partner or unmarried partner of householder', 'indent': 2}, 'B09021019': {'name': 'Child of householder', 'indent': 2}, 'B09021020': {'name': 'Other relatives', 'indent': 2}, 'B09021021': {'name': 'Other nonrelatives', 'indent': 2}, 'B09021022': {'name': '65 years and over:', 'indent': 1}, 'B09021023': {'name': 'Lives alone', 'indent': 2}, 'B09021024': {'name': 'Householder living with spouse or spouse of householder', 'indent': 2}, 'B09021025': {'name': 'Householder living with unmarried partner or unmarried partner of householder', 'indent': 2}, 'B09021026': {'name': 'Child of householder', 'indent': 2}, 'B09021027': {'name': 'Other relatives', 'indent': 2}, 'B09021028': {'name': 'Other nonrelatives', 'indent': 2}}}}}\n"
     ]
    }
   ],
   "source": [
    "with open('/Users/ligeaalexander/Desktop/Developer/Project-2/acs2021_5yr_B09021.json', 'r') as file:\n",
    "        bk_pop_living = json.load(file)\n",
    "print(bk_pop_living)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "12aa3221",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['release', 'tables'])\n"
     ]
    }
   ],
   "source": [
    "print(bk_pop_living.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "94dad257",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs = pd.read_csv('acs2021_5yr_B09021_86000US11230.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ba2e7b50",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geoid</th>\n",
       "      <th>Zipcode</th>\n",
       "      <th>Total</th>\n",
       "      <th>B09021001, Error</th>\n",
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       "      <th>0</th>\n",
       "      <td>06000US3604710022</td>\n",
       "      <td>Brooklyn borough, Kings County, NY</td>\n",
       "      <td>2049635</td>\n",
       "      <td>1837</td>\n",
       "      <td>288737</td>\n",
       "      <td>3751</td>\n",
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       "      <td>3926</td>\n",
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       "      <td>1084</td>\n",
       "      <td>2543</td>\n",
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       "      <td>...</td>\n",
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       "      <td>618</td>\n",
       "      <td>127</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>2070</td>\n",
       "      <td>331</td>\n",
       "      <td>272</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US07305</td>\n",
       "      <td>7305</td>\n",
       "      <td>53225</td>\n",
       "      <td>1791</td>\n",
       "      <td>7248</td>\n",
       "      <td>755</td>\n",
       "      <td>18997</td>\n",
       "      <td>1622</td>\n",
       "      <td>3247</td>\n",
       "      <td>844</td>\n",
       "      <td>...</td>\n",
       "      <td>3113</td>\n",
       "      <td>601</td>\n",
       "      <td>248</td>\n",
       "      <td>126</td>\n",
       "      <td>16</td>\n",
       "      <td>25</td>\n",
       "      <td>3136</td>\n",
       "      <td>549</td>\n",
       "      <td>152</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>27405</td>\n",
       "      <td>1402</td>\n",
       "      <td>6451</td>\n",
       "      <td>749</td>\n",
       "      <td>10152</td>\n",
       "      <td>1089</td>\n",
       "      <td>2697</td>\n",
       "      <td>543</td>\n",
       "      <td>...</td>\n",
       "      <td>1016</td>\n",
       "      <td>372</td>\n",
       "      <td>61</td>\n",
       "      <td>95</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>411</td>\n",
       "      <td>172</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US11201</td>\n",
       "      <td>11201</td>\n",
       "      <td>52600</td>\n",
       "      <td>1708</td>\n",
       "      <td>11693</td>\n",
       "      <td>845</td>\n",
       "      <td>22795</td>\n",
       "      <td>1370</td>\n",
       "      <td>6973</td>\n",
       "      <td>741</td>\n",
       "      <td>...</td>\n",
       "      <td>3219</td>\n",
       "      <td>466</td>\n",
       "      <td>251</td>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>899</td>\n",
       "      <td>239</td>\n",
       "      <td>71</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               geoid                             Zipcode    Total  \\\n",
       "0  06000US3604710022  Brooklyn borough, Kings County, NY  2049635   \n",
       "1       86000US07002                                7002    54196   \n",
       "2       86000US07305                                7305    53225   \n",
       "3       86000US11101                               11101    27405   \n",
       "4       86000US11201                               11201    52600   \n",
       "\n",
       "   B09021001, Error  Lives alone  B09021002, Error  \\\n",
       "0              1837       288737              3751   \n",
       "1               906         8157               832   \n",
       "2              1791         7248               755   \n",
       "3              1402         6451               749   \n",
       "4              1708        11693               845   \n",
       "\n",
       "   Householder living with spouse or spouse of householder  B09021003, Error  \\\n",
       "0                                             743459                    7989   \n",
       "1                                              23770                    1084   \n",
       "2                                              18997                    1622   \n",
       "3                                              10152                    1089   \n",
       "4                                              22795                    1370   \n",
       "\n",
       "   Householder living with unmarried partner or unmarried partner of householder  \\\n",
       "0                                             127366                               \n",
       "1                                               2543                               \n",
       "2                                               3247                               \n",
       "3                                               2697                               \n",
       "4                                               6973                               \n",
       "\n",
       "   B09021004, Error  ...  \\\n",
       "0              3926  ...   \n",
       "1               533  ...   \n",
       "2               844  ...   \n",
       "3               543  ...   \n",
       "4               741  ...   \n",
       "\n",
       "   Householder living with spouse or spouse of householder.3  \\\n",
       "0                                             147373           \n",
       "1                                               4417           \n",
       "2                                               3113           \n",
       "3                                               1016           \n",
       "4                                               3219           \n",
       "\n",
       "   B09021024, Error  \\\n",
       "0              3369   \n",
       "1               618   \n",
       "2               601   \n",
       "3               372   \n",
       "4               466   \n",
       "\n",
       "   Householder living with unmarried partner or unmarried partner of householder.3  \\\n",
       "0                                               6937                                 \n",
       "1                                                127                                 \n",
       "2                                                248                                 \n",
       "3                                                 61                                 \n",
       "4                                                251                                 \n",
       "\n",
       "   B09021025, Error  Child of householder.3  B09021026, Error  \\\n",
       "0               727                    1495               368   \n",
       "1                73                       0                31   \n",
       "2               126                      16                25   \n",
       "3                95                       0                27   \n",
       "4               121                       0                30   \n",
       "\n",
       "   Other relatives.3  B09021027, Error  Other nonrelatives.3  B09021028, Error  \n",
       "0              98707              2610                 12970              1158  \n",
       "1               2070               331                   272               156  \n",
       "2               3136               549                   152               114  \n",
       "3                411               172                    21                21  \n",
       "4                899               239                    71                61  \n",
       "\n",
       "[5 rows x 58 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "1d767bd3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# with open('acs2021_5yr_B09021.json', 'r') as file:\n",
    "#         acs_labels = json.load(file)\n",
    "# print(acs_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ed78759a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# acs_labels['tables']['B09021']['columns'].values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "04805640",
   "metadata": {},
   "outputs": [],
   "source": [
    "# labels = pd.DataFrame(acs_labels['tables']['B09021']['columns'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "19fbd723",
   "metadata": {},
   "outputs": [],
   "source": [
    "# labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "9d265e31",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_acs.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "01259a04",
   "metadata": {},
   "outputs": [],
   "source": [
    "# labels.to_csv('acs_labels.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "bded7423",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs = pd.read_csv('acs2021_5yr_B09021_86000US11230.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "403b847f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geoid</th>\n",
       "      <th>Zipcode</th>\n",
       "      <th>Total</th>\n",
       "      <th>B09021001, Error</th>\n",
       "      <th>Lives alone</th>\n",
       "      <th>B09021002, Error</th>\n",
       "      <th>Householder living with spouse or spouse of householder</th>\n",
       "      <th>B09021003, Error</th>\n",
       "      <th>Householder living with unmarried partner or unmarried partner of householder</th>\n",
       "      <th>B09021004, Error</th>\n",
       "      <th>...</th>\n",
       "      <th>Householder living with spouse or spouse of householder.3</th>\n",
       "      <th>B09021024, Error</th>\n",
       "      <th>Householder living with unmarried partner or unmarried partner of householder.3</th>\n",
       "      <th>B09021025, Error</th>\n",
       "      <th>Child of householder.3</th>\n",
       "      <th>B09021026, Error</th>\n",
       "      <th>Other relatives.3</th>\n",
       "      <th>B09021027, Error</th>\n",
       "      <th>Other nonrelatives.3</th>\n",
       "      <th>B09021028, Error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06000US3604710022</td>\n",
       "      <td>Brooklyn borough, Kings County, NY</td>\n",
       "      <td>2049635</td>\n",
       "      <td>1837</td>\n",
       "      <td>288737</td>\n",
       "      <td>3751</td>\n",
       "      <td>743459</td>\n",
       "      <td>7989</td>\n",
       "      <td>127366</td>\n",
       "      <td>3926</td>\n",
       "      <td>...</td>\n",
       "      <td>147373</td>\n",
       "      <td>3369</td>\n",
       "      <td>6937</td>\n",
       "      <td>727</td>\n",
       "      <td>1495</td>\n",
       "      <td>368</td>\n",
       "      <td>98707</td>\n",
       "      <td>2610</td>\n",
       "      <td>12970</td>\n",
       "      <td>1158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US07002</td>\n",
       "      <td>7002</td>\n",
       "      <td>54196</td>\n",
       "      <td>906</td>\n",
       "      <td>8157</td>\n",
       "      <td>832</td>\n",
       "      <td>23770</td>\n",
       "      <td>1084</td>\n",
       "      <td>2543</td>\n",
       "      <td>533</td>\n",
       "      <td>...</td>\n",
       "      <td>4417</td>\n",
       "      <td>618</td>\n",
       "      <td>127</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>2070</td>\n",
       "      <td>331</td>\n",
       "      <td>272</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US07305</td>\n",
       "      <td>7305</td>\n",
       "      <td>53225</td>\n",
       "      <td>1791</td>\n",
       "      <td>7248</td>\n",
       "      <td>755</td>\n",
       "      <td>18997</td>\n",
       "      <td>1622</td>\n",
       "      <td>3247</td>\n",
       "      <td>844</td>\n",
       "      <td>...</td>\n",
       "      <td>3113</td>\n",
       "      <td>601</td>\n",
       "      <td>248</td>\n",
       "      <td>126</td>\n",
       "      <td>16</td>\n",
       "      <td>25</td>\n",
       "      <td>3136</td>\n",
       "      <td>549</td>\n",
       "      <td>152</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>27405</td>\n",
       "      <td>1402</td>\n",
       "      <td>6451</td>\n",
       "      <td>749</td>\n",
       "      <td>10152</td>\n",
       "      <td>1089</td>\n",
       "      <td>2697</td>\n",
       "      <td>543</td>\n",
       "      <td>...</td>\n",
       "      <td>1016</td>\n",
       "      <td>372</td>\n",
       "      <td>61</td>\n",
       "      <td>95</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>411</td>\n",
       "      <td>172</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US11201</td>\n",
       "      <td>11201</td>\n",
       "      <td>52600</td>\n",
       "      <td>1708</td>\n",
       "      <td>11693</td>\n",
       "      <td>845</td>\n",
       "      <td>22795</td>\n",
       "      <td>1370</td>\n",
       "      <td>6973</td>\n",
       "      <td>741</td>\n",
       "      <td>...</td>\n",
       "      <td>3219</td>\n",
       "      <td>466</td>\n",
       "      <td>251</td>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>899</td>\n",
       "      <td>239</td>\n",
       "      <td>71</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               geoid                             Zipcode    Total  \\\n",
       "0  06000US3604710022  Brooklyn borough, Kings County, NY  2049635   \n",
       "1       86000US07002                                7002    54196   \n",
       "2       86000US07305                                7305    53225   \n",
       "3       86000US11101                               11101    27405   \n",
       "4       86000US11201                               11201    52600   \n",
       "\n",
       "   B09021001, Error  Lives alone  B09021002, Error  \\\n",
       "0              1837       288737              3751   \n",
       "1               906         8157               832   \n",
       "2              1791         7248               755   \n",
       "3              1402         6451               749   \n",
       "4              1708        11693               845   \n",
       "\n",
       "   Householder living with spouse or spouse of householder  B09021003, Error  \\\n",
       "0                                             743459                    7989   \n",
       "1                                              23770                    1084   \n",
       "2                                              18997                    1622   \n",
       "3                                              10152                    1089   \n",
       "4                                              22795                    1370   \n",
       "\n",
       "   Householder living with unmarried partner or unmarried partner of householder  \\\n",
       "0                                             127366                               \n",
       "1                                               2543                               \n",
       "2                                               3247                               \n",
       "3                                               2697                               \n",
       "4                                               6973                               \n",
       "\n",
       "   B09021004, Error  ...  \\\n",
       "0              3926  ...   \n",
       "1               533  ...   \n",
       "2               844  ...   \n",
       "3               543  ...   \n",
       "4               741  ...   \n",
       "\n",
       "   Householder living with spouse or spouse of householder.3  \\\n",
       "0                                             147373           \n",
       "1                                               4417           \n",
       "2                                               3113           \n",
       "3                                               1016           \n",
       "4                                               3219           \n",
       "\n",
       "   B09021024, Error  \\\n",
       "0              3369   \n",
       "1               618   \n",
       "2               601   \n",
       "3               372   \n",
       "4               466   \n",
       "\n",
       "   Householder living with unmarried partner or unmarried partner of householder.3  \\\n",
       "0                                               6937                                 \n",
       "1                                                127                                 \n",
       "2                                                248                                 \n",
       "3                                                 61                                 \n",
       "4                                                251                                 \n",
       "\n",
       "   B09021025, Error  Child of householder.3  B09021026, Error  \\\n",
       "0               727                    1495               368   \n",
       "1                73                       0                31   \n",
       "2               126                      16                25   \n",
       "3                95                       0                27   \n",
       "4               121                       0                30   \n",
       "\n",
       "   Other relatives.3  B09021027, Error  Other nonrelatives.3  B09021028, Error  \n",
       "0              98707              2610                 12970              1158  \n",
       "1               2070               331                   272               156  \n",
       "2               3136               549                   152               114  \n",
       "3                411               172                    21                21  \n",
       "4                899               239                    71                61  \n",
       "\n",
       "[5 rows x 58 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "d90aad22",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs.columns = df_acs.columns.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "3db4e882",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>geoid</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>total</th>\n",
       "      <th>b09021001, error</th>\n",
       "      <th>lives alone</th>\n",
       "      <th>b09021002, error</th>\n",
       "      <th>householder living with spouse or spouse of householder</th>\n",
       "      <th>b09021003, error</th>\n",
       "      <th>householder living with unmarried partner or unmarried partner of householder</th>\n",
       "      <th>b09021004, error</th>\n",
       "      <th>...</th>\n",
       "      <th>householder living with spouse or spouse of householder.3</th>\n",
       "      <th>b09021024, error</th>\n",
       "      <th>householder living with unmarried partner or unmarried partner of householder.3</th>\n",
       "      <th>b09021025, error</th>\n",
       "      <th>child of householder.3</th>\n",
       "      <th>b09021026, error</th>\n",
       "      <th>other relatives.3</th>\n",
       "      <th>b09021027, error</th>\n",
       "      <th>other nonrelatives.3</th>\n",
       "      <th>b09021028, error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06000US3604710022</td>\n",
       "      <td>Brooklyn borough, Kings County, NY</td>\n",
       "      <td>2049635</td>\n",
       "      <td>1837</td>\n",
       "      <td>288737</td>\n",
       "      <td>3751</td>\n",
       "      <td>743459</td>\n",
       "      <td>7989</td>\n",
       "      <td>127366</td>\n",
       "      <td>3926</td>\n",
       "      <td>...</td>\n",
       "      <td>147373</td>\n",
       "      <td>3369</td>\n",
       "      <td>6937</td>\n",
       "      <td>727</td>\n",
       "      <td>1495</td>\n",
       "      <td>368</td>\n",
       "      <td>98707</td>\n",
       "      <td>2610</td>\n",
       "      <td>12970</td>\n",
       "      <td>1158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US07002</td>\n",
       "      <td>7002</td>\n",
       "      <td>54196</td>\n",
       "      <td>906</td>\n",
       "      <td>8157</td>\n",
       "      <td>832</td>\n",
       "      <td>23770</td>\n",
       "      <td>1084</td>\n",
       "      <td>2543</td>\n",
       "      <td>533</td>\n",
       "      <td>...</td>\n",
       "      <td>4417</td>\n",
       "      <td>618</td>\n",
       "      <td>127</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>2070</td>\n",
       "      <td>331</td>\n",
       "      <td>272</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US07305</td>\n",
       "      <td>7305</td>\n",
       "      <td>53225</td>\n",
       "      <td>1791</td>\n",
       "      <td>7248</td>\n",
       "      <td>755</td>\n",
       "      <td>18997</td>\n",
       "      <td>1622</td>\n",
       "      <td>3247</td>\n",
       "      <td>844</td>\n",
       "      <td>...</td>\n",
       "      <td>3113</td>\n",
       "      <td>601</td>\n",
       "      <td>248</td>\n",
       "      <td>126</td>\n",
       "      <td>16</td>\n",
       "      <td>25</td>\n",
       "      <td>3136</td>\n",
       "      <td>549</td>\n",
       "      <td>152</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               geoid                             zipcode    total  \\\n",
       "0  06000US3604710022  Brooklyn borough, Kings County, NY  2049635   \n",
       "1       86000US07002                                7002    54196   \n",
       "2       86000US07305                                7305    53225   \n",
       "\n",
       "   b09021001, error  lives alone  b09021002, error  \\\n",
       "0              1837       288737              3751   \n",
       "1               906         8157               832   \n",
       "2              1791         7248               755   \n",
       "\n",
       "   householder living with spouse or spouse of householder  b09021003, error  \\\n",
       "0                                             743459                    7989   \n",
       "1                                              23770                    1084   \n",
       "2                                              18997                    1622   \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder  \\\n",
       "0                                             127366                               \n",
       "1                                               2543                               \n",
       "2                                               3247                               \n",
       "\n",
       "   b09021004, error  ...  \\\n",
       "0              3926  ...   \n",
       "1               533  ...   \n",
       "2               844  ...   \n",
       "\n",
       "   householder living with spouse or spouse of householder.3  \\\n",
       "0                                             147373           \n",
       "1                                               4417           \n",
       "2                                               3113           \n",
       "\n",
       "   b09021024, error  \\\n",
       "0              3369   \n",
       "1               618   \n",
       "2               601   \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder.3  \\\n",
       "0                                               6937                                 \n",
       "1                                                127                                 \n",
       "2                                                248                                 \n",
       "\n",
       "   b09021025, error  child of householder.3  b09021026, error  \\\n",
       "0               727                    1495               368   \n",
       "1                73                       0                31   \n",
       "2               126                      16                25   \n",
       "\n",
       "   other relatives.3  b09021027, error  other nonrelatives.3  b09021028, error  \n",
       "0              98707              2610                 12970              1158  \n",
       "1               2070               331                   272               156  \n",
       "2               3136               549                   152               114  \n",
       "\n",
       "[3 rows x 58 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "235cad91",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs = df_acs.iloc[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "0c00b3c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>geoid</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>total</th>\n",
       "      <th>b09021001, error</th>\n",
       "      <th>lives alone</th>\n",
       "      <th>b09021002, error</th>\n",
       "      <th>householder living with spouse or spouse of householder</th>\n",
       "      <th>b09021003, error</th>\n",
       "      <th>householder living with unmarried partner or unmarried partner of householder</th>\n",
       "      <th>b09021004, error</th>\n",
       "      <th>...</th>\n",
       "      <th>householder living with spouse or spouse of householder.3</th>\n",
       "      <th>b09021024, error</th>\n",
       "      <th>householder living with unmarried partner or unmarried partner of householder.3</th>\n",
       "      <th>b09021025, error</th>\n",
       "      <th>child of householder.3</th>\n",
       "      <th>b09021026, error</th>\n",
       "      <th>other relatives.3</th>\n",
       "      <th>b09021027, error</th>\n",
       "      <th>other nonrelatives.3</th>\n",
       "      <th>b09021028, error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US07002</td>\n",
       "      <td>7002</td>\n",
       "      <td>54196</td>\n",
       "      <td>906</td>\n",
       "      <td>8157</td>\n",
       "      <td>832</td>\n",
       "      <td>23770</td>\n",
       "      <td>1084</td>\n",
       "      <td>2543</td>\n",
       "      <td>533</td>\n",
       "      <td>...</td>\n",
       "      <td>4417</td>\n",
       "      <td>618</td>\n",
       "      <td>127</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>2070</td>\n",
       "      <td>331</td>\n",
       "      <td>272</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US07305</td>\n",
       "      <td>7305</td>\n",
       "      <td>53225</td>\n",
       "      <td>1791</td>\n",
       "      <td>7248</td>\n",
       "      <td>755</td>\n",
       "      <td>18997</td>\n",
       "      <td>1622</td>\n",
       "      <td>3247</td>\n",
       "      <td>844</td>\n",
       "      <td>...</td>\n",
       "      <td>3113</td>\n",
       "      <td>601</td>\n",
       "      <td>248</td>\n",
       "      <td>126</td>\n",
       "      <td>16</td>\n",
       "      <td>25</td>\n",
       "      <td>3136</td>\n",
       "      <td>549</td>\n",
       "      <td>152</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>27405</td>\n",
       "      <td>1402</td>\n",
       "      <td>6451</td>\n",
       "      <td>749</td>\n",
       "      <td>10152</td>\n",
       "      <td>1089</td>\n",
       "      <td>2697</td>\n",
       "      <td>543</td>\n",
       "      <td>...</td>\n",
       "      <td>1016</td>\n",
       "      <td>372</td>\n",
       "      <td>61</td>\n",
       "      <td>95</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>411</td>\n",
       "      <td>172</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US11201</td>\n",
       "      <td>11201</td>\n",
       "      <td>52600</td>\n",
       "      <td>1708</td>\n",
       "      <td>11693</td>\n",
       "      <td>845</td>\n",
       "      <td>22795</td>\n",
       "      <td>1370</td>\n",
       "      <td>6973</td>\n",
       "      <td>741</td>\n",
       "      <td>...</td>\n",
       "      <td>3219</td>\n",
       "      <td>466</td>\n",
       "      <td>251</td>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>899</td>\n",
       "      <td>239</td>\n",
       "      <td>71</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86000US11203</td>\n",
       "      <td>11203</td>\n",
       "      <td>62279</td>\n",
       "      <td>2066</td>\n",
       "      <td>8376</td>\n",
       "      <td>590</td>\n",
       "      <td>18095</td>\n",
       "      <td>1065</td>\n",
       "      <td>2343</td>\n",
       "      <td>535</td>\n",
       "      <td>...</td>\n",
       "      <td>5640</td>\n",
       "      <td>583</td>\n",
       "      <td>283</td>\n",
       "      <td>110</td>\n",
       "      <td>47</td>\n",
       "      <td>34</td>\n",
       "      <td>4271</td>\n",
       "      <td>503</td>\n",
       "      <td>477</td>\n",
       "      <td>195</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid zipcode  total  b09021001, error  lives alone  \\\n",
       "1  86000US07002    7002  54196               906         8157   \n",
       "2  86000US07305    7305  53225              1791         7248   \n",
       "3  86000US11101   11101  27405              1402         6451   \n",
       "4  86000US11201   11201  52600              1708        11693   \n",
       "5  86000US11203   11203  62279              2066         8376   \n",
       "\n",
       "   b09021002, error  householder living with spouse or spouse of householder  \\\n",
       "1               832                                              23770         \n",
       "2               755                                              18997         \n",
       "3               749                                              10152         \n",
       "4               845                                              22795         \n",
       "5               590                                              18095         \n",
       "\n",
       "   b09021003, error  \\\n",
       "1              1084   \n",
       "2              1622   \n",
       "3              1089   \n",
       "4              1370   \n",
       "5              1065   \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder  \\\n",
       "1                                               2543                               \n",
       "2                                               3247                               \n",
       "3                                               2697                               \n",
       "4                                               6973                               \n",
       "5                                               2343                               \n",
       "\n",
       "   b09021004, error  ...  \\\n",
       "1               533  ...   \n",
       "2               844  ...   \n",
       "3               543  ...   \n",
       "4               741  ...   \n",
       "5               535  ...   \n",
       "\n",
       "   householder living with spouse or spouse of householder.3  \\\n",
       "1                                               4417           \n",
       "2                                               3113           \n",
       "3                                               1016           \n",
       "4                                               3219           \n",
       "5                                               5640           \n",
       "\n",
       "   b09021024, error  \\\n",
       "1               618   \n",
       "2               601   \n",
       "3               372   \n",
       "4               466   \n",
       "5               583   \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder.3  \\\n",
       "1                                                127                                 \n",
       "2                                                248                                 \n",
       "3                                                 61                                 \n",
       "4                                                251                                 \n",
       "5                                                283                                 \n",
       "\n",
       "   b09021025, error  child of householder.3  b09021026, error  \\\n",
       "1                73                       0                31   \n",
       "2               126                      16                25   \n",
       "3                95                       0                27   \n",
       "4               121                       0                30   \n",
       "5               110                      47                34   \n",
       "\n",
       "   other relatives.3  b09021027, error  other nonrelatives.3  b09021028, error  \n",
       "1               2070               331                   272               156  \n",
       "2               3136               549                   152               114  \n",
       "3                411               172                    21                21  \n",
       "4                899               239                    71                61  \n",
       "5               4271               503                   477               195  \n",
       "\n",
       "[5 rows x 58 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "60a59b40",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs.reset_index(drop = True, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "e8a694c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>geoid</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>total</th>\n",
       "      <th>b09021001, error</th>\n",
       "      <th>lives alone</th>\n",
       "      <th>b09021002, error</th>\n",
       "      <th>householder living with spouse or spouse of householder</th>\n",
       "      <th>b09021003, error</th>\n",
       "      <th>householder living with unmarried partner or unmarried partner of householder</th>\n",
       "      <th>b09021004, error</th>\n",
       "      <th>...</th>\n",
       "      <th>householder living with spouse or spouse of householder.3</th>\n",
       "      <th>b09021024, error</th>\n",
       "      <th>householder living with unmarried partner or unmarried partner of householder.3</th>\n",
       "      <th>b09021025, error</th>\n",
       "      <th>child of householder.3</th>\n",
       "      <th>b09021026, error</th>\n",
       "      <th>other relatives.3</th>\n",
       "      <th>b09021027, error</th>\n",
       "      <th>other nonrelatives.3</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86000US07002</td>\n",
       "      <td>7002</td>\n",
       "      <td>54196</td>\n",
       "      <td>906</td>\n",
       "      <td>8157</td>\n",
       "      <td>832</td>\n",
       "      <td>23770</td>\n",
       "      <td>1084</td>\n",
       "      <td>2543</td>\n",
       "      <td>533</td>\n",
       "      <td>...</td>\n",
       "      <td>4417</td>\n",
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       "      <td>127</td>\n",
       "      <td>73</td>\n",
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       "      <td>31</td>\n",
       "      <td>2070</td>\n",
       "      <td>331</td>\n",
       "      <td>272</td>\n",
       "      <td>156</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid zipcode  total  b09021001, error  lives alone  \\\n",
       "0  86000US07002    7002  54196               906         8157   \n",
       "\n",
       "   b09021002, error  householder living with spouse or spouse of householder  \\\n",
       "0               832                                              23770         \n",
       "\n",
       "   b09021003, error  \\\n",
       "0              1084   \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder  \\\n",
       "0                                               2543                               \n",
       "\n",
       "   b09021004, error  ...  \\\n",
       "0               533  ...   \n",
       "\n",
       "   householder living with spouse or spouse of householder.3  \\\n",
       "0                                               4417           \n",
       "\n",
       "   b09021024, error  \\\n",
       "0               618   \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder.3  \\\n",
       "0                                                127                                 \n",
       "\n",
       "   b09021025, error  child of householder.3  b09021026, error  \\\n",
       "0                73                       0                31   \n",
       "\n",
       "   other relatives.3  b09021027, error  other nonrelatives.3  b09021028, error  \n",
       "0               2070               331                   272               156  \n",
       "\n",
       "[1 rows x 58 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs[df_acs.zipcode == '7002']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "7e1d7f02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['geoid', 'zipcode', 'total', 'b09021001, error', 'lives alone',\n",
       "       'b09021002, error',\n",
       "       'householder living with spouse or spouse of householder',\n",
       "       'b09021003, error',\n",
       "       'householder living with unmarried partner or unmarried partner of householder',\n",
       "       'b09021004, error', 'child of householder', 'b09021005, error',\n",
       "       'other relatives', 'b09021006, error', 'other nonrelatives',\n",
       "       'b09021007, error', '18 to 34 years:', 'b09021008, error',\n",
       "       'lives alone.1', 'b09021009, error',\n",
       "       'householder living with spouse or spouse of householder.1',\n",
       "       'b09021010, error',\n",
       "       'householder living with unmarried partner or unmarried partner of householder.1',\n",
       "       'b09021011, error', 'child of householder.1', 'b09021012, error',\n",
       "       'other relatives.1', 'b09021013, error', 'other nonrelatives.1',\n",
       "       'b09021014, error', '35 to 64 years:', 'b09021015, error',\n",
       "       'lives alone.2', 'b09021016, error',\n",
       "       'householder living with spouse or spouse of householder.2',\n",
       "       'b09021017, error',\n",
       "       'householder living with unmarried partner or unmarried partner of householder.2',\n",
       "       'b09021018, error', 'child of householder.2', 'b09021019, error',\n",
       "       'other relatives.2', 'b09021020, error', 'other nonrelatives.2',\n",
       "       'b09021021, error', '65 years and over:', 'b09021022, error',\n",
       "       'lives alone.3', 'b09021023, error',\n",
       "       'householder living with spouse or spouse of householder.3',\n",
       "       'b09021024, error',\n",
       "       'householder living with unmarried partner or unmarried partner of householder.3',\n",
       "       'b09021025, error', 'child of householder.3', 'b09021026, error',\n",
       "       'other relatives.3', 'b09021027, error', 'other nonrelatives.3',\n",
       "       'b09021028, error'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "f0a07dc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs.columns = [re.sub(r'\\W+', '', col.strip().lower()) if 'error' in col.lower() else col for col in df_acs.columns]\n",
    "filtered_columns = [col for col in df_acs.columns if 'error' not in col.lower()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "eb786bf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs_filtered = df_acs[filtered_columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "f82898e0",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geoid</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>total</th>\n",
       "      <th>lives alone</th>\n",
       "      <th>householder living with spouse or spouse of householder</th>\n",
       "      <th>householder living with unmarried partner or unmarried partner of householder</th>\n",
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       "      <th>18 to 34 years:</th>\n",
       "      <th>...</th>\n",
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       "      <th>65 years and over:</th>\n",
       "      <th>lives alone.3</th>\n",
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       "      <th>householder living with unmarried partner or unmarried partner of householder.3</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86000US07002</td>\n",
       "      <td>7002</td>\n",
       "      <td>54196</td>\n",
       "      <td>8157</td>\n",
       "      <td>23770</td>\n",
       "      <td>2543</td>\n",
       "      <td>7490</td>\n",
       "      <td>9911</td>\n",
       "      <td>2325</td>\n",
       "      <td>15402</td>\n",
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       "      <td>1164</td>\n",
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       "      <td>3198</td>\n",
       "      <td>4417</td>\n",
       "      <td>127</td>\n",
       "      <td>0</td>\n",
       "      <td>2070</td>\n",
       "      <td>272</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US07305</td>\n",
       "      <td>7305</td>\n",
       "      <td>53225</td>\n",
       "      <td>7248</td>\n",
       "      <td>18997</td>\n",
       "      <td>3247</td>\n",
       "      <td>8626</td>\n",
       "      <td>12269</td>\n",
       "      <td>2838</td>\n",
       "      <td>17113</td>\n",
       "      <td>...</td>\n",
       "      <td>1598</td>\n",
       "      <td>5916</td>\n",
       "      <td>1368</td>\n",
       "      <td>9730</td>\n",
       "      <td>3065</td>\n",
       "      <td>3113</td>\n",
       "      <td>248</td>\n",
       "      <td>16</td>\n",
       "      <td>3136</td>\n",
       "      <td>152</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US11101</td>\n",
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       "      <td>6451</td>\n",
       "      <td>10152</td>\n",
       "      <td>2697</td>\n",
       "      <td>1617</td>\n",
       "      <td>3384</td>\n",
       "      <td>3104</td>\n",
       "      <td>11862</td>\n",
       "      <td>...</td>\n",
       "      <td>279</td>\n",
       "      <td>1970</td>\n",
       "      <td>889</td>\n",
       "      <td>2523</td>\n",
       "      <td>1014</td>\n",
       "      <td>1016</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>411</td>\n",
       "      <td>21</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US11201</td>\n",
       "      <td>11201</td>\n",
       "      <td>52600</td>\n",
       "      <td>11693</td>\n",
       "      <td>22795</td>\n",
       "      <td>6973</td>\n",
       "      <td>2394</td>\n",
       "      <td>4719</td>\n",
       "      <td>4026</td>\n",
       "      <td>18784</td>\n",
       "      <td>...</td>\n",
       "      <td>354</td>\n",
       "      <td>2628</td>\n",
       "      <td>833</td>\n",
       "      <td>7503</td>\n",
       "      <td>3063</td>\n",
       "      <td>3219</td>\n",
       "      <td>251</td>\n",
       "      <td>0</td>\n",
       "      <td>899</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US11203</td>\n",
       "      <td>11203</td>\n",
       "      <td>62279</td>\n",
       "      <td>8376</td>\n",
       "      <td>18095</td>\n",
       "      <td>2343</td>\n",
       "      <td>12599</td>\n",
       "      <td>17988</td>\n",
       "      <td>2878</td>\n",
       "      <td>17409</td>\n",
       "      <td>...</td>\n",
       "      <td>4033</td>\n",
       "      <td>9132</td>\n",
       "      <td>1323</td>\n",
       "      <td>14080</td>\n",
       "      <td>3362</td>\n",
       "      <td>5640</td>\n",
       "      <td>283</td>\n",
       "      <td>47</td>\n",
       "      <td>4271</td>\n",
       "      <td>477</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid zipcode  total  lives alone  \\\n",
       "0  86000US07002    7002  54196         8157   \n",
       "1  86000US07305    7305  53225         7248   \n",
       "2  86000US11101   11101  27405         6451   \n",
       "3  86000US11201   11201  52600        11693   \n",
       "4  86000US11203   11203  62279         8376   \n",
       "\n",
       "   householder living with spouse or spouse of householder  \\\n",
       "0                                              23770         \n",
       "1                                              18997         \n",
       "2                                              10152         \n",
       "3                                              22795         \n",
       "4                                              18095         \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder  \\\n",
       "0                                               2543                               \n",
       "1                                               3247                               \n",
       "2                                               2697                               \n",
       "3                                               6973                               \n",
       "4                                               2343                               \n",
       "\n",
       "   child of householder  other relatives  other nonrelatives  18 to 34 years:  \\\n",
       "0                  7490             9911                2325            15402   \n",
       "1                  8626            12269                2838            17113   \n",
       "2                  1617             3384                3104            11862   \n",
       "3                  2394             4719                4026            18784   \n",
       "4                 12599            17988                2878            17409   \n",
       "\n",
       "   ...  child of householder.2  other relatives.2  other nonrelatives.2  \\\n",
       "0  ...                    1164               5725                  1185   \n",
       "1  ...                    1598               5916                  1368   \n",
       "2  ...                     279               1970                   889   \n",
       "3  ...                     354               2628                   833   \n",
       "4  ...                    4033               9132                  1323   \n",
       "\n",
       "   65 years and over:  lives alone.3  \\\n",
       "0               10084           3198   \n",
       "1                9730           3065   \n",
       "2                2523           1014   \n",
       "3                7503           3063   \n",
       "4               14080           3362   \n",
       "\n",
       "   householder living with spouse or spouse of householder.3  \\\n",
       "0                                               4417           \n",
       "1                                               3113           \n",
       "2                                               1016           \n",
       "3                                               3219           \n",
       "4                                               5640           \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder.3  \\\n",
       "0                                                127                                 \n",
       "1                                                248                                 \n",
       "2                                                 61                                 \n",
       "3                                                251                                 \n",
       "4                                                283                                 \n",
       "\n",
       "   child of householder.3  other relatives.3  other nonrelatives.3  \n",
       "0                       0               2070                   272  \n",
       "1                      16               3136                   152  \n",
       "2                       0                411                    21  \n",
       "3                       0                899                    71  \n",
       "4                      47               4271                   477  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs_filtered.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36e58fa9",
   "metadata": {},
   "source": [
    "# Analysis and Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "dcf2d51d",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_zipcodes = ['11215', '11217', '11225', '11218','11226','11238']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "a1fc5fc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs_selected_zipcodes = df_acs_filtered[df_acs_filtered['zipcode'].isin(selected_zipcodes)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b31d474a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs_selected_zipcodes.reset_index(drop = True, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "abf78202",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geoid</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>total</th>\n",
       "      <th>lives alone</th>\n",
       "      <th>householder living with spouse or spouse of householder</th>\n",
       "      <th>householder living with unmarried partner or unmarried partner of householder</th>\n",
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       "      <th>18 to 34 years:</th>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86000US11215</td>\n",
       "      <td>11215</td>\n",
       "      <td>56580</td>\n",
       "      <td>7522</td>\n",
       "      <td>29844</td>\n",
       "      <td>5705</td>\n",
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       "      <td>4359</td>\n",
       "      <td>5789</td>\n",
       "      <td>16567</td>\n",
       "      <td>...</td>\n",
       "      <td>672</td>\n",
       "      <td>2357</td>\n",
       "      <td>1552</td>\n",
       "      <td>7889</td>\n",
       "      <td>1684</td>\n",
       "      <td>4468</td>\n",
       "      <td>243</td>\n",
       "      <td>11</td>\n",
       "      <td>1104</td>\n",
       "      <td>379</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US11217</td>\n",
       "      <td>11217</td>\n",
       "      <td>33427</td>\n",
       "      <td>6388</td>\n",
       "      <td>12215</td>\n",
       "      <td>4630</td>\n",
       "      <td>2308</td>\n",
       "      <td>3794</td>\n",
       "      <td>4092</td>\n",
       "      <td>12560</td>\n",
       "      <td>...</td>\n",
       "      <td>454</td>\n",
       "      <td>2017</td>\n",
       "      <td>1163</td>\n",
       "      <td>4482</td>\n",
       "      <td>1361</td>\n",
       "      <td>1823</td>\n",
       "      <td>169</td>\n",
       "      <td>34</td>\n",
       "      <td>879</td>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US11218</td>\n",
       "      <td>11218</td>\n",
       "      <td>54613</td>\n",
       "      <td>6965</td>\n",
       "      <td>25500</td>\n",
       "      <td>2770</td>\n",
       "      <td>7418</td>\n",
       "      <td>8187</td>\n",
       "      <td>3773</td>\n",
       "      <td>15461</td>\n",
       "      <td>...</td>\n",
       "      <td>1474</td>\n",
       "      <td>3742</td>\n",
       "      <td>1260</td>\n",
       "      <td>9352</td>\n",
       "      <td>2521</td>\n",
       "      <td>3738</td>\n",
       "      <td>200</td>\n",
       "      <td>30</td>\n",
       "      <td>2618</td>\n",
       "      <td>245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US11225</td>\n",
       "      <td>11225</td>\n",
       "      <td>48984</td>\n",
       "      <td>8978</td>\n",
       "      <td>12766</td>\n",
       "      <td>3832</td>\n",
       "      <td>6997</td>\n",
       "      <td>10241</td>\n",
       "      <td>6170</td>\n",
       "      <td>18374</td>\n",
       "      <td>...</td>\n",
       "      <td>1815</td>\n",
       "      <td>4358</td>\n",
       "      <td>1291</td>\n",
       "      <td>9414</td>\n",
       "      <td>3194</td>\n",
       "      <td>2605</td>\n",
       "      <td>156</td>\n",
       "      <td>45</td>\n",
       "      <td>3121</td>\n",
       "      <td>293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US11226</td>\n",
       "      <td>11226</td>\n",
       "      <td>78956</td>\n",
       "      <td>11590</td>\n",
       "      <td>20624</td>\n",
       "      <td>4652</td>\n",
       "      <td>13136</td>\n",
       "      <td>20512</td>\n",
       "      <td>8442</td>\n",
       "      <td>28997</td>\n",
       "      <td>...</td>\n",
       "      <td>3213</td>\n",
       "      <td>10028</td>\n",
       "      <td>2535</td>\n",
       "      <td>12353</td>\n",
       "      <td>3147</td>\n",
       "      <td>3543</td>\n",
       "      <td>250</td>\n",
       "      <td>42</td>\n",
       "      <td>4913</td>\n",
       "      <td>458</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86000US11238</td>\n",
       "      <td>11238</td>\n",
       "      <td>47998</td>\n",
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       "      <td>16884</td>\n",
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       "      <td>4747</td>\n",
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       "      <td>2441</td>\n",
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       "      <td>2182</td>\n",
       "      <td>2120</td>\n",
       "      <td>272</td>\n",
       "      <td>7</td>\n",
       "      <td>1421</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid zipcode  total  lives alone  \\\n",
       "0  86000US11215   11215  56580         7522   \n",
       "1  86000US11217   11217  33427         6388   \n",
       "2  86000US11218   11218  54613         6965   \n",
       "3  86000US11225   11225  48984         8978   \n",
       "4  86000US11226   11226  78956        11590   \n",
       "5  86000US11238   11238  47998         9299   \n",
       "\n",
       "   householder living with spouse or spouse of householder  \\\n",
       "0                                              29844         \n",
       "1                                              12215         \n",
       "2                                              25500         \n",
       "3                                              12766         \n",
       "4                                              20624         \n",
       "5                                              16884         \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder  \\\n",
       "0                                               5705                               \n",
       "1                                               4630                               \n",
       "2                                               2770                               \n",
       "3                                               3832                               \n",
       "4                                               4652                               \n",
       "5                                               5428                               \n",
       "\n",
       "   child of householder  other relatives  other nonrelatives  18 to 34 years:  \\\n",
       "0                  3361             4359                5789            16567   \n",
       "1                  2308             3794                4092            12560   \n",
       "2                  7418             8187                3773            15461   \n",
       "3                  6997            10241                6170            18374   \n",
       "4                 13136            20512                8442            28997   \n",
       "5                  3323             4747                8317            19005   \n",
       "\n",
       "   ...  child of householder.2  other relatives.2  other nonrelatives.2  \\\n",
       "0  ...                     672               2357                  1552   \n",
       "1  ...                     454               2017                  1163   \n",
       "2  ...                    1474               3742                  1260   \n",
       "3  ...                    1815               4358                  1291   \n",
       "4  ...                    3213              10028                  2535   \n",
       "5  ...                    1062               2441                  1544   \n",
       "\n",
       "   65 years and over:  lives alone.3  \\\n",
       "0                7889           1684   \n",
       "1                4482           1361   \n",
       "2                9352           2521   \n",
       "3                9414           3194   \n",
       "4               12353           3147   \n",
       "5                6352           2182   \n",
       "\n",
       "   householder living with spouse or spouse of householder.3  \\\n",
       "0                                               4468           \n",
       "1                                               1823           \n",
       "2                                               3738           \n",
       "3                                               2605           \n",
       "4                                               3543           \n",
       "5                                               2120           \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder.3  \\\n",
       "0                                                243                                 \n",
       "1                                                169                                 \n",
       "2                                                200                                 \n",
       "3                                                156                                 \n",
       "4                                                250                                 \n",
       "5                                                272                                 \n",
       "\n",
       "   child of householder.3  other relatives.3  other nonrelatives.3  \n",
       "0                      11               1104                   379  \n",
       "1                      34                879                   216  \n",
       "2                      30               2618                   245  \n",
       "3                      45               3121                   293  \n",
       "4                      42               4913                   458  \n",
       "5                       7               1421                   350  \n",
       "\n",
       "[6 rows x 30 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs_selected_zipcodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "3a2229b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_bk_income_selected.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "5e2349fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_acs_selected_zipcodes.to_csv('acs_living_selected_zipcodes.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "60bb6408",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/km/gmzkf_4n5qn6c84ksf3bzy0c0000gn/T/ipykernel_84608/391628179.py:24: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_acs_selected_zipcodes.rename(columns=column_names, inplace=True)\n"
     ]
    }
   ],
   "source": [
    "# Define the new column names mapping\n",
    "column_names = {\n",
    "    'lives alone.1': 'lives alone 18-34',\n",
    "    'householder living with spouse or spouse of householder.1': 'householder with spouse 18-34',\n",
    "    'householder living with unmarried partner or unmarried partner of householder.1': 'householder with partner 18-34',\n",
    "    'child of householder.1': 'child of householder 18-34',\n",
    "    'other relatives.1': 'other relatives 18-34',\n",
    "    'other nonrelatives.1': 'other nonrelatives 18-34',\n",
    "    'lives alone.2': 'lives alone 35-64',\n",
    "    'householder living with spouse or spouse of householder.2': 'householder with spouse 35-64',\n",
    "    'householder living with unmarried partner or unmarried partner of householder.2': 'householder with partner 35-64',\n",
    "    'child of householder.2': 'child of householder 35-64',\n",
    "    'other relatives.2': 'other relatives 35-64',\n",
    "    'other nonrelatives.2': 'other nonrelatives 35-64',\n",
    "    'lives alone.3': 'lives alone 65+',\n",
    "    'householder living with spouse or spouse of householder.3': 'householder with spouse 65+',\n",
    "    'householder living with unmarried partner or unmarried partner of householder.3': 'householder with partner 65+',\n",
    "    'child of householder.3': 'child of householder 65+',\n",
    "    'other relatives.3': 'other relatives 65+',\n",
    "    'other nonrelatives.3': 'other nonrelatives 65+'\n",
    "}\n",
    "\n",
    "# Rename the columns\n",
    "df_acs_selected_zipcodes.rename(columns=column_names, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "dcd89e2a",
   "metadata": {},
   "outputs": [
    {
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       "      <td>86000US11217</td>\n",
       "      <td>11217</td>\n",
       "      <td>33427</td>\n",
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       "      <td>4630</td>\n",
       "      <td>2308</td>\n",
       "      <td>3794</td>\n",
       "      <td>4092</td>\n",
       "      <td>12560</td>\n",
       "      <td>...</td>\n",
       "      <td>454</td>\n",
       "      <td>2017</td>\n",
       "      <td>1163</td>\n",
       "      <td>4482</td>\n",
       "      <td>1361</td>\n",
       "      <td>1823</td>\n",
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       "      <th>2</th>\n",
       "      <td>86000US11218</td>\n",
       "      <td>11218</td>\n",
       "      <td>54613</td>\n",
       "      <td>6965</td>\n",
       "      <td>25500</td>\n",
       "      <td>2770</td>\n",
       "      <td>7418</td>\n",
       "      <td>8187</td>\n",
       "      <td>3773</td>\n",
       "      <td>15461</td>\n",
       "      <td>...</td>\n",
       "      <td>1474</td>\n",
       "      <td>3742</td>\n",
       "      <td>1260</td>\n",
       "      <td>9352</td>\n",
       "      <td>2521</td>\n",
       "      <td>3738</td>\n",
       "      <td>200</td>\n",
       "      <td>30</td>\n",
       "      <td>2618</td>\n",
       "      <td>245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US11225</td>\n",
       "      <td>11225</td>\n",
       "      <td>48984</td>\n",
       "      <td>8978</td>\n",
       "      <td>12766</td>\n",
       "      <td>3832</td>\n",
       "      <td>6997</td>\n",
       "      <td>10241</td>\n",
       "      <td>6170</td>\n",
       "      <td>18374</td>\n",
       "      <td>...</td>\n",
       "      <td>1815</td>\n",
       "      <td>4358</td>\n",
       "      <td>1291</td>\n",
       "      <td>9414</td>\n",
       "      <td>3194</td>\n",
       "      <td>2605</td>\n",
       "      <td>156</td>\n",
       "      <td>45</td>\n",
       "      <td>3121</td>\n",
       "      <td>293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US11226</td>\n",
       "      <td>11226</td>\n",
       "      <td>78956</td>\n",
       "      <td>11590</td>\n",
       "      <td>20624</td>\n",
       "      <td>4652</td>\n",
       "      <td>13136</td>\n",
       "      <td>20512</td>\n",
       "      <td>8442</td>\n",
       "      <td>28997</td>\n",
       "      <td>...</td>\n",
       "      <td>3213</td>\n",
       "      <td>10028</td>\n",
       "      <td>2535</td>\n",
       "      <td>12353</td>\n",
       "      <td>3147</td>\n",
       "      <td>3543</td>\n",
       "      <td>250</td>\n",
       "      <td>42</td>\n",
       "      <td>4913</td>\n",
       "      <td>458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86000US11238</td>\n",
       "      <td>11238</td>\n",
       "      <td>47998</td>\n",
       "      <td>9299</td>\n",
       "      <td>16884</td>\n",
       "      <td>5428</td>\n",
       "      <td>3323</td>\n",
       "      <td>4747</td>\n",
       "      <td>8317</td>\n",
       "      <td>19005</td>\n",
       "      <td>...</td>\n",
       "      <td>1062</td>\n",
       "      <td>2441</td>\n",
       "      <td>1544</td>\n",
       "      <td>6352</td>\n",
       "      <td>2182</td>\n",
       "      <td>2120</td>\n",
       "      <td>272</td>\n",
       "      <td>7</td>\n",
       "      <td>1421</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid zipcode  total  lives alone  \\\n",
       "0  86000US11215   11215  56580         7522   \n",
       "1  86000US11217   11217  33427         6388   \n",
       "2  86000US11218   11218  54613         6965   \n",
       "3  86000US11225   11225  48984         8978   \n",
       "4  86000US11226   11226  78956        11590   \n",
       "5  86000US11238   11238  47998         9299   \n",
       "\n",
       "   householder living with spouse or spouse of householder  \\\n",
       "0                                              29844         \n",
       "1                                              12215         \n",
       "2                                              25500         \n",
       "3                                              12766         \n",
       "4                                              20624         \n",
       "5                                              16884         \n",
       "\n",
       "   householder living with unmarried partner or unmarried partner of householder  \\\n",
       "0                                               5705                               \n",
       "1                                               4630                               \n",
       "2                                               2770                               \n",
       "3                                               3832                               \n",
       "4                                               4652                               \n",
       "5                                               5428                               \n",
       "\n",
       "   child of householder  other relatives  other nonrelatives  18 to 34 years:  \\\n",
       "0                  3361             4359                5789            16567   \n",
       "1                  2308             3794                4092            12560   \n",
       "2                  7418             8187                3773            15461   \n",
       "3                  6997            10241                6170            18374   \n",
       "4                 13136            20512                8442            28997   \n",
       "5                  3323             4747                8317            19005   \n",
       "\n",
       "   ...  child of householder 35-64  other relatives 35-64  \\\n",
       "0  ...                         672                   2357   \n",
       "1  ...                         454                   2017   \n",
       "2  ...                        1474                   3742   \n",
       "3  ...                        1815                   4358   \n",
       "4  ...                        3213                  10028   \n",
       "5  ...                        1062                   2441   \n",
       "\n",
       "   other nonrelatives 35-64  65 years and over:  lives alone 65+  \\\n",
       "0                      1552                7889             1684   \n",
       "1                      1163                4482             1361   \n",
       "2                      1260                9352             2521   \n",
       "3                      1291                9414             3194   \n",
       "4                      2535               12353             3147   \n",
       "5                      1544                6352             2182   \n",
       "\n",
       "   householder with spouse 65+  householder with partner 65+  \\\n",
       "0                         4468                           243   \n",
       "1                         1823                           169   \n",
       "2                         3738                           200   \n",
       "3                         2605                           156   \n",
       "4                         3543                           250   \n",
       "5                         2120                           272   \n",
       "\n",
       "   child of householder 65+  other relatives 65+  other nonrelatives 65+  \n",
       "0                        11                 1104                     379  \n",
       "1                        34                  879                     216  \n",
       "2                        30                 2618                     245  \n",
       "3                        45                 3121                     293  \n",
       "4                        42                 4913                     458  \n",
       "5                         7                 1421                     350  \n",
       "\n",
       "[6 rows x 30 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_acs_selected_zipcodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "7384ad5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define age groups for the columns\n",
    "age_groups = ['18-34', '35-64', '65+']\n",
    "\n",
    "# Initialize an empty list to store each reshaped DataFrame\n",
    "dfs = []\n",
    "\n",
    "# Loop over each age group\n",
    "for age in age_groups:\n",
    "    # Select the columns related to the current age group\n",
    "    cols = [col for col in df_acs_selected_zipcodes.columns if age in col]\n",
    "    \n",
    "    # Reshape the DataFrame\n",
    "    df_melted = df_acs_selected_zipcodes.melt(id_vars='zipcode', value_vars=cols, var_name='living_arrangement', value_name='count')\n",
    "    \n",
    "    # Add the age group column\n",
    "    df_melted['age_group'] = age\n",
    "    \n",
    "    # Append the reshaped DataFrame to the list\n",
    "    dfs.append(df_melted)\n",
    "\n",
    "# Concatenate all reshaped DataFrames\n",
    "df_tidy_acs = pd.concat(dfs, ignore_index=True)\n",
    "\n",
    "# Extract the living arrangement from the 'living_arrangement' column\n",
    "df_tidy_acs['living_arrangement'],df_tidy_acs['age_group'] = zip(*df_tidy_acs['living_arrangement'].str.rsplit(n=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "c5142f4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>zipcode</th>\n",
       "      <th>living_arrangement</th>\n",
       "      <th>count</th>\n",
       "      <th>age_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11215</td>\n",
       "      <td>lives alone</td>\n",
       "      <td>1880</td>\n",
       "      <td>18-34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11217</td>\n",
       "      <td>lives alone</td>\n",
       "      <td>1916</td>\n",
       "      <td>18-34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11218</td>\n",
       "      <td>lives alone</td>\n",
       "      <td>1107</td>\n",
       "      <td>18-34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11225</td>\n",
       "      <td>lives alone</td>\n",
       "      <td>1596</td>\n",
       "      <td>18-34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11226</td>\n",
       "      <td>lives alone</td>\n",
       "      <td>2863</td>\n",
       "      <td>18-34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>11217</td>\n",
       "      <td>other nonrelatives</td>\n",
       "      <td>216</td>\n",
       "      <td>65+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>11218</td>\n",
       "      <td>other nonrelatives</td>\n",
       "      <td>245</td>\n",
       "      <td>65+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>11225</td>\n",
       "      <td>other nonrelatives</td>\n",
       "      <td>293</td>\n",
       "      <td>65+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>11226</td>\n",
       "      <td>other nonrelatives</td>\n",
       "      <td>458</td>\n",
       "      <td>65+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>11238</td>\n",
       "      <td>other nonrelatives</td>\n",
       "      <td>350</td>\n",
       "      <td>65+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>108 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    zipcode  living_arrangement  count age_group\n",
       "0     11215         lives alone   1880     18-34\n",
       "1     11217         lives alone   1916     18-34\n",
       "2     11218         lives alone   1107     18-34\n",
       "3     11225         lives alone   1596     18-34\n",
       "4     11226         lives alone   2863     18-34\n",
       "..      ...                 ...    ...       ...\n",
       "103   11217  other nonrelatives    216       65+\n",
       "104   11218  other nonrelatives    245       65+\n",
       "105   11225  other nonrelatives    293       65+\n",
       "106   11226  other nonrelatives    458       65+\n",
       "107   11238  other nonrelatives    350       65+\n",
       "\n",
       "[108 rows x 4 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tidy_acs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "c1710a6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_tidy_acs.to_csv('checking.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "4a03847b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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\"age_group\": \"18-34\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"child of householder\", \"count\": 2678, \"age_group\": \"18-34\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"child of householder\", \"count\": 1820, \"age_group\": \"18-34\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"child of householder\", \"count\": 5914, \"age_group\": \"18-34\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"child of householder\", \"count\": 5137, \"age_group\": \"18-34\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"child of householder\", \"count\": 9881, \"age_group\": \"18-34\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"child of householder\", \"count\": 2254, \"age_group\": \"18-34\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"other relatives\", \"count\": 898, \"age_group\": \"18-34\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"other relatives\", \"count\": 898, \"age_group\": \"18-34\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"other relatives\", \"count\": 1827, \"age_group\": \"18-34\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"other relatives\", \"count\": 2762, \"age_group\": \"18-34\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"other relatives\", \"count\": 5571, \"age_group\": \"18-34\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"other relatives\", \"count\": 885, \"age_group\": \"18-34\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"other nonrelatives\", \"count\": 3858, \"age_group\": \"18-34\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"other nonrelatives\", \"count\": 2713, \"age_group\": \"18-34\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"other nonrelatives\", \"count\": 2268, \"age_group\": \"18-34\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"other nonrelatives\", \"count\": 4586, \"age_group\": \"18-34\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"other nonrelatives\", \"count\": 5449, \"age_group\": \"18-34\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"other nonrelatives\", \"count\": 6423, \"age_group\": \"18-34\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"lives alone\", \"count\": 3958, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"lives alone\", \"count\": 3111, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"lives alone\", \"count\": 3337, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"lives alone\", \"count\": 4188, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"lives alone\", \"count\": 5580, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"lives alone\", \"count\": 4596, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"householder with spouse\", \"count\": 21217, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"householder with spouse\", \"count\": 8151, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"householder with spouse\", \"count\": 18631, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"householder with spouse\", \"count\": 7943, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"householder with spouse\", \"count\": 13859, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"householder with spouse\", \"count\": 11089, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"householder with partner\", \"count\": 2368, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"householder with partner\", \"count\": 1489, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"householder with partner\", \"count\": 1356, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"householder with partner\", \"count\": 1601, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"householder with partner\", \"count\": 2391, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"householder with partner\", \"count\": 1909, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"child of householder\", \"count\": 672, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"child of householder\", \"count\": 454, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"child of householder\", \"count\": 1474, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"child of householder\", \"count\": 1815, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"child of householder\", \"count\": 3213, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"child of householder\", \"count\": 1062, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"other relatives\", \"count\": 2357, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"other relatives\", \"count\": 2017, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"other relatives\", \"count\": 3742, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"other relatives\", \"count\": 4358, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"other relatives\", \"count\": 10028, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"other relatives\", \"count\": 2441, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1552, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1163, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1260, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1291, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"other nonrelatives\", \"count\": 2535, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1544, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"lives alone\", \"count\": 1684, \"age_group\": \"65+\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"lives alone\", \"count\": 1361, \"age_group\": \"65+\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"lives alone\", \"count\": 2521, \"age_group\": \"65+\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"lives alone\", \"count\": 3194, \"age_group\": \"65+\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"lives alone\", \"count\": 3147, \"age_group\": \"65+\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"lives alone\", \"count\": 2182, \"age_group\": \"65+\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"householder with spouse\", \"count\": 4468, \"age_group\": \"65+\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"householder with spouse\", \"count\": 1823, \"age_group\": \"65+\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"householder with spouse\", \"count\": 3738, \"age_group\": \"65+\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"householder with spouse\", \"count\": 2605, \"age_group\": \"65+\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"householder with spouse\", \"count\": 3543, \"age_group\": \"65+\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"householder with spouse\", \"count\": 2120, \"age_group\": \"65+\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"householder with partner\", \"count\": 243, \"age_group\": \"65+\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"householder with partner\", \"count\": 169, \"age_group\": \"65+\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"householder with partner\", \"count\": 200, \"age_group\": \"65+\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"householder with partner\", \"count\": 156, \"age_group\": \"65+\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"householder with partner\", \"count\": 250, \"age_group\": \"65+\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"householder with partner\", \"count\": 272, \"age_group\": \"65+\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"child of householder\", \"count\": 11, \"age_group\": \"65+\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"child of householder\", \"count\": 34, \"age_group\": \"65+\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"child of householder\", \"count\": 30, \"age_group\": \"65+\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"child of householder\", \"count\": 45, \"age_group\": \"65+\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"child of householder\", \"count\": 42, \"age_group\": \"65+\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"child of householder\", \"count\": 7, \"age_group\": \"65+\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"other relatives\", \"count\": 1104, \"age_group\": \"65+\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"other relatives\", \"count\": 879, \"age_group\": \"65+\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"other relatives\", \"count\": 2618, \"age_group\": \"65+\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"other relatives\", \"count\": 3121, \"age_group\": \"65+\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"other relatives\", \"count\": 4913, \"age_group\": \"65+\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"other relatives\", \"count\": 1421, \"age_group\": \"65+\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"other nonrelatives\", \"count\": 379, \"age_group\": \"65+\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"other nonrelatives\", \"count\": 216, \"age_group\": \"65+\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"other nonrelatives\", \"count\": 245, \"age_group\": \"65+\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"other nonrelatives\", \"count\": 293, \"age_group\": \"65+\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"other nonrelatives\", \"count\": 458, \"age_group\": \"65+\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"other nonrelatives\", \"count\": 350, \"age_group\": \"65+\"}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import altair as alt\n",
    "\n",
    "chart = alt.Chart(df_tidy_acs).mark_bar().encode(\n",
    "    x=alt.X('living_arrangement:N', title='Zipcode'),\n",
    "    y=alt.Y('count:Q', title='Count'),\n",
    "    color='age_group:N',\n",
    "    tooltip=['zipcode', 'living_arrangement', 'count', 'age_group'],\n",
    "    column='zipcode:N'\n",
    ").properties(\n",
    "    width=150,\n",
    "    height=300\n",
    ")\n",
    "\n",
    "chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "e74aede7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_census_reporter = pd.read_csv('census_reporter_demographic_df')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "736a6f64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>zipcode</th>\n",
       "      <th>median age</th>\n",
       "      <th>per capita income</th>\n",
       "      <th>median household income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11215</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11217</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11218</td>\n",
       "      <td>36.4</td>\n",
       "      <td>43113</td>\n",
       "      <td>81857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11225</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497</td>\n",
       "      <td>68542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11226</td>\n",
       "      <td>35.4</td>\n",
       "      <td>34323</td>\n",
       "      <td>66173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11238</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   zipcode  median age  per capita income  median household income\n",
       "0    11215        37.0              87707                   156930\n",
       "1    11217        35.5              85813                   133269\n",
       "2    11218        36.4              43113                    81857\n",
       "3    11225        36.1              41497                    68542\n",
       "4    11226        35.4              34323                    66173\n",
       "5    11238        35.3              67950                   114427"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_census_reporter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "f80299c2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode                      int64\n",
       "median age                 float64\n",
       "per capita income            int64\n",
       "median household income      int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_census_reporter.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "8f2cb15c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_census_reporter['zipcode'] = df_census_reporter['zipcode'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "de0ece65",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "  #altair-viz-621c5e7eadbb43d188ee5af92d72899b.vega-embed {\n",
       "    width: 100%;\n",
       "    display: flex;\n",
       "  }\n",
       "\n",
       "  #altair-viz-621c5e7eadbb43d188ee5af92d72899b.vega-embed details,\n",
       "  #altair-viz-621c5e7eadbb43d188ee5af92d72899b.vega-embed details summary {\n",
       "    position: relative;\n",
       "  }\n",
       "</style>\n",
       "<div id=\"altair-viz-621c5e7eadbb43d188ee5af92d72899b\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-621c5e7eadbb43d188ee5af92d72899b\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-621c5e7eadbb43d188ee5af92d72899b\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm/vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm/vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm/vega-lite@5.8.0?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm/vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function maybeLoadScript(lib, version) {\n",
       "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
       "      return (VEGA_DEBUG[key] == version) ?\n",
       "        Promise.resolve(paths[lib]) :\n",
       "        new Promise(function(resolve, reject) {\n",
       "          var s = document.createElement('script');\n",
       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "          s.async = true;\n",
       "          s.onload = () => {\n",
       "            VEGA_DEBUG[key] = version;\n",
       "            return resolve(paths[lib]);\n",
       "          };\n",
       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "          s.src = paths[lib];\n",
       "        });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"5.8.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 300, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-506e0c97901dd6e3c26c1c4f84bd18a0\"}, \"facet\": {\"column\": {\"field\": \"living_arrangement\", \"type\": \"nominal\"}}, \"spec\": {\"mark\": {\"type\": \"bar\"}, \"encoding\": {\"color\": {\"field\": \"living_arrangement\", \"type\": \"nominal\"}, \"tooltip\": [{\"field\": \"zipcode\", \"type\": \"nominal\"}, {\"field\": \"living_arrangement\", \"type\": \"nominal\"}, {\"field\": \"count\", \"type\": \"quantitative\"}], \"x\": {\"field\": \"zipcode\", \"title\": \"Zipcode\", \"type\": \"nominal\"}, \"y\": {\"field\": \"count\", \"title\": \"Count\", \"type\": \"quantitative\"}}, \"height\": 300, \"width\": 150}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v5.8.0.json\", \"datasets\": {\"data-506e0c97901dd6e3c26c1c4f84bd18a0\": [{\"zipcode\": \"11215\", \"living_arrangement\": \"lives alone\", \"count\": 3958, \"age_group\": \"35-64\"}, {\"zipcode\": 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\"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"householder with spouse\", \"count\": 13859, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"householder with spouse\", \"count\": 11089, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"householder with partner\", \"count\": 2368, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"householder with partner\", \"count\": 1489, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"householder with partner\", \"count\": 1356, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"householder with partner\", \"count\": 1601, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"householder with partner\", \"count\": 2391, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"householder with partner\", \"count\": 1909, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"child of householder\", \"count\": 672, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"child of householder\", \"count\": 454, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"child of householder\", \"count\": 1474, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"child of householder\", \"count\": 1815, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"child of householder\", \"count\": 3213, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"child of householder\", \"count\": 1062, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"other relatives\", \"count\": 2357, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"other relatives\", \"count\": 2017, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"other relatives\", \"count\": 3742, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"other relatives\", \"count\": 4358, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"other relatives\", \"count\": 10028, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"other relatives\", \"count\": 2441, \"age_group\": \"35-64\"}, {\"zipcode\": \"11215\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1552, \"age_group\": \"35-64\"}, {\"zipcode\": \"11217\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1163, \"age_group\": \"35-64\"}, {\"zipcode\": \"11218\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1260, \"age_group\": \"35-64\"}, {\"zipcode\": \"11225\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1291, \"age_group\": \"35-64\"}, {\"zipcode\": \"11226\", \"living_arrangement\": \"other nonrelatives\", \"count\": 2535, \"age_group\": \"35-64\"}, {\"zipcode\": \"11238\", \"living_arrangement\": \"other nonrelatives\", \"count\": 1544, \"age_group\": \"35-64\"}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.FacetChart(...)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter data\n",
    "df_filtered_living_arrangement = df_tidy_acs[df_tidy_acs['age_group'] == '35-64']\n",
    "\n",
    "# Create chart\n",
    "chart = alt.Chart(df_filtered_living_arrangement).mark_bar().encode(\n",
    "    x=alt.X('zipcode:N', title='Zipcode'),\n",
    "    y=alt.Y('count:Q', title='Count'),\n",
    "    color='living_arrangement:N',\n",
    "    tooltip=['zipcode', 'living_arrangement', 'count']\n",
    ").properties(\n",
    "    width=150,\n",
    "    height=300\n",
    ").facet(\n",
    "    column='living_arrangement:N'\n",
    ")\n",
    "\n",
    "chart\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "21ff6993",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "zipcode\n",
      "11215    12.0\n",
      "11217    19.0\n",
      "11218    11.0\n",
      "11225    20.0\n",
      "11226    15.0\n",
      "11238    20.0\n",
      "Name: count, dtype: float64\n",
      "zipcode\n",
      "11215    66.0\n",
      "11217    50.0\n",
      "11218    63.0\n",
      "11225    37.0\n",
      "11226    37.0\n",
      "11238    49.0\n",
      "Name: count, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# First, let's get only the rows for the 35-64 age group\n",
    "df_35_64 = df_filtered_living_arrangement[df_filtered_living_arrangement['age_group'] == '35-64']\n",
    "\n",
    "# Now let's calculate the total count per zipcode\n",
    "total_counts = df_35_64.groupby('zipcode')['count'].sum()\n",
    "\n",
    "# Let's calculate the sum of counts for the 'lives alone' and 'householder living with spouse or spouse of householder' living arrangements\n",
    "alone_counts = df_35_64[df_35_64['living_arrangement'] == 'lives alone'].groupby('zipcode')['count'].sum()\n",
    "with_spouse_counts = df_35_64[df_35_64['living_arrangement'] == 'householder with spouse'].groupby('zipcode')['count'].sum()\n",
    "\n",
    "# Now, we calculate the percentages\n",
    "alone_percentages = alone_counts / total_counts * 100\n",
    "with_spouse_percentages = with_spouse_counts / total_counts * 100\n",
    "\n",
    "# The results are pandas Series with the zipcodes as indices and the percentages as values\n",
    "print(alone_percentages.round())\n",
    "print(with_spouse_percentages.round())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "3e9ae9db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['zipcode', 'living_arrangement', 'count', 'age_group'], dtype='object')"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_35_64.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "32075e04",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>listing_path</th>\n",
       "      <th>location</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>floor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>l-2g3vm2ptsq8i</td>\n",
       "      <td>11225</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3726</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3726</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>l-2in0401r3l0j</td>\n",
       "      <td>11215</td>\n",
       "      <td>1B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>l-dgbncnljpk2t</td>\n",
       "      <td>11217</td>\n",
       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1041</th>\n",
       "      <td>l-f280460qpan0</td>\n",
       "      <td>11221</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1066.0</td>\n",
       "      <td>4150</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1043</th>\n",
       "      <td>l-21m12jnumbm4</td>\n",
       "      <td>11221</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3678</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3678</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1062</th>\n",
       "      <td>l-iqp310aocqdd</td>\n",
       "      <td>11213</td>\n",
       "      <td>4F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3250</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3250</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1067</th>\n",
       "      <td>l-7g7gkgl3ak4i</td>\n",
       "      <td>11213</td>\n",
       "      <td>2B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>2850</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1068</th>\n",
       "      <td>l-1s265npkj314</td>\n",
       "      <td>11213</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4250</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4250</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>230 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        listing_path location unit_number building_class  beds    size  rent  \\\n",
       "0     l-2g3vm2ptsq8i    11225           2    rental unit   3.0     NaN  3726   \n",
       "1     l-2in0401r3l0j    11215          1B    rental unit   2.0     NaN  4500   \n",
       "3     l-dgbncnljpk2t    11217          B2    rental unit   3.0   900.0  4750   \n",
       "199   l-k5pmp1c6dcau    11215           3    rental unit   1.0     NaN  3750   \n",
       "200   l-ok0278ecbrpc    11217         312    rental unit   1.0     NaN  4000   \n",
       "...              ...      ...         ...            ...   ...     ...   ...   \n",
       "1041  l-f280460qpan0    11221          1R    rental unit   1.0  1066.0  4150   \n",
       "1043  l-21m12jnumbm4    11221           2    rental unit   3.0     NaN  3678   \n",
       "1062  l-iqp310aocqdd    11213          4F    rental unit   3.0     NaN  3250   \n",
       "1067  l-7g7gkgl3ak4i    11213          2B    rental unit   1.0   600.0  2850   \n",
       "1068  l-1s265npkj314    11213           2    rental unit   3.0     NaN  4250   \n",
       "\n",
       "           sun_exposure_cat  \\\n",
       "0          No sunlight data   \n",
       "1          No sunlight data   \n",
       "3          No sunlight data   \n",
       "199       Moderate sunlight   \n",
       "200        No sunlight data   \n",
       "...                     ...   \n",
       "1041       No sunlight data   \n",
       "1043       No sunlight data   \n",
       "1062       No sunlight data   \n",
       "1067  Limited natural light   \n",
       "1068       No sunlight data   \n",
       "\n",
       "                                           sun_exposure floor  \n",
       "0       No sunlight data available and the rent is 3726     2  \n",
       "1       No sunlight data available and the rent is 4500     1  \n",
       "3       No sunlight data available and the rent is 4750     2  \n",
       "199   This apartment has moderate sunlight and the r...     3  \n",
       "200     No sunlight data available and the rent is 4000     3  \n",
       "...                                                 ...   ...  \n",
       "1041    No sunlight data available and the rent is 4150     1  \n",
       "1043    No sunlight data available and the rent is 3678     2  \n",
       "1062    No sunlight data available and the rent is 3250     4  \n",
       "1067  This apartment has limited sunlight and the re...     2  \n",
       "1068    No sunlight data available and the rent is 4250     2  \n",
       "\n",
       "[230 rows x 10 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "aa6e25c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sun_exposure = df_sun_exposure.rename(columns = {'location':'zipcode'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "45f35cc5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# df_sun_exposure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "43c49add",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11201    23\n",
       "11205     2\n",
       "11210     8\n",
       "11213     3\n",
       "11215    51\n",
       "11216    15\n",
       "11217    42\n",
       "11218     2\n",
       "11219     1\n",
       "11221     2\n",
       "11225    10\n",
       "11226    30\n",
       "11230     1\n",
       "11231     3\n",
       "11232     1\n",
       "11238    36\n",
       "dtype: int64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure.groupby(by='zipcode').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "b5ff72d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>floor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>l-2g3vm2ptsq8i</td>\n",
       "      <td>11225</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3726</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3726</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>l-2in0401r3l0j</td>\n",
       "      <td>11215</td>\n",
       "      <td>1B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>l-dgbncnljpk2t</td>\n",
       "      <td>11217</td>\n",
       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200</td>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>734</td>\n",
       "      <td>l-ue6jib37qqnf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>757</td>\n",
       "      <td>l-metf0tnqb3oa</td>\n",
       "      <td>11238</td>\n",
       "      <td>6B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>781</td>\n",
       "      <td>l-qtrv180v4kc8</td>\n",
       "      <td>11238</td>\n",
       "      <td>504</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>782</td>\n",
       "      <td>l-v22eed67chvl</td>\n",
       "      <td>11238</td>\n",
       "      <td>501</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>783</td>\n",
       "      <td>l-rk0ue9fad9jb</td>\n",
       "      <td>11238</td>\n",
       "      <td>404</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2995</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 2995</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>171 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds   size  \\\n",
       "0        0  l-2g3vm2ptsq8i   11225           2    rental unit   3.0    NaN   \n",
       "1        1  l-2in0401r3l0j   11215          1B    rental unit   2.0    NaN   \n",
       "2        3  l-dgbncnljpk2t   11217          B2    rental unit   3.0  900.0   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0    NaN   \n",
       "4      200  l-ok0278ecbrpc   11217         312    rental unit   1.0    NaN   \n",
       "..     ...             ...     ...         ...            ...   ...    ...   \n",
       "166    734  l-ue6jib37qqnf   11238           4    rental unit   1.0    NaN   \n",
       "167    757  l-metf0tnqb3oa   11238          6B    rental unit   2.0    NaN   \n",
       "168    781  l-qtrv180v4kc8   11238         504    rental unit   1.0    NaN   \n",
       "169    782  l-v22eed67chvl   11238         501    rental unit   2.0    NaN   \n",
       "170    783  l-rk0ue9fad9jb   11238         404    rental unit   0.0    NaN   \n",
       "\n",
       "     rent   sun_exposure_cat  \\\n",
       "0    3726   No sunlight data   \n",
       "1    4500   No sunlight data   \n",
       "2    4750   No sunlight data   \n",
       "3    3750  Moderate sunlight   \n",
       "4    4000   No sunlight data   \n",
       "..    ...                ...   \n",
       "166  3500   No sunlight data   \n",
       "167  4000   No sunlight data   \n",
       "168  3500   No sunlight data   \n",
       "169  4200   No sunlight data   \n",
       "170  2995   No sunlight data   \n",
       "\n",
       "                                          sun_exposure floor  \n",
       "0      No sunlight data available and the rent is 3726     2  \n",
       "1      No sunlight data available and the rent is 4500     1  \n",
       "2      No sunlight data available and the rent is 4750     2  \n",
       "3    This apartment has moderate sunlight and the r...     3  \n",
       "4      No sunlight data available and the rent is 4000     3  \n",
       "..                                                 ...   ...  \n",
       "166    No sunlight data available and the rent is 3500     4  \n",
       "167    No sunlight data available and the rent is 4000     6  \n",
       "168    No sunlight data available and the rent is 3500     5  \n",
       "169    No sunlight data available and the rent is 4200     5  \n",
       "170    No sunlight data available and the rent is 2995     4  \n",
       "\n",
       "[171 rows x 11 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure_selected = df_sun_exposure[df_sun_exposure['zipcode'].isin(selected_zipcodes)].reset_index()\n",
    "df_sun_exposure_selected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "58a76532",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>1</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>11217</td>\n",
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       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200</td>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>734</td>\n",
       "      <td>l-ue6jib37qqnf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>757</td>\n",
       "      <td>l-metf0tnqb3oa</td>\n",
       "      <td>11238</td>\n",
       "      <td>6B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>781</td>\n",
       "      <td>l-qtrv180v4kc8</td>\n",
       "      <td>11238</td>\n",
       "      <td>504</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>782</td>\n",
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       "      <td>11238</td>\n",
       "      <td>501</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>783</td>\n",
       "      <td>l-rk0ue9fad9jb</td>\n",
       "      <td>11238</td>\n",
       "      <td>404</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2995</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 2995</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>171 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds   size  \\\n",
       "0        0  l-2g3vm2ptsq8i   11225           2    rental unit   3.0    NaN   \n",
       "1        1  l-2in0401r3l0j   11215          1B    rental unit   2.0    NaN   \n",
       "2        3  l-dgbncnljpk2t   11217          B2    rental unit   3.0  900.0   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0    NaN   \n",
       "4      200  l-ok0278ecbrpc   11217         312    rental unit   1.0    NaN   \n",
       "..     ...             ...     ...         ...            ...   ...    ...   \n",
       "166    734  l-ue6jib37qqnf   11238           4    rental unit   1.0    NaN   \n",
       "167    757  l-metf0tnqb3oa   11238          6B    rental unit   2.0    NaN   \n",
       "168    781  l-qtrv180v4kc8   11238         504    rental unit   1.0    NaN   \n",
       "169    782  l-v22eed67chvl   11238         501    rental unit   2.0    NaN   \n",
       "170    783  l-rk0ue9fad9jb   11238         404    rental unit   0.0    NaN   \n",
       "\n",
       "     rent   sun_exposure_cat  \\\n",
       "0    3726   No sunlight data   \n",
       "1    4500   No sunlight data   \n",
       "2    4750   No sunlight data   \n",
       "3    3750  Moderate sunlight   \n",
       "4    4000   No sunlight data   \n",
       "..    ...                ...   \n",
       "166  3500   No sunlight data   \n",
       "167  4000   No sunlight data   \n",
       "168  3500   No sunlight data   \n",
       "169  4200   No sunlight data   \n",
       "170  2995   No sunlight data   \n",
       "\n",
       "                                          sun_exposure floor  \n",
       "0      No sunlight data available and the rent is 3726     2  \n",
       "1      No sunlight data available and the rent is 4500     1  \n",
       "2      No sunlight data available and the rent is 4750     2  \n",
       "3    This apartment has moderate sunlight and the r...     3  \n",
       "4      No sunlight data available and the rent is 4000     3  \n",
       "..                                                 ...   ...  \n",
       "166    No sunlight data available and the rent is 3500     4  \n",
       "167    No sunlight data available and the rent is 4000     6  \n",
       "168    No sunlight data available and the rent is 3500     5  \n",
       "169    No sunlight data available and the rent is 4200     5  \n",
       "170    No sunlight data available and the rent is 2995     4  \n",
       "\n",
       "[171 rows x 11 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure_selected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "5f9df664",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    51\n",
       "11217    42\n",
       "11218     2\n",
       "11225    10\n",
       "11226    30\n",
       "11238    36\n",
       "dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure_selected.groupby(by='zipcode').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "53e00eb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['No sunlight data', 'Moderate sunlight', 'Limited natural light',\n",
       "       'Bright & sun drenched'], dtype=object)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure.sun_exposure_cat.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "92a0b0e7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <td>2800</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
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       "      <th>18</th>\n",
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       "      <td>This apartment has limited sunlight and the re...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
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       "      <td>900.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>242</td>\n",
       "      <td>l-4b0n1hfp83tg</td>\n",
       "      <td>11215</td>\n",
       "      <td>5</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>245</td>\n",
       "      <td>l-52b5rnl1erg8</td>\n",
       "      <td>11215</td>\n",
       "      <td>5F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4995</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>250</td>\n",
       "      <td>l-phubtn46t7vj</td>\n",
       "      <td>11215</td>\n",
       "      <td>2C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>252</td>\n",
       "      <td>l-mmegr1flhf1d</td>\n",
       "      <td>11225</td>\n",
       "      <td>2F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>273</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>289</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>306</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>318</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>320</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>334</td>\n",
       "      <td>l-cpa3tvjh3aer</td>\n",
       "      <td>11215</td>\n",
       "      <td>7H</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3422</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>344</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>355</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>358</td>\n",
       "      <td>l-155vl5l7p3mt</td>\n",
       "      <td>11215</td>\n",
       "      <td>3R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.5</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>365</td>\n",
       "      <td>l-phubtn46t7vj</td>\n",
       "      <td>11215</td>\n",
       "      <td>2C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>371</td>\n",
       "      <td>l-r51ae16miros</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>372</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>390</td>\n",
       "      <td>l-r51ae16miros</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>391</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>393</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>505</td>\n",
       "      <td>l-u78ca500udu6</td>\n",
       "      <td>11217</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>7000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>541</td>\n",
       "      <td>l-4lgcsvm0lf5o</td>\n",
       "      <td>11217</td>\n",
       "      <td>GARDEN</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>4995</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>551</td>\n",
       "      <td>l-ftuu4iri0p65</td>\n",
       "      <td>11217</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6850</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>579</td>\n",
       "      <td>l-4brn1q68tp8k</td>\n",
       "      <td>11238</td>\n",
       "      <td>1S</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>632</td>\n",
       "      <td>l-1ts5anpgrdrk</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>695</td>\n",
       "      <td>l-7u0vaugt03jf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>3850</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds    size  \\\n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0     NaN   \n",
       "15     213  l-4vkr066dfpsq   11217           1    rental unit   2.0     NaN   \n",
       "18     216  l-jlm1f9thn9hb   11225           1    rental unit   4.0  2000.0   \n",
       "23     227  l-mmegr1flhf1d   11225          2F    rental unit   1.0     NaN   \n",
       "32     241  l-155vl5l7p3mt   11215          3R    rental unit   2.5   900.0   \n",
       "33     242  l-4b0n1hfp83tg   11215           5    rental unit   3.0     NaN   \n",
       "36     245  l-52b5rnl1erg8   11215          5F    rental unit   3.0     NaN   \n",
       "38     250  l-phubtn46t7vj   11215          2C    rental unit   4.0     NaN   \n",
       "39     252  l-mmegr1flhf1d   11225          2F    rental unit   1.0     NaN   \n",
       "57     273  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "68     289  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "77     306  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "85     318  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "87     320  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "97     334  l-cpa3tvjh3aer   11215          7H    rental unit   0.0     NaN   \n",
       "98     344  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "100    355  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "102    358  l-155vl5l7p3mt   11215          3R    rental unit   2.5   900.0   \n",
       "103    365  l-phubtn46t7vj   11215          2C    rental unit   4.0     NaN   \n",
       "105    371  l-r51ae16miros   11215           3    rental unit   1.0   800.0   \n",
       "106    372  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "115    390  l-r51ae16miros   11215           3    rental unit   1.0   800.0   \n",
       "116    391  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "118    393  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "133    505  l-u78ca500udu6   11217           1    rental unit   2.0  1000.0   \n",
       "151    541  l-4lgcsvm0lf5o   11217      GARDEN    rental unit   2.0  1400.0   \n",
       "152    551  l-ftuu4iri0p65   11217           3    rental unit   2.0     NaN   \n",
       "153    579  l-4brn1q68tp8k   11238          1S    rental unit   3.0     NaN   \n",
       "160    632  l-1ts5anpgrdrk   11238           4    rental unit   4.0     NaN   \n",
       "163    695  l-7u0vaugt03jf   11238          4L    rental unit   3.0  1100.0   \n",
       "164    704  l-1akn6ug8021r   11238          2L    rental unit   2.0     NaN   \n",
       "\n",
       "     rent       sun_exposure_cat  \\\n",
       "3    3750      Moderate sunlight   \n",
       "15   2800      Moderate sunlight   \n",
       "18   4795  Limited natural light   \n",
       "23   1895  Limited natural light   \n",
       "32   4000  Limited natural light   \n",
       "33   4500  Limited natural light   \n",
       "36   4995  Limited natural light   \n",
       "38   5995      Moderate sunlight   \n",
       "39   1895  Limited natural light   \n",
       "57   4700  Bright & sun drenched   \n",
       "68   4700  Bright & sun drenched   \n",
       "77   4700  Bright & sun drenched   \n",
       "85   2950      Moderate sunlight   \n",
       "87   2950      Moderate sunlight   \n",
       "97   3422  Bright & sun drenched   \n",
       "98   2800  Limited natural light   \n",
       "100  2950      Moderate sunlight   \n",
       "102  4000  Limited natural light   \n",
       "103  5995      Moderate sunlight   \n",
       "105  2600  Bright & sun drenched   \n",
       "106  2800  Limited natural light   \n",
       "115  2600  Bright & sun drenched   \n",
       "116  2800  Limited natural light   \n",
       "118  4700  Bright & sun drenched   \n",
       "133  7000  Limited natural light   \n",
       "151  4995  Limited natural light   \n",
       "152  6850  Limited natural light   \n",
       "153  5500  Limited natural light   \n",
       "160  5900      Moderate sunlight   \n",
       "163  3850  Bright & sun drenched   \n",
       "164  3900      Moderate sunlight   \n",
       "\n",
       "                                          sun_exposure floor  \n",
       "3    This apartment has moderate sunlight and the r...     3  \n",
       "15   This apartment has moderate sunlight and the r...     1  \n",
       "18   This apartment has limited sunlight and the re...     1  \n",
       "23   This apartment has limited sunlight and the re...     2  \n",
       "32   This apartment has limited sunlight and the re...     3  \n",
       "33   This apartment has limited sunlight and the re...     5  \n",
       "36   This apartment has limited sunlight and the re...     5  \n",
       "38   This apartment has moderate sunlight and the r...     2  \n",
       "39   This apartment has limited sunlight and the re...     2  \n",
       "57   This apartment is bright & sun-drenched and th...     1  \n",
       "68   This apartment is bright & sun-drenched and th...     1  \n",
       "77   This apartment is bright & sun-drenched and th...     1  \n",
       "85   This apartment has moderate sunlight and the r...     1  \n",
       "87   This apartment has moderate sunlight and the r...     1  \n",
       "97   This apartment is bright & sun-drenched and th...     7  \n",
       "98   This apartment has limited sunlight and the re...     1  \n",
       "100  This apartment has moderate sunlight and the r...     1  \n",
       "102  This apartment has limited sunlight and the re...     3  \n",
       "103  This apartment has moderate sunlight and the r...     2  \n",
       "105  This apartment is bright & sun-drenched and th...     3  \n",
       "106  This apartment has limited sunlight and the re...     1  \n",
       "115  This apartment is bright & sun-drenched and th...     3  \n",
       "116  This apartment has limited sunlight and the re...     1  \n",
       "118  This apartment is bright & sun-drenched and th...     1  \n",
       "133  This apartment has limited sunlight and the re...     1  \n",
       "151  This apartment has limited sunlight and the re...  None  \n",
       "152  This apartment has limited sunlight and the re...     3  \n",
       "153  This apartment has limited sunlight and the re...     1  \n",
       "160  This apartment has moderate sunlight and the r...     4  \n",
       "163  This apartment is bright & sun-drenched and th...     4  \n",
       "164  This apartment has moderate sunlight and the r...     2  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure_selected[df_sun_exposure_selected['sun_exposure_cat'] != 'No sunlight data']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "d121b49b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>zipcode</th>\n",
       "      <th>counts</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11215</td>\n",
       "      <td>13</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11217</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11225</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11238</td>\n",
       "      <td>8</td>\n",
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      "text/plain": [
       "  zipcode  counts\n",
       "0   11215      13\n",
       "1   11217       7\n",
       "2   11225       3\n",
       "3   11238       8"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sun_exposure_selected[df_sun_exposure_selected['sun_exposure_cat'] != 'No sunlight data'].groupby('zipcode').size().reset_index(name='counts')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "85f69a75",
   "metadata": {
    "scrolled": false
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   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>zipcode</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>rent</th>\n",
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       "      <th>11</th>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11217</td>\n",
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       "      <td>11238</td>\n",
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       "      <td>5900</td>\n",
       "      <td>1</td>\n",
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       "      <th>17</th>\n",
       "      <td>11238</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>5500</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11215</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>4995</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>11217</td>\n",
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       "      <td>4995</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>11225</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>4795</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>11238</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>4700</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11215</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>4500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11215</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>4000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>11238</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>3900</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>11238</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>3850</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11215</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>3750</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11215</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>3422</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11215</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>2950</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11217</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>2800</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>11217</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>2800</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11215</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>2600</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11225</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>1895</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   zipcode       sun_exposure_cat  rent  counts\n",
       "11   11217  Limited natural light  7000       1\n",
       "10   11217  Limited natural light  6850       1\n",
       "7    11215      Moderate sunlight  5995       2\n",
       "19   11238      Moderate sunlight  5900       1\n",
       "17   11238  Limited natural light  5500       1\n",
       "4    11215  Limited natural light  4995       1\n",
       "9    11217  Limited natural light  4995       1\n",
       "14   11225  Limited natural light  4795       1\n",
       "16   11238  Bright & sun drenched  4700       4\n",
       "3    11215  Limited natural light  4500       1\n",
       "2    11215  Limited natural light  4000       2\n",
       "18   11238      Moderate sunlight  3900       1\n",
       "15   11238  Bright & sun drenched  3850       1\n",
       "6    11215      Moderate sunlight  3750       1\n",
       "1    11215  Bright & sun drenched  3422       1\n",
       "5    11215      Moderate sunlight  2950       3\n",
       "8    11217  Limited natural light  2800       3\n",
       "12   11217      Moderate sunlight  2800       1\n",
       "0    11215  Bright & sun drenched  2600       2\n",
       "13   11225  Limited natural light  1895       2"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_sun_exposure_selected[df_sun_exposure_selected['sun_exposure_cat'] != 'No sunlight data']\n",
    "    .groupby(['zipcode','sun_exposure_cat','rent'])\n",
    "    .size()\n",
    "    .reset_index(name='counts')\n",
    "    .sort_values(by='rent', ascending = False)\n",
    "    .head(30))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "49839625",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th></th>\n",
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       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
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       "      <th>0</th>\n",
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       "      <td>l-2g3vm2ptsq8i</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>3726</td>\n",
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       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>l-dgbncnljpk2t</td>\n",
       "      <td>11217</td>\n",
       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>2</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
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       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200</td>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>3</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
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       "    <tr>\n",
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       "      <th>166</th>\n",
       "      <td>734</td>\n",
       "      <td>l-ue6jib37qqnf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>4</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
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       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>757</td>\n",
       "      <td>l-metf0tnqb3oa</td>\n",
       "      <td>11238</td>\n",
       "      <td>6B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>6</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>781</td>\n",
       "      <td>l-qtrv180v4kc8</td>\n",
       "      <td>11238</td>\n",
       "      <td>504</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>5</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>782</td>\n",
       "      <td>l-v22eed67chvl</td>\n",
       "      <td>11238</td>\n",
       "      <td>501</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "      <td>5</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>783</td>\n",
       "      <td>l-rk0ue9fad9jb</td>\n",
       "      <td>11238</td>\n",
       "      <td>404</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2995</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 2995</td>\n",
       "      <td>4</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>171 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds   size  \\\n",
       "0        0  l-2g3vm2ptsq8i   11225           2    rental unit   3.0    NaN   \n",
       "1        1  l-2in0401r3l0j   11215          1B    rental unit   2.0    NaN   \n",
       "2        3  l-dgbncnljpk2t   11217          B2    rental unit   3.0  900.0   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0    NaN   \n",
       "4      200  l-ok0278ecbrpc   11217         312    rental unit   1.0    NaN   \n",
       "..     ...             ...     ...         ...            ...   ...    ...   \n",
       "166    734  l-ue6jib37qqnf   11238           4    rental unit   1.0    NaN   \n",
       "167    757  l-metf0tnqb3oa   11238          6B    rental unit   2.0    NaN   \n",
       "168    781  l-qtrv180v4kc8   11238         504    rental unit   1.0    NaN   \n",
       "169    782  l-v22eed67chvl   11238         501    rental unit   2.0    NaN   \n",
       "170    783  l-rk0ue9fad9jb   11238         404    rental unit   0.0    NaN   \n",
       "\n",
       "     rent   sun_exposure_cat  \\\n",
       "0    3726   No sunlight data   \n",
       "1    4500   No sunlight data   \n",
       "2    4750   No sunlight data   \n",
       "3    3750  Moderate sunlight   \n",
       "4    4000   No sunlight data   \n",
       "..    ...                ...   \n",
       "166  3500   No sunlight data   \n",
       "167  4000   No sunlight data   \n",
       "168  3500   No sunlight data   \n",
       "169  4200   No sunlight data   \n",
       "170  2995   No sunlight data   \n",
       "\n",
       "                                          sun_exposure floor  median age  \\\n",
       "0      No sunlight data available and the rent is 3726     2        36.1   \n",
       "1      No sunlight data available and the rent is 4500     1        37.0   \n",
       "2      No sunlight data available and the rent is 4750     2        35.5   \n",
       "3    This apartment has moderate sunlight and the r...     3        37.0   \n",
       "4      No sunlight data available and the rent is 4000     3        35.5   \n",
       "..                                                 ...   ...         ...   \n",
       "166    No sunlight data available and the rent is 3500     4        35.3   \n",
       "167    No sunlight data available and the rent is 4000     6        35.3   \n",
       "168    No sunlight data available and the rent is 3500     5        35.3   \n",
       "169    No sunlight data available and the rent is 4200     5        35.3   \n",
       "170    No sunlight data available and the rent is 2995     4        35.3   \n",
       "\n",
       "     per capita income  median household income  \n",
       "0                41497                    68542  \n",
       "1                87707                   156930  \n",
       "2                85813                   133269  \n",
       "3                87707                   156930  \n",
       "4                85813                   133269  \n",
       "..                 ...                      ...  \n",
       "166              67950                   114427  \n",
       "167              67950                   114427  \n",
       "168              67950                   114427  \n",
       "169              67950                   114427  \n",
       "170              67950                   114427  \n",
       "\n",
       "[171 rows x 14 columns]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged = pd.merge(df_sun_exposure_selected, df_census_reporter, on='zipcode', how='left')\n",
    "df_merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "a3092ecc",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    [No sunlight data, Moderate sunlight, Limited ...\n",
       "11217    [No sunlight data, Moderate sunlight, Limited ...\n",
       "11218                                   [No sunlight data]\n",
       "11225            [No sunlight data, Limited natural light]\n",
       "11226                                   [No sunlight data]\n",
       "11238    [No sunlight data, Bright & sun drenched, Limi...\n",
       "Name: sun_exposure_cat, dtype: object"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sun_exposure_per_zipcode = df_merged.groupby('zipcode')['sun_exposure_cat'].unique()\n",
    "sun_exposure_per_zipcode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "59916b78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The available sun exposure levels for apartments in this area are: ['No sunlight data' 'Moderate sunlight' 'Limited natural light'\n",
      " 'Bright & sun drenched']\n",
      "The available sun exposure levels for apartments in this area are: ['No sunlight data' 'Moderate sunlight' 'Limited natural light']\n",
      "The available sun exposure levels for apartments in this area are: ['No sunlight data']\n",
      "The available sun exposure levels for apartments in this area are: ['No sunlight data' 'Limited natural light']\n",
      "The available sun exposure levels for apartments in this area are: ['No sunlight data']\n",
      "The available sun exposure levels for apartments in this area are: ['No sunlight data' 'Bright & sun drenched' 'Limited natural light'\n",
      " 'Moderate sunlight']\n"
     ]
    }
   ],
   "source": [
    "for zipcode in sun_exposure_per_zipcode:\n",
    "    print(f\"The available sun exposure levels for apartments in this area are: {zipcode}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "1e718e2d",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For zipcode 11215, the available sun exposure categories are: ['No sunlight data' 'Moderate sunlight' 'Limited natural light'\n",
      " 'Bright & sun drenched']\n",
      "--------\n",
      "For zipcode 11217, the available sun exposure categories are: ['No sunlight data' 'Moderate sunlight' 'Limited natural light']\n",
      "--------\n",
      "For zipcode 11218, the available sun exposure categories are: ['No sunlight data']\n",
      "--------\n",
      "For zipcode 11225, the available sun exposure categories are: ['No sunlight data' 'Limited natural light']\n",
      "--------\n",
      "For zipcode 11226, the available sun exposure categories are: ['No sunlight data']\n",
      "--------\n",
      "For zipcode 11238, the available sun exposure categories are: ['No sunlight data' 'Bright & sun drenched' 'Limited natural light'\n",
      " 'Moderate sunlight']\n",
      "--------\n"
     ]
    }
   ],
   "source": [
    "for zipcode, sun_exposure in sun_exposure_per_zipcode.items():\n",
    "    print(f\"For zipcode {zipcode}, the available sun exposure categories are: {sun_exposure}\")\n",
    "    print(\"--------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "dba05638",
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_sun_exposure = df_merged[df_merged['sun_exposure_cat'] != 'No sunlight data']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "5bf08df7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>floor</th>\n",
       "      <th>median age</th>\n",
       "      <th>per capita income</th>\n",
       "      <th>median household income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>3</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>213</td>\n",
       "      <td>l-4vkr066dfpsq</td>\n",
       "      <td>11217</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>216</td>\n",
       "      <td>l-jlm1f9thn9hb</td>\n",
       "      <td>11225</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>4795</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497</td>\n",
       "      <td>68542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>227</td>\n",
       "      <td>l-mmegr1flhf1d</td>\n",
       "      <td>11225</td>\n",
       "      <td>2F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>2</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497</td>\n",
       "      <td>68542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>241</td>\n",
       "      <td>l-155vl5l7p3mt</td>\n",
       "      <td>11215</td>\n",
       "      <td>3R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.5</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>3</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>242</td>\n",
       "      <td>l-4b0n1hfp83tg</td>\n",
       "      <td>11215</td>\n",
       "      <td>5</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>5</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>245</td>\n",
       "      <td>l-52b5rnl1erg8</td>\n",
       "      <td>11215</td>\n",
       "      <td>5F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4995</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>5</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>250</td>\n",
       "      <td>l-phubtn46t7vj</td>\n",
       "      <td>11215</td>\n",
       "      <td>2C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>2</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>252</td>\n",
       "      <td>l-mmegr1flhf1d</td>\n",
       "      <td>11225</td>\n",
       "      <td>2F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>2</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497</td>\n",
       "      <td>68542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>273</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>289</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>306</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>318</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>1</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>320</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>1</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>334</td>\n",
       "      <td>l-cpa3tvjh3aer</td>\n",
       "      <td>11215</td>\n",
       "      <td>7H</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3422</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>7</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>344</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>355</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>1</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>358</td>\n",
       "      <td>l-155vl5l7p3mt</td>\n",
       "      <td>11215</td>\n",
       "      <td>3R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.5</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>3</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>365</td>\n",
       "      <td>l-phubtn46t7vj</td>\n",
       "      <td>11215</td>\n",
       "      <td>2C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>2</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>371</td>\n",
       "      <td>l-r51ae16miros</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>3</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>372</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>390</td>\n",
       "      <td>l-r51ae16miros</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>3</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>391</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>393</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>505</td>\n",
       "      <td>l-u78ca500udu6</td>\n",
       "      <td>11217</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>7000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>541</td>\n",
       "      <td>l-4lgcsvm0lf5o</td>\n",
       "      <td>11217</td>\n",
       "      <td>GARDEN</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>4995</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>None</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>551</td>\n",
       "      <td>l-ftuu4iri0p65</td>\n",
       "      <td>11217</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6850</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>3</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>579</td>\n",
       "      <td>l-4brn1q68tp8k</td>\n",
       "      <td>11238</td>\n",
       "      <td>1S</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>1</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>632</td>\n",
       "      <td>l-1ts5anpgrdrk</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>4</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>695</td>\n",
       "      <td>l-7u0vaugt03jf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>3850</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>4</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>2</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds    size  \\\n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0     NaN   \n",
       "15     213  l-4vkr066dfpsq   11217           1    rental unit   2.0     NaN   \n",
       "18     216  l-jlm1f9thn9hb   11225           1    rental unit   4.0  2000.0   \n",
       "23     227  l-mmegr1flhf1d   11225          2F    rental unit   1.0     NaN   \n",
       "32     241  l-155vl5l7p3mt   11215          3R    rental unit   2.5   900.0   \n",
       "33     242  l-4b0n1hfp83tg   11215           5    rental unit   3.0     NaN   \n",
       "36     245  l-52b5rnl1erg8   11215          5F    rental unit   3.0     NaN   \n",
       "38     250  l-phubtn46t7vj   11215          2C    rental unit   4.0     NaN   \n",
       "39     252  l-mmegr1flhf1d   11225          2F    rental unit   1.0     NaN   \n",
       "57     273  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "68     289  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "77     306  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "85     318  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "87     320  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "97     334  l-cpa3tvjh3aer   11215          7H    rental unit   0.0     NaN   \n",
       "98     344  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "100    355  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "102    358  l-155vl5l7p3mt   11215          3R    rental unit   2.5   900.0   \n",
       "103    365  l-phubtn46t7vj   11215          2C    rental unit   4.0     NaN   \n",
       "105    371  l-r51ae16miros   11215           3    rental unit   1.0   800.0   \n",
       "106    372  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "115    390  l-r51ae16miros   11215           3    rental unit   1.0   800.0   \n",
       "116    391  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "118    393  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "133    505  l-u78ca500udu6   11217           1    rental unit   2.0  1000.0   \n",
       "151    541  l-4lgcsvm0lf5o   11217      GARDEN    rental unit   2.0  1400.0   \n",
       "152    551  l-ftuu4iri0p65   11217           3    rental unit   2.0     NaN   \n",
       "153    579  l-4brn1q68tp8k   11238          1S    rental unit   3.0     NaN   \n",
       "160    632  l-1ts5anpgrdrk   11238           4    rental unit   4.0     NaN   \n",
       "163    695  l-7u0vaugt03jf   11238          4L    rental unit   3.0  1100.0   \n",
       "164    704  l-1akn6ug8021r   11238          2L    rental unit   2.0     NaN   \n",
       "\n",
       "     rent       sun_exposure_cat  \\\n",
       "3    3750      Moderate sunlight   \n",
       "15   2800      Moderate sunlight   \n",
       "18   4795  Limited natural light   \n",
       "23   1895  Limited natural light   \n",
       "32   4000  Limited natural light   \n",
       "33   4500  Limited natural light   \n",
       "36   4995  Limited natural light   \n",
       "38   5995      Moderate sunlight   \n",
       "39   1895  Limited natural light   \n",
       "57   4700  Bright & sun drenched   \n",
       "68   4700  Bright & sun drenched   \n",
       "77   4700  Bright & sun drenched   \n",
       "85   2950      Moderate sunlight   \n",
       "87   2950      Moderate sunlight   \n",
       "97   3422  Bright & sun drenched   \n",
       "98   2800  Limited natural light   \n",
       "100  2950      Moderate sunlight   \n",
       "102  4000  Limited natural light   \n",
       "103  5995      Moderate sunlight   \n",
       "105  2600  Bright & sun drenched   \n",
       "106  2800  Limited natural light   \n",
       "115  2600  Bright & sun drenched   \n",
       "116  2800  Limited natural light   \n",
       "118  4700  Bright & sun drenched   \n",
       "133  7000  Limited natural light   \n",
       "151  4995  Limited natural light   \n",
       "152  6850  Limited natural light   \n",
       "153  5500  Limited natural light   \n",
       "160  5900      Moderate sunlight   \n",
       "163  3850  Bright & sun drenched   \n",
       "164  3900      Moderate sunlight   \n",
       "\n",
       "                                          sun_exposure floor  median age  \\\n",
       "3    This apartment has moderate sunlight and the r...     3        37.0   \n",
       "15   This apartment has moderate sunlight and the r...     1        35.5   \n",
       "18   This apartment has limited sunlight and the re...     1        36.1   \n",
       "23   This apartment has limited sunlight and the re...     2        36.1   \n",
       "32   This apartment has limited sunlight and the re...     3        37.0   \n",
       "33   This apartment has limited sunlight and the re...     5        37.0   \n",
       "36   This apartment has limited sunlight and the re...     5        37.0   \n",
       "38   This apartment has moderate sunlight and the r...     2        37.0   \n",
       "39   This apartment has limited sunlight and the re...     2        36.1   \n",
       "57   This apartment is bright & sun-drenched and th...     1        35.3   \n",
       "68   This apartment is bright & sun-drenched and th...     1        35.3   \n",
       "77   This apartment is bright & sun-drenched and th...     1        35.3   \n",
       "85   This apartment has moderate sunlight and the r...     1        37.0   \n",
       "87   This apartment has moderate sunlight and the r...     1        37.0   \n",
       "97   This apartment is bright & sun-drenched and th...     7        37.0   \n",
       "98   This apartment has limited sunlight and the re...     1        35.5   \n",
       "100  This apartment has moderate sunlight and the r...     1        37.0   \n",
       "102  This apartment has limited sunlight and the re...     3        37.0   \n",
       "103  This apartment has moderate sunlight and the r...     2        37.0   \n",
       "105  This apartment is bright & sun-drenched and th...     3        37.0   \n",
       "106  This apartment has limited sunlight and the re...     1        35.5   \n",
       "115  This apartment is bright & sun-drenched and th...     3        37.0   \n",
       "116  This apartment has limited sunlight and the re...     1        35.5   \n",
       "118  This apartment is bright & sun-drenched and th...     1        35.3   \n",
       "133  This apartment has limited sunlight and the re...     1        35.5   \n",
       "151  This apartment has limited sunlight and the re...  None        35.5   \n",
       "152  This apartment has limited sunlight and the re...     3        35.5   \n",
       "153  This apartment has limited sunlight and the re...     1        35.3   \n",
       "160  This apartment has moderate sunlight and the r...     4        35.3   \n",
       "163  This apartment is bright & sun-drenched and th...     4        35.3   \n",
       "164  This apartment has moderate sunlight and the r...     2        35.3   \n",
       "\n",
       "     per capita income  median household income  \n",
       "3                87707                   156930  \n",
       "15               85813                   133269  \n",
       "18               41497                    68542  \n",
       "23               41497                    68542  \n",
       "32               87707                   156930  \n",
       "33               87707                   156930  \n",
       "36               87707                   156930  \n",
       "38               87707                   156930  \n",
       "39               41497                    68542  \n",
       "57               67950                   114427  \n",
       "68               67950                   114427  \n",
       "77               67950                   114427  \n",
       "85               87707                   156930  \n",
       "87               87707                   156930  \n",
       "97               87707                   156930  \n",
       "98               85813                   133269  \n",
       "100              87707                   156930  \n",
       "102              87707                   156930  \n",
       "103              87707                   156930  \n",
       "105              87707                   156930  \n",
       "106              85813                   133269  \n",
       "115              87707                   156930  \n",
       "116              85813                   133269  \n",
       "118              67950                   114427  \n",
       "133              85813                   133269  \n",
       "151              85813                   133269  \n",
       "152              85813                   133269  \n",
       "153              67950                   114427  \n",
       "160              67950                   114427  \n",
       "163              67950                   114427  \n",
       "164              67950                   114427  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_sun_exposure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "703b6d32",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For zipcode 11215, the available sun exposure categories are: ['Moderate sunlight' 'Limited natural light' 'Bright & sun drenched']\n",
      "--------\n",
      "For zipcode 11217, the available sun exposure categories are: ['Moderate sunlight' 'Limited natural light']\n",
      "--------\n",
      "For zipcode 11225, the available sun exposure categories are: ['Limited natural light']\n",
      "--------\n",
      "For zipcode 11238, the available sun exposure categories are: ['Bright & sun drenched' 'Limited natural light' 'Moderate sunlight']\n",
      "--------\n"
     ]
    }
   ],
   "source": [
    "sun_exposure_per_zipcode = filtered_sun_exposure.groupby('zipcode')['sun_exposure_cat'].unique()\n",
    "sun_exposure_per_zipcode\n",
    "\n",
    "for zipcode, sun_exposure in sun_exposure_per_zipcode.items():\n",
    "    print(f\"For zipcode {zipcode}, the available sun exposure categories are: {sun_exposure}\")\n",
    "    print(\"--------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "8ecba891",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zipcode</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">11215</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2874.000000</td>\n",
       "      <td>474.581921</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>3011.00</td>\n",
       "      <td>3422.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>4.0</td>\n",
       "      <td>4373.750000</td>\n",
       "      <td>476.539173</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4250.0</td>\n",
       "      <td>4623.75</td>\n",
       "      <td>4995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>6.0</td>\n",
       "      <td>4098.333333</td>\n",
       "      <td>1501.468170</td>\n",
       "      <td>2950.0</td>\n",
       "      <td>2950.0</td>\n",
       "      <td>3350.0</td>\n",
       "      <td>5433.75</td>\n",
       "      <td>5995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>38.0</td>\n",
       "      <td>3752.184211</td>\n",
       "      <td>1726.856382</td>\n",
       "      <td>2025.0</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>3300.0</td>\n",
       "      <td>4375.00</td>\n",
       "      <td>8700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">11217</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>6.0</td>\n",
       "      <td>4540.833333</td>\n",
       "      <td>2033.593904</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>3897.5</td>\n",
       "      <td>6386.25</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>35.0</td>\n",
       "      <td>4142.000000</td>\n",
       "      <td>882.366037</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>3400.0</td>\n",
       "      <td>4100.0</td>\n",
       "      <td>4700.00</td>\n",
       "      <td>6534.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11218</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3050.000000</td>\n",
       "      <td>282.842712</td>\n",
       "      <td>2850.0</td>\n",
       "      <td>2950.0</td>\n",
       "      <td>3050.0</td>\n",
       "      <td>3150.00</td>\n",
       "      <td>3250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">11225</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2861.666667</td>\n",
       "      <td>1674.315781</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>3345.00</td>\n",
       "      <td>4795.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>7.0</td>\n",
       "      <td>3455.142857</td>\n",
       "      <td>1126.808979</td>\n",
       "      <td>2520.0</td>\n",
       "      <td>2520.0</td>\n",
       "      <td>3300.0</td>\n",
       "      <td>3863.00</td>\n",
       "      <td>5600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11226</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>30.0</td>\n",
       "      <td>3073.200000</td>\n",
       "      <td>466.162204</td>\n",
       "      <td>2350.0</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2875.0</td>\n",
       "      <td>3290.00</td>\n",
       "      <td>4500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">11238</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4530.000000</td>\n",
       "      <td>380.131556</td>\n",
       "      <td>3850.0</td>\n",
       "      <td>4700.0</td>\n",
       "      <td>4700.0</td>\n",
       "      <td>4700.00</td>\n",
       "      <td>4700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5500.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>5500.00</td>\n",
       "      <td>5500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4900.000000</td>\n",
       "      <td>1414.213562</td>\n",
       "      <td>3900.0</td>\n",
       "      <td>4400.0</td>\n",
       "      <td>4900.0</td>\n",
       "      <td>5400.00</td>\n",
       "      <td>5900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>28.0</td>\n",
       "      <td>4084.892857</td>\n",
       "      <td>999.892933</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>3350.0</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4300.00</td>\n",
       "      <td>6245.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               count         mean          std     min  \\\n",
       "zipcode sun_exposure_cat                                                 \n",
       "11215   Bright & sun drenched    3.0  2874.000000   474.581921  2600.0   \n",
       "        Limited natural light    4.0  4373.750000   476.539173  4000.0   \n",
       "        Moderate sunlight        6.0  4098.333333  1501.468170  2950.0   \n",
       "        No sunlight data        38.0  3752.184211  1726.856382  2025.0   \n",
       "11217   Limited natural light    6.0  4540.833333  2033.593904  2800.0   \n",
       "        Moderate sunlight        1.0  2800.000000          NaN  2800.0   \n",
       "        No sunlight data        35.0  4142.000000   882.366037  3000.0   \n",
       "11218   No sunlight data         2.0  3050.000000   282.842712  2850.0   \n",
       "11225   Limited natural light    3.0  2861.666667  1674.315781  1895.0   \n",
       "        No sunlight data         7.0  3455.142857  1126.808979  2520.0   \n",
       "11226   No sunlight data        30.0  3073.200000   466.162204  2350.0   \n",
       "11238   Bright & sun drenched    5.0  4530.000000   380.131556  3850.0   \n",
       "        Limited natural light    1.0  5500.000000          NaN  5500.0   \n",
       "        Moderate sunlight        2.0  4900.000000  1414.213562  3900.0   \n",
       "        No sunlight data        28.0  4084.892857   999.892933  2800.0   \n",
       "\n",
       "                                  25%     50%      75%     max  \n",
       "zipcode sun_exposure_cat                                        \n",
       "11215   Bright & sun drenched  2600.0  2600.0  3011.00  3422.0  \n",
       "        Limited natural light  4000.0  4250.0  4623.75  4995.0  \n",
       "        Moderate sunlight      2950.0  3350.0  5433.75  5995.0  \n",
       "        No sunlight data       2600.0  3300.0  4375.00  8700.0  \n",
       "11217   Limited natural light  2800.0  3897.5  6386.25  7000.0  \n",
       "        Moderate sunlight      2800.0  2800.0  2800.00  2800.0  \n",
       "        No sunlight data       3400.0  4100.0  4700.00  6534.0  \n",
       "11218   No sunlight data       2950.0  3050.0  3150.00  3250.0  \n",
       "11225   Limited natural light  1895.0  1895.0  3345.00  4795.0  \n",
       "        No sunlight data       2520.0  3300.0  3863.00  5600.0  \n",
       "11226   No sunlight data       2800.0  2875.0  3290.00  4500.0  \n",
       "11238   Bright & sun drenched  4700.0  4700.0  4700.00  4700.0  \n",
       "        Limited natural light  5500.0  5500.0  5500.00  5500.0  \n",
       "        Moderate sunlight      4400.0  4900.0  5400.00  5900.0  \n",
       "        No sunlight data       3350.0  4000.0  4300.00  6245.0  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged.groupby(['zipcode', 'sun_exposure_cat'])['rent'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "af8e7fae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode  sun_exposure_cat     \n",
       "11215    Bright & sun drenched    2600.0\n",
       "         Limited natural light    4250.0\n",
       "         Moderate sunlight        3350.0\n",
       "         No sunlight data         3300.0\n",
       "11217    Limited natural light    3897.5\n",
       "         Moderate sunlight        2800.0\n",
       "         No sunlight data         4100.0\n",
       "11218    No sunlight data         3050.0\n",
       "11225    Limited natural light    1895.0\n",
       "         No sunlight data         3300.0\n",
       "11226    No sunlight data         2875.0\n",
       "11238    Bright & sun drenched    4700.0\n",
       "         Limited natural light    5500.0\n",
       "         Moderate sunlight        4900.0\n",
       "         No sunlight data         4000.0\n",
       "Name: rent, dtype: float64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_merged\n",
    "     .groupby(['zipcode', 'sun_exposure_cat'])['rent']\n",
    "     .median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "c1d99ab0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zipcode</th>\n",
       "      <th>beds</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">11215</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">0.0</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3422.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3422.0</td>\n",
       "      <td>3422.00</td>\n",
       "      <td>3422.0</td>\n",
       "      <td>3422.00</td>\n",
       "      <td>3422.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2950.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2950.0</td>\n",
       "      <td>2950.00</td>\n",
       "      <td>2950.0</td>\n",
       "      <td>2950.00</td>\n",
       "      <td>2950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>6.0</td>\n",
       "      <td>2562.500000</td>\n",
       "      <td>966.792377</td>\n",
       "      <td>2025.0</td>\n",
       "      <td>2025.00</td>\n",
       "      <td>2212.5</td>\n",
       "      <td>2400.00</td>\n",
       "      <td>4500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1.0</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2600.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2600.00</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2600.00</td>\n",
       "      <td>2600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3750.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750.0</td>\n",
       "      <td>3750.00</td>\n",
       "      <td>3750.0</td>\n",
       "      <td>3750.00</td>\n",
       "      <td>3750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>16.0</td>\n",
       "      <td>3079.250000</td>\n",
       "      <td>616.773594</td>\n",
       "      <td>2153.0</td>\n",
       "      <td>2575.00</td>\n",
       "      <td>3150.0</td>\n",
       "      <td>3400.00</td>\n",
       "      <td>4690.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.5</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2600.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2600.00</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2600.00</td>\n",
       "      <td>2600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>10.0</td>\n",
       "      <td>4444.000000</td>\n",
       "      <td>1499.815989</td>\n",
       "      <td>2850.0</td>\n",
       "      <td>3437.25</td>\n",
       "      <td>3999.5</td>\n",
       "      <td>4869.75</td>\n",
       "      <td>7995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.5</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>4000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">3.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4747.500000</td>\n",
       "      <td>350.017857</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>4623.75</td>\n",
       "      <td>4747.5</td>\n",
       "      <td>4871.25</td>\n",
       "      <td>4995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>4.0</td>\n",
       "      <td>7075.000000</td>\n",
       "      <td>2030.394050</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>5925.00</td>\n",
       "      <td>7550.0</td>\n",
       "      <td>8700.00</td>\n",
       "      <td>8700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>2.0</td>\n",
       "      <td>5995.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5995.0</td>\n",
       "      <td>5995.00</td>\n",
       "      <td>5995.0</td>\n",
       "      <td>5995.00</td>\n",
       "      <td>5995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"7\" valign=\"top\">11217</th>\n",
       "      <th>0.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>12.0</td>\n",
       "      <td>3430.250000</td>\n",
       "      <td>142.622913</td>\n",
       "      <td>3258.0</td>\n",
       "      <td>3300.00</td>\n",
       "      <td>3400.0</td>\n",
       "      <td>3565.25</td>\n",
       "      <td>3656.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>16.0</td>\n",
       "      <td>4126.437500</td>\n",
       "      <td>592.932820</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>4200.0</td>\n",
       "      <td>4588.25</td>\n",
       "      <td>4800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6281.666667</td>\n",
       "      <td>1116.807205</td>\n",
       "      <td>4995.0</td>\n",
       "      <td>5922.50</td>\n",
       "      <td>6850.0</td>\n",
       "      <td>6925.00</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>5.0</td>\n",
       "      <td>5656.800000</td>\n",
       "      <td>818.340516</td>\n",
       "      <td>4400.0</td>\n",
       "      <td>5400.00</td>\n",
       "      <td>5800.0</td>\n",
       "      <td>6150.00</td>\n",
       "      <td>6534.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4750.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4750.0</td>\n",
       "      <td>4750.00</td>\n",
       "      <td>4750.0</td>\n",
       "      <td>4750.00</td>\n",
       "      <td>4750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">11218</th>\n",
       "      <th>1.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2850.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2850.0</td>\n",
       "      <td>2850.00</td>\n",
       "      <td>2850.0</td>\n",
       "      <td>2850.00</td>\n",
       "      <td>2850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3250.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3250.0</td>\n",
       "      <td>3250.00</td>\n",
       "      <td>3250.0</td>\n",
       "      <td>3250.00</td>\n",
       "      <td>3250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">11225</th>\n",
       "      <th>0.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2520.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2520.0</td>\n",
       "      <td>2520.00</td>\n",
       "      <td>2520.0</td>\n",
       "      <td>2520.00</td>\n",
       "      <td>2520.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1895.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>1895.00</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>1895.00</td>\n",
       "      <td>1895.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3300.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3300.0</td>\n",
       "      <td>3300.00</td>\n",
       "      <td>3300.0</td>\n",
       "      <td>3300.00</td>\n",
       "      <td>3300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4000.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>4000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4663.000000</td>\n",
       "      <td>1325.118108</td>\n",
       "      <td>3726.0</td>\n",
       "      <td>4194.50</td>\n",
       "      <td>4663.0</td>\n",
       "      <td>5131.50</td>\n",
       "      <td>5600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4795.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4795.0</td>\n",
       "      <td>4795.00</td>\n",
       "      <td>4795.0</td>\n",
       "      <td>4795.00</td>\n",
       "      <td>4795.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">11226</th>\n",
       "      <th>0.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2456.666667</td>\n",
       "      <td>184.752086</td>\n",
       "      <td>2350.0</td>\n",
       "      <td>2350.00</td>\n",
       "      <td>2350.0</td>\n",
       "      <td>2510.00</td>\n",
       "      <td>2670.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>18.0</td>\n",
       "      <td>2904.444444</td>\n",
       "      <td>151.391671</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2866.0</td>\n",
       "      <td>2938.00</td>\n",
       "      <td>3290.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>7.0</td>\n",
       "      <td>3513.428571</td>\n",
       "      <td>448.024500</td>\n",
       "      <td>3200.0</td>\n",
       "      <td>3300.00</td>\n",
       "      <td>3400.0</td>\n",
       "      <td>3447.00</td>\n",
       "      <td>4500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3976.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3976.0</td>\n",
       "      <td>3976.00</td>\n",
       "      <td>3976.0</td>\n",
       "      <td>3976.00</td>\n",
       "      <td>3976.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">11238</th>\n",
       "      <th>0.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>8.0</td>\n",
       "      <td>3179.375000</td>\n",
       "      <td>453.111761</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2912.50</td>\n",
       "      <td>2997.5</td>\n",
       "      <td>3298.75</td>\n",
       "      <td>3895.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>7.0</td>\n",
       "      <td>3971.428571</td>\n",
       "      <td>345.032780</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>3750.00</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4250.00</td>\n",
       "      <td>4300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2.0</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>4.0</td>\n",
       "      <td>4700.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4700.0</td>\n",
       "      <td>4700.00</td>\n",
       "      <td>4700.0</td>\n",
       "      <td>4700.00</td>\n",
       "      <td>4700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3900.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900.0</td>\n",
       "      <td>3900.00</td>\n",
       "      <td>3900.0</td>\n",
       "      <td>3900.00</td>\n",
       "      <td>3900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No sunlight data</th>\n",
       "      <td>13.0</td>\n",
       "      <td>4703.230769</td>\n",
       "      <td>1049.702272</td>\n",
       "      <td>3350.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>4222.0</td>\n",
       "      <td>5095.00</td>\n",
       "      <td>6245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">3.0</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3850.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3850.0</td>\n",
       "      <td>3850.00</td>\n",
       "      <td>3850.0</td>\n",
       "      <td>3850.00</td>\n",
       "      <td>3850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5500.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>5500.00</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>5500.00</td>\n",
       "      <td>5500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5900.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>5900.00</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>5900.00</td>\n",
       "      <td>5900.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    count         mean          std     min  \\\n",
       "zipcode beds sun_exposure_cat                                                 \n",
       "11215   0.0  Bright & sun drenched    1.0  3422.000000          NaN  3422.0   \n",
       "             Moderate sunlight        3.0  2950.000000     0.000000  2950.0   \n",
       "             No sunlight data         6.0  2562.500000   966.792377  2025.0   \n",
       "        1.0  Bright & sun drenched    2.0  2600.000000     0.000000  2600.0   \n",
       "             Moderate sunlight        1.0  3750.000000          NaN  3750.0   \n",
       "             No sunlight data        16.0  3079.250000   616.773594  2153.0   \n",
       "        1.5  No sunlight data         2.0  2600.000000     0.000000  2600.0   \n",
       "        2.0  No sunlight data        10.0  4444.000000  1499.815989  2850.0   \n",
       "        2.5  Limited natural light    2.0  4000.000000     0.000000  4000.0   \n",
       "        3.0  Limited natural light    2.0  4747.500000   350.017857  4500.0   \n",
       "             No sunlight data         4.0  7075.000000  2030.394050  4500.0   \n",
       "        4.0  Moderate sunlight        2.0  5995.000000     0.000000  5995.0   \n",
       "11217   0.0  No sunlight data        12.0  3430.250000   142.622913  3258.0   \n",
       "        1.0  Limited natural light    3.0  2800.000000     0.000000  2800.0   \n",
       "             No sunlight data        16.0  4126.437500   592.932820  3000.0   \n",
       "        2.0  Limited natural light    3.0  6281.666667  1116.807205  4995.0   \n",
       "             Moderate sunlight        1.0  2800.000000          NaN  2800.0   \n",
       "             No sunlight data         5.0  5656.800000   818.340516  4400.0   \n",
       "        3.0  No sunlight data         2.0  4750.000000     0.000000  4750.0   \n",
       "11218   1.0  No sunlight data         1.0  2850.000000          NaN  2850.0   \n",
       "        2.0  No sunlight data         1.0  3250.000000          NaN  3250.0   \n",
       "11225   0.0  No sunlight data         3.0  2520.000000     0.000000  2520.0   \n",
       "        1.0  Limited natural light    2.0  1895.000000     0.000000  1895.0   \n",
       "             No sunlight data         1.0  3300.000000          NaN  3300.0   \n",
       "        2.0  No sunlight data         1.0  4000.000000          NaN  4000.0   \n",
       "        3.0  No sunlight data         2.0  4663.000000  1325.118108  3726.0   \n",
       "        4.0  Limited natural light    1.0  4795.000000          NaN  4795.0   \n",
       "11226   0.0  No sunlight data         3.0  2456.666667   184.752086  2350.0   \n",
       "        1.0  No sunlight data        18.0  2904.444444   151.391671  2800.0   \n",
       "        2.0  No sunlight data         7.0  3513.428571   448.024500  3200.0   \n",
       "        3.0  No sunlight data         2.0  3976.000000     0.000000  3976.0   \n",
       "11238   0.0  No sunlight data         8.0  3179.375000   453.111761  2800.0   \n",
       "        1.0  No sunlight data         7.0  3971.428571   345.032780  3500.0   \n",
       "        2.0  Bright & sun drenched    4.0  4700.000000     0.000000  4700.0   \n",
       "             Moderate sunlight        1.0  3900.000000          NaN  3900.0   \n",
       "             No sunlight data        13.0  4703.230769  1049.702272  3350.0   \n",
       "        3.0  Bright & sun drenched    1.0  3850.000000          NaN  3850.0   \n",
       "             Limited natural light    1.0  5500.000000          NaN  5500.0   \n",
       "        4.0  Moderate sunlight        1.0  5900.000000          NaN  5900.0   \n",
       "\n",
       "                                        25%     50%      75%     max  \n",
       "zipcode beds sun_exposure_cat                                         \n",
       "11215   0.0  Bright & sun drenched  3422.00  3422.0  3422.00  3422.0  \n",
       "             Moderate sunlight      2950.00  2950.0  2950.00  2950.0  \n",
       "             No sunlight data       2025.00  2212.5  2400.00  4500.0  \n",
       "        1.0  Bright & sun drenched  2600.00  2600.0  2600.00  2600.0  \n",
       "             Moderate sunlight      3750.00  3750.0  3750.00  3750.0  \n",
       "             No sunlight data       2575.00  3150.0  3400.00  4690.0  \n",
       "        1.5  No sunlight data       2600.00  2600.0  2600.00  2600.0  \n",
       "        2.0  No sunlight data       3437.25  3999.5  4869.75  7995.0  \n",
       "        2.5  Limited natural light  4000.00  4000.0  4000.00  4000.0  \n",
       "        3.0  Limited natural light  4623.75  4747.5  4871.25  4995.0  \n",
       "             No sunlight data       5925.00  7550.0  8700.00  8700.0  \n",
       "        4.0  Moderate sunlight      5995.00  5995.0  5995.00  5995.0  \n",
       "11217   0.0  No sunlight data       3300.00  3400.0  3565.25  3656.0  \n",
       "        1.0  Limited natural light  2800.00  2800.0  2800.00  2800.0  \n",
       "             No sunlight data       4000.00  4200.0  4588.25  4800.0  \n",
       "        2.0  Limited natural light  5922.50  6850.0  6925.00  7000.0  \n",
       "             Moderate sunlight      2800.00  2800.0  2800.00  2800.0  \n",
       "             No sunlight data       5400.00  5800.0  6150.00  6534.0  \n",
       "        3.0  No sunlight data       4750.00  4750.0  4750.00  4750.0  \n",
       "11218   1.0  No sunlight data       2850.00  2850.0  2850.00  2850.0  \n",
       "        2.0  No sunlight data       3250.00  3250.0  3250.00  3250.0  \n",
       "11225   0.0  No sunlight data       2520.00  2520.0  2520.00  2520.0  \n",
       "        1.0  Limited natural light  1895.00  1895.0  1895.00  1895.0  \n",
       "             No sunlight data       3300.00  3300.0  3300.00  3300.0  \n",
       "        2.0  No sunlight data       4000.00  4000.0  4000.00  4000.0  \n",
       "        3.0  No sunlight data       4194.50  4663.0  5131.50  5600.0  \n",
       "        4.0  Limited natural light  4795.00  4795.0  4795.00  4795.0  \n",
       "11226   0.0  No sunlight data       2350.00  2350.0  2510.00  2670.0  \n",
       "        1.0  No sunlight data       2800.00  2866.0  2938.00  3290.0  \n",
       "        2.0  No sunlight data       3300.00  3400.0  3447.00  4500.0  \n",
       "        3.0  No sunlight data       3976.00  3976.0  3976.00  3976.0  \n",
       "11238   0.0  No sunlight data       2912.50  2997.5  3298.75  3895.0  \n",
       "        1.0  No sunlight data       3750.00  4000.0  4250.00  4300.0  \n",
       "        2.0  Bright & sun drenched  4700.00  4700.0  4700.00  4700.0  \n",
       "             Moderate sunlight      3900.00  3900.0  3900.00  3900.0  \n",
       "             No sunlight data       4000.00  4222.0  5095.00  6245.0  \n",
       "        3.0  Bright & sun drenched  3850.00  3850.0  3850.00  3850.0  \n",
       "             Limited natural light  5500.00  5500.0  5500.00  5500.0  \n",
       "        4.0  Moderate sunlight      5900.00  5900.0  5900.00  5900.0  "
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_merged\n",
    "     .groupby(['zipcode','beds', 'sun_exposure_cat' ])['rent']\n",
    "     .describe()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "7c665b52",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zipcode</th>\n",
       "      <th>beds</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"7\" valign=\"top\">11215</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">0.0</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3422.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3422.0</td>\n",
       "      <td>3422.00</td>\n",
       "      <td>3422.0</td>\n",
       "      <td>3422.00</td>\n",
       "      <td>3422.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2950.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2950.0</td>\n",
       "      <td>2950.00</td>\n",
       "      <td>2950.0</td>\n",
       "      <td>2950.00</td>\n",
       "      <td>2950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.0</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2600.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2600.00</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2600.00</td>\n",
       "      <td>2600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3750.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750.0</td>\n",
       "      <td>3750.00</td>\n",
       "      <td>3750.0</td>\n",
       "      <td>3750.00</td>\n",
       "      <td>3750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.5</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>4000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4747.500000</td>\n",
       "      <td>350.017857</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>4623.75</td>\n",
       "      <td>4747.5</td>\n",
       "      <td>4871.25</td>\n",
       "      <td>4995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>2.0</td>\n",
       "      <td>5995.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5995.0</td>\n",
       "      <td>5995.00</td>\n",
       "      <td>5995.0</td>\n",
       "      <td>5995.00</td>\n",
       "      <td>5995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">11217</th>\n",
       "      <th>1.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6281.666667</td>\n",
       "      <td>1116.807205</td>\n",
       "      <td>4995.0</td>\n",
       "      <td>5922.50</td>\n",
       "      <td>6850.0</td>\n",
       "      <td>6925.00</td>\n",
       "      <td>7000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>2800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">11225</th>\n",
       "      <th>1.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1895.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>1895.00</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>1895.00</td>\n",
       "      <td>1895.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4795.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4795.0</td>\n",
       "      <td>4795.00</td>\n",
       "      <td>4795.0</td>\n",
       "      <td>4795.00</td>\n",
       "      <td>4795.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">11238</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">2.0</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>4.0</td>\n",
       "      <td>4700.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4700.0</td>\n",
       "      <td>4700.00</td>\n",
       "      <td>4700.0</td>\n",
       "      <td>4700.00</td>\n",
       "      <td>4700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3900.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900.0</td>\n",
       "      <td>3900.00</td>\n",
       "      <td>3900.0</td>\n",
       "      <td>3900.00</td>\n",
       "      <td>3900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">3.0</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3850.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3850.0</td>\n",
       "      <td>3850.00</td>\n",
       "      <td>3850.0</td>\n",
       "      <td>3850.00</td>\n",
       "      <td>3850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5500.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>5500.00</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>5500.00</td>\n",
       "      <td>5500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5900.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>5900.00</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>5900.00</td>\n",
       "      <td>5900.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    count         mean          std     min  \\\n",
       "zipcode beds sun_exposure_cat                                                 \n",
       "11215   0.0  Bright & sun drenched    1.0  3422.000000          NaN  3422.0   \n",
       "             Moderate sunlight        3.0  2950.000000     0.000000  2950.0   \n",
       "        1.0  Bright & sun drenched    2.0  2600.000000     0.000000  2600.0   \n",
       "             Moderate sunlight        1.0  3750.000000          NaN  3750.0   \n",
       "        2.5  Limited natural light    2.0  4000.000000     0.000000  4000.0   \n",
       "        3.0  Limited natural light    2.0  4747.500000   350.017857  4500.0   \n",
       "        4.0  Moderate sunlight        2.0  5995.000000     0.000000  5995.0   \n",
       "11217   1.0  Limited natural light    3.0  2800.000000     0.000000  2800.0   \n",
       "        2.0  Limited natural light    3.0  6281.666667  1116.807205  4995.0   \n",
       "             Moderate sunlight        1.0  2800.000000          NaN  2800.0   \n",
       "11225   1.0  Limited natural light    2.0  1895.000000     0.000000  1895.0   \n",
       "        4.0  Limited natural light    1.0  4795.000000          NaN  4795.0   \n",
       "11238   2.0  Bright & sun drenched    4.0  4700.000000     0.000000  4700.0   \n",
       "             Moderate sunlight        1.0  3900.000000          NaN  3900.0   \n",
       "        3.0  Bright & sun drenched    1.0  3850.000000          NaN  3850.0   \n",
       "             Limited natural light    1.0  5500.000000          NaN  5500.0   \n",
       "        4.0  Moderate sunlight        1.0  5900.000000          NaN  5900.0   \n",
       "\n",
       "                                        25%     50%      75%     max  \n",
       "zipcode beds sun_exposure_cat                                         \n",
       "11215   0.0  Bright & sun drenched  3422.00  3422.0  3422.00  3422.0  \n",
       "             Moderate sunlight      2950.00  2950.0  2950.00  2950.0  \n",
       "        1.0  Bright & sun drenched  2600.00  2600.0  2600.00  2600.0  \n",
       "             Moderate sunlight      3750.00  3750.0  3750.00  3750.0  \n",
       "        2.5  Limited natural light  4000.00  4000.0  4000.00  4000.0  \n",
       "        3.0  Limited natural light  4623.75  4747.5  4871.25  4995.0  \n",
       "        4.0  Moderate sunlight      5995.00  5995.0  5995.00  5995.0  \n",
       "11217   1.0  Limited natural light  2800.00  2800.0  2800.00  2800.0  \n",
       "        2.0  Limited natural light  5922.50  6850.0  6925.00  7000.0  \n",
       "             Moderate sunlight      2800.00  2800.0  2800.00  2800.0  \n",
       "11225   1.0  Limited natural light  1895.00  1895.0  1895.00  1895.0  \n",
       "        4.0  Limited natural light  4795.00  4795.0  4795.00  4795.0  \n",
       "11238   2.0  Bright & sun drenched  4700.00  4700.0  4700.00  4700.0  \n",
       "             Moderate sunlight      3900.00  3900.0  3900.00  3900.0  \n",
       "        3.0  Bright & sun drenched  3850.00  3850.0  3850.00  3850.0  \n",
       "             Limited natural light  5500.00  5500.0  5500.00  5500.0  \n",
       "        4.0  Moderate sunlight      5900.00  5900.0  5900.00  5900.0  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(filtered_sun_exposure\n",
    "     .groupby(['zipcode','beds', 'sun_exposure_cat' ])['rent']\n",
    "     .describe()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8d8c85c",
   "metadata": {},
   "source": [
    "## Affordability for Living Alone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "235cec46",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    87707.0\n",
       "11217    85813.0\n",
       "11225    41497.0\n",
       "11238    67950.0\n",
       "Name: per capita income, dtype: float64"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(filtered_sun_exposure\n",
    "     .groupby(['zipcode'])['per capita income']\n",
    "     .median()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "a94c549e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged['affordable_rent_single'] = df_merged['per capita income'] / 40\n",
    "df_merged['affordable_rent_couple'] = df_merged['median household income']/40"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "2902cd0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged['is_affordable_individual'] = df_merged['rent'] <= df_merged['affordable_rent_single']\n",
    "df_merged['is_affordable_couple']= df_merged['rent'] <= df_merged['affordable_rent_couple']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "ac70b455",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>floor</th>\n",
       "      <th>median age</th>\n",
       "      <th>per capita income</th>\n",
       "      <th>median household income</th>\n",
       "      <th>affordable_rent_single</th>\n",
       "      <th>affordable_rent_couple</th>\n",
       "      <th>is_affordable_individual</th>\n",
       "      <th>is_affordable_couple</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>l-2g3vm2ptsq8i</td>\n",
       "      <td>11225</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3726</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3726</td>\n",
       "      <td>2</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497</td>\n",
       "      <td>68542</td>\n",
       "      <td>1037.425</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>l-2in0401r3l0j</td>\n",
       "      <td>11215</td>\n",
       "      <td>1B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "      <td>1</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>l-dgbncnljpk2t</td>\n",
       "      <td>11217</td>\n",
       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>2</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>3</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200</td>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>3</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index    listing_path zipcode unit_number building_class  beds   size  \\\n",
       "0      0  l-2g3vm2ptsq8i   11225           2    rental unit   3.0    NaN   \n",
       "1      1  l-2in0401r3l0j   11215          1B    rental unit   2.0    NaN   \n",
       "2      3  l-dgbncnljpk2t   11217          B2    rental unit   3.0  900.0   \n",
       "3    199  l-k5pmp1c6dcau   11215           3    rental unit   1.0    NaN   \n",
       "4    200  l-ok0278ecbrpc   11217         312    rental unit   1.0    NaN   \n",
       "\n",
       "   rent   sun_exposure_cat                                       sun_exposure  \\\n",
       "0  3726   No sunlight data    No sunlight data available and the rent is 3726   \n",
       "1  4500   No sunlight data    No sunlight data available and the rent is 4500   \n",
       "2  4750   No sunlight data    No sunlight data available and the rent is 4750   \n",
       "3  3750  Moderate sunlight  This apartment has moderate sunlight and the r...   \n",
       "4  4000   No sunlight data    No sunlight data available and the rent is 4000   \n",
       "\n",
       "  floor  median age  per capita income  median household income  \\\n",
       "0     2        36.1              41497                    68542   \n",
       "1     1        37.0              87707                   156930   \n",
       "2     2        35.5              85813                   133269   \n",
       "3     3        37.0              87707                   156930   \n",
       "4     3        35.5              85813                   133269   \n",
       "\n",
       "   affordable_rent_single  affordable_rent_couple  is_affordable_individual  \\\n",
       "0                1037.425                1713.550                     False   \n",
       "1                2192.675                3923.250                     False   \n",
       "2                2145.325                3331.725                     False   \n",
       "3                2192.675                3923.250                     False   \n",
       "4                2145.325                3331.725                     False   \n",
       "\n",
       "   is_affordable_couple  \n",
       "0                 False  \n",
       "1                 False  \n",
       "2                 False  \n",
       "3                  True  \n",
       "4                 False  "
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "a51e3b54",
   "metadata": {},
   "outputs": [],
   "source": [
    "indiv_affordability_by_zipcode = df_merged.groupby('zipcode')['is_affordable_individual'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "4bea9cf7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    0.078431\n",
       "11217    0.000000\n",
       "11218    0.000000\n",
       "11225    0.000000\n",
       "11226    0.000000\n",
       "11238    0.000000\n",
       "Name: is_affordable_individual, dtype: float64"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indiv_affordability_by_zipcode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "f0555806",
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_sun_exposure = df_merged[df_merged['sun_exposure_cat'] != 'No sunlight data']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "96069c44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    0.0\n",
       "11217    0.0\n",
       "11225    0.0\n",
       "11238    0.0\n",
       "Name: is_affordable_individual, dtype: float64"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_sun_exposure.groupby('zipcode')['is_affordable_individual'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "5d23f1b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged['rent_difference_single'] = df_merged['rent'] - df_merged['affordable_rent_single']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "7edff3df",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>l-2in0401r3l0j</td>\n",
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       "      <td>1B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "      <td>1</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2307.325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
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       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>2</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2604.675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>3</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>1557.325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200</td>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>3</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1854.675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>734</td>\n",
       "      <td>l-ue6jib37qqnf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>4</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1801.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>757</td>\n",
       "      <td>l-metf0tnqb3oa</td>\n",
       "      <td>11238</td>\n",
       "      <td>6B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>6</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2301.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>781</td>\n",
       "      <td>l-qtrv180v4kc8</td>\n",
       "      <td>11238</td>\n",
       "      <td>504</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>5</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1801.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>782</td>\n",
       "      <td>l-v22eed67chvl</td>\n",
       "      <td>11238</td>\n",
       "      <td>501</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "      <td>5</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2501.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>783</td>\n",
       "      <td>l-rk0ue9fad9jb</td>\n",
       "      <td>11238</td>\n",
       "      <td>404</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2995</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 2995</td>\n",
       "      <td>4</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1296.250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>171 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds   size  \\\n",
       "0        0  l-2g3vm2ptsq8i   11225           2    rental unit   3.0    NaN   \n",
       "1        1  l-2in0401r3l0j   11215          1B    rental unit   2.0    NaN   \n",
       "2        3  l-dgbncnljpk2t   11217          B2    rental unit   3.0  900.0   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0    NaN   \n",
       "4      200  l-ok0278ecbrpc   11217         312    rental unit   1.0    NaN   \n",
       "..     ...             ...     ...         ...            ...   ...    ...   \n",
       "166    734  l-ue6jib37qqnf   11238           4    rental unit   1.0    NaN   \n",
       "167    757  l-metf0tnqb3oa   11238          6B    rental unit   2.0    NaN   \n",
       "168    781  l-qtrv180v4kc8   11238         504    rental unit   1.0    NaN   \n",
       "169    782  l-v22eed67chvl   11238         501    rental unit   2.0    NaN   \n",
       "170    783  l-rk0ue9fad9jb   11238         404    rental unit   0.0    NaN   \n",
       "\n",
       "     rent   sun_exposure_cat  \\\n",
       "0    3726   No sunlight data   \n",
       "1    4500   No sunlight data   \n",
       "2    4750   No sunlight data   \n",
       "3    3750  Moderate sunlight   \n",
       "4    4000   No sunlight data   \n",
       "..    ...                ...   \n",
       "166  3500   No sunlight data   \n",
       "167  4000   No sunlight data   \n",
       "168  3500   No sunlight data   \n",
       "169  4200   No sunlight data   \n",
       "170  2995   No sunlight data   \n",
       "\n",
       "                                          sun_exposure floor  median age  \\\n",
       "0      No sunlight data available and the rent is 3726     2        36.1   \n",
       "1      No sunlight data available and the rent is 4500     1        37.0   \n",
       "2      No sunlight data available and the rent is 4750     2        35.5   \n",
       "3    This apartment has moderate sunlight and the r...     3        37.0   \n",
       "4      No sunlight data available and the rent is 4000     3        35.5   \n",
       "..                                                 ...   ...         ...   \n",
       "166    No sunlight data available and the rent is 3500     4        35.3   \n",
       "167    No sunlight data available and the rent is 4000     6        35.3   \n",
       "168    No sunlight data available and the rent is 3500     5        35.3   \n",
       "169    No sunlight data available and the rent is 4200     5        35.3   \n",
       "170    No sunlight data available and the rent is 2995     4        35.3   \n",
       "\n",
       "     per capita income  median household income  affordable_rent_single  \\\n",
       "0                41497                    68542                1037.425   \n",
       "1                87707                   156930                2192.675   \n",
       "2                85813                   133269                2145.325   \n",
       "3                87707                   156930                2192.675   \n",
       "4                85813                   133269                2145.325   \n",
       "..                 ...                      ...                     ...   \n",
       "166              67950                   114427                1698.750   \n",
       "167              67950                   114427                1698.750   \n",
       "168              67950                   114427                1698.750   \n",
       "169              67950                   114427                1698.750   \n",
       "170              67950                   114427                1698.750   \n",
       "\n",
       "     affordable_rent_couple  is_affordable_individual  is_affordable_couple  \\\n",
       "0                  1713.550                     False                 False   \n",
       "1                  3923.250                     False                 False   \n",
       "2                  3331.725                     False                 False   \n",
       "3                  3923.250                     False                  True   \n",
       "4                  3331.725                     False                 False   \n",
       "..                      ...                       ...                   ...   \n",
       "166                2860.675                     False                 False   \n",
       "167                2860.675                     False                 False   \n",
       "168                2860.675                     False                 False   \n",
       "169                2860.675                     False                 False   \n",
       "170                2860.675                     False                 False   \n",
       "\n",
       "     rent_difference_single  \n",
       "0                  2688.575  \n",
       "1                  2307.325  \n",
       "2                  2604.675  \n",
       "3                  1557.325  \n",
       "4                  1854.675  \n",
       "..                      ...  \n",
       "166                1801.250  \n",
       "167                2301.250  \n",
       "168                1801.250  \n",
       "169                2501.250  \n",
       "170                1296.250  \n",
       "\n",
       "[171 rows x 19 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "3a8024d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "indiv_average_rent_difference_by_zipcode = df_merged.groupby('zipcode')['rent_difference_single'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "da96f212",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    1597.0\n",
       "11217    2022.0\n",
       "11218    1972.0\n",
       "11225    2240.0\n",
       "11226    2215.0\n",
       "11238    2533.0\n",
       "Name: rent_difference_single, dtype: float64"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indiv_average_rent_difference_by_zipcode.round()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "e19cef3f",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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   "source": [
    "# Calculate average rent and rent_difference for each zipcode\n",
    "df_avg_single = df_merged.groupby('zipcode')[['rent', 'affordable_rent_single']].mean().reset_index()\n",
    "\n",
    "# Melt the DataFrame to long format\n",
    "df_melted_single = df_avg_single.melt(id_vars='zipcode', value_vars=['rent', 'affordable_rent_single'])\n",
    "\n",
    "# Create small multiple bar charts\n",
    "chart = alt.Chart(df_melted_single).mark_bar().encode(\n",
    "    x='variable:N',  # variable column contains 'rent' and 'rent_difference'\n",
    "    y='value:Q',  # value column contains the corresponding values\n",
    "    color='variable:N',\n",
    "    column='zipcode:N'\n",
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    "    height=200\n",
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    "chart"
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  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "c2bb680f",
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       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"5.8.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 300, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-9a2dd96a9d66ca787e347fdd0449280f\"}, \"mark\": {\"type\": \"bar\"}, \"encoding\": {\"color\": {\"field\": \"variable\", \"type\": \"nominal\"}, \"column\": {\"field\": \"zipcode\", \"type\": \"nominal\"}, \"x\": {\"field\": \"variable\", \"type\": \"nominal\"}, \"y\": {\"field\": \"value\", \"type\": \"quantitative\"}}, \"height\": 200, \"width\": 200, \"$schema\": \"https://vega.github.io/schema/vega-lite/v5.8.0.json\", \"datasets\": {\"data-9a2dd96a9d66ca787e347fdd0449280f\": [{\"zipcode\": \"11215\", \"variable\": \"rent\", \"value\": 3790.0}, {\"zipcode\": \"11217\", \"variable\": \"rent\", \"value\": 4167.023809523809}, {\"zipcode\": \"11218\", \"variable\": \"rent\", \"value\": 3050.0}, {\"zipcode\": \"11225\", \"variable\": \"rent\", \"value\": 3277.1}, {\"zipcode\": \"11226\", \"variable\": \"rent\", \"value\": 3073.2}, {\"zipcode\": \"11238\", \"variable\": \"rent\", \"value\": 4231.305555555556}, {\"zipcode\": \"11215\", \"variable\": \"affordable_rent_single\", \"value\": 2192.675}, {\"zipcode\": \"11217\", \"variable\": \"affordable_rent_single\", \"value\": 2145.325}, {\"zipcode\": \"11218\", \"variable\": \"affordable_rent_single\", \"value\": 1077.825}, {\"zipcode\": \"11225\", \"variable\": \"affordable_rent_single\", \"value\": 1037.425}, {\"zipcode\": \"11226\", \"variable\": \"affordable_rent_single\", \"value\": 858.075}, {\"zipcode\": \"11238\", \"variable\": \"affordable_rent_single\", \"value\": 1698.75}, {\"zipcode\": \"11215\", \"variable\": \"rent_difference_single\", \"value\": 1597.325}, {\"zipcode\": \"11217\", \"variable\": \"rent_difference_single\", \"value\": 2021.6988095238096}, {\"zipcode\": \"11218\", \"variable\": \"rent_difference_single\", \"value\": 1972.1750000000002}, {\"zipcode\": \"11225\", \"variable\": \"rent_difference_single\", \"value\": 2239.675}, {\"zipcode\": \"11226\", \"variable\": \"rent_difference_single\", \"value\": 2215.125}, {\"zipcode\": \"11238\", \"variable\": \"rent_difference_single\", \"value\": 2532.5555555555557}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate average rent, affordable rent and rent_difference for each zipcode\n",
    "df_avg_single = df_merged.groupby('zipcode')[['rent', 'affordable_rent_single', 'rent_difference_single']].mean().reset_index()\n",
    "\n",
    "# Melt the DataFrame to long format\n",
    "df_melted_single = df_avg_single.melt(id_vars='zipcode', value_vars=['rent', 'affordable_rent_single', 'rent_difference_single'])\n",
    "\n",
    "# Create small multiple grouped bar charts\n",
    "chart = alt.Chart(df_melted_single).mark_bar().encode(\n",
    "    x='variable:N',  # variable column contains 'rent', 'affordable_rent' and 'rent_difference'\n",
    "    y='value:Q',  # value column contains the corresponding values\n",
    "    color='variable:N',\n",
    "    column='zipcode:N'\n",
    ").properties(\n",
    "    width=200,\n",
    "    height=200\n",
    ")\n",
    "\n",
    "chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "cbaefedf",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged['annualized_rent']=(df_merged['rent']*12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "9e63a8ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged['indiv_affordability_to_rent_ratio'] = df_merged['affordable_rent_single']/(df_merged['rent']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "3e10214c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>...</th>\n",
       "      <th>median age</th>\n",
       "      <th>per capita income</th>\n",
       "      <th>median household income</th>\n",
       "      <th>affordable_rent_single</th>\n",
       "      <th>affordable_rent_couple</th>\n",
       "      <th>is_affordable_individual</th>\n",
       "      <th>is_affordable_couple</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>l-2g3vm2ptsq8i</td>\n",
       "      <td>11225</td>\n",
       "      <td>2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3726</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3726</td>\n",
       "      <td>...</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497</td>\n",
       "      <td>68542</td>\n",
       "      <td>1037.425</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2688.575</td>\n",
       "      <td>44712</td>\n",
       "      <td>0.278429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>l-2in0401r3l0j</td>\n",
       "      <td>11215</td>\n",
       "      <td>1B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "      <td>...</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2307.325</td>\n",
       "      <td>54000</td>\n",
       "      <td>0.487261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>l-dgbncnljpk2t</td>\n",
       "      <td>11217</td>\n",
       "      <td>B2</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>...</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2604.675</td>\n",
       "      <td>57000</td>\n",
       "      <td>0.451647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200</td>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>...</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1854.675</td>\n",
       "      <td>48000</td>\n",
       "      <td>0.536331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>734</td>\n",
       "      <td>l-ue6jib37qqnf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>...</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1801.250</td>\n",
       "      <td>42000</td>\n",
       "      <td>0.485357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>757</td>\n",
       "      <td>l-metf0tnqb3oa</td>\n",
       "      <td>11238</td>\n",
       "      <td>6B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>...</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2301.250</td>\n",
       "      <td>48000</td>\n",
       "      <td>0.424687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>781</td>\n",
       "      <td>l-qtrv180v4kc8</td>\n",
       "      <td>11238</td>\n",
       "      <td>504</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>...</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1801.250</td>\n",
       "      <td>42000</td>\n",
       "      <td>0.485357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>782</td>\n",
       "      <td>l-v22eed67chvl</td>\n",
       "      <td>11238</td>\n",
       "      <td>501</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "      <td>...</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2501.250</td>\n",
       "      <td>50400</td>\n",
       "      <td>0.404464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>783</td>\n",
       "      <td>l-rk0ue9fad9jb</td>\n",
       "      <td>11238</td>\n",
       "      <td>404</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2995</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 2995</td>\n",
       "      <td>...</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1296.250</td>\n",
       "      <td>35940</td>\n",
       "      <td>0.567195</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>171 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds   size  \\\n",
       "0        0  l-2g3vm2ptsq8i   11225           2    rental unit   3.0    NaN   \n",
       "1        1  l-2in0401r3l0j   11215          1B    rental unit   2.0    NaN   \n",
       "2        3  l-dgbncnljpk2t   11217          B2    rental unit   3.0  900.0   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0    NaN   \n",
       "4      200  l-ok0278ecbrpc   11217         312    rental unit   1.0    NaN   \n",
       "..     ...             ...     ...         ...            ...   ...    ...   \n",
       "166    734  l-ue6jib37qqnf   11238           4    rental unit   1.0    NaN   \n",
       "167    757  l-metf0tnqb3oa   11238          6B    rental unit   2.0    NaN   \n",
       "168    781  l-qtrv180v4kc8   11238         504    rental unit   1.0    NaN   \n",
       "169    782  l-v22eed67chvl   11238         501    rental unit   2.0    NaN   \n",
       "170    783  l-rk0ue9fad9jb   11238         404    rental unit   0.0    NaN   \n",
       "\n",
       "     rent   sun_exposure_cat  \\\n",
       "0    3726   No sunlight data   \n",
       "1    4500   No sunlight data   \n",
       "2    4750   No sunlight data   \n",
       "3    3750  Moderate sunlight   \n",
       "4    4000   No sunlight data   \n",
       "..    ...                ...   \n",
       "166  3500   No sunlight data   \n",
       "167  4000   No sunlight data   \n",
       "168  3500   No sunlight data   \n",
       "169  4200   No sunlight data   \n",
       "170  2995   No sunlight data   \n",
       "\n",
       "                                          sun_exposure  ... median age  \\\n",
       "0      No sunlight data available and the rent is 3726  ...       36.1   \n",
       "1      No sunlight data available and the rent is 4500  ...       37.0   \n",
       "2      No sunlight data available and the rent is 4750  ...       35.5   \n",
       "3    This apartment has moderate sunlight and the r...  ...       37.0   \n",
       "4      No sunlight data available and the rent is 4000  ...       35.5   \n",
       "..                                                 ...  ...        ...   \n",
       "166    No sunlight data available and the rent is 3500  ...       35.3   \n",
       "167    No sunlight data available and the rent is 4000  ...       35.3   \n",
       "168    No sunlight data available and the rent is 3500  ...       35.3   \n",
       "169    No sunlight data available and the rent is 4200  ...       35.3   \n",
       "170    No sunlight data available and the rent is 2995  ...       35.3   \n",
       "\n",
       "     per capita income  median household income  affordable_rent_single  \\\n",
       "0                41497                    68542                1037.425   \n",
       "1                87707                   156930                2192.675   \n",
       "2                85813                   133269                2145.325   \n",
       "3                87707                   156930                2192.675   \n",
       "4                85813                   133269                2145.325   \n",
       "..                 ...                      ...                     ...   \n",
       "166              67950                   114427                1698.750   \n",
       "167              67950                   114427                1698.750   \n",
       "168              67950                   114427                1698.750   \n",
       "169              67950                   114427                1698.750   \n",
       "170              67950                   114427                1698.750   \n",
       "\n",
       "     affordable_rent_couple  is_affordable_individual  is_affordable_couple  \\\n",
       "0                  1713.550                     False                 False   \n",
       "1                  3923.250                     False                 False   \n",
       "2                  3331.725                     False                 False   \n",
       "3                  3923.250                     False                  True   \n",
       "4                  3331.725                     False                 False   \n",
       "..                      ...                       ...                   ...   \n",
       "166                2860.675                     False                 False   \n",
       "167                2860.675                     False                 False   \n",
       "168                2860.675                     False                 False   \n",
       "169                2860.675                     False                 False   \n",
       "170                2860.675                     False                 False   \n",
       "\n",
       "     rent_difference_single  annualized_rent  \\\n",
       "0                  2688.575            44712   \n",
       "1                  2307.325            54000   \n",
       "2                  2604.675            57000   \n",
       "3                  1557.325            45000   \n",
       "4                  1854.675            48000   \n",
       "..                      ...              ...   \n",
       "166                1801.250            42000   \n",
       "167                2301.250            48000   \n",
       "168                1801.250            42000   \n",
       "169                2501.250            50400   \n",
       "170                1296.250            35940   \n",
       "\n",
       "     indiv_affordability_to_rent_ratio  \n",
       "0                             0.278429  \n",
       "1                             0.487261  \n",
       "2                             0.451647  \n",
       "3                             0.584713  \n",
       "4                             0.536331  \n",
       "..                                 ...  \n",
       "166                           0.485357  \n",
       "167                           0.424687  \n",
       "168                           0.485357  \n",
       "169                           0.404464  \n",
       "170                           0.567195  \n",
       "\n",
       "[171 rows x 21 columns]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "e63afc29",
   "metadata": {},
   "outputs": [],
   "source": [
    "def map_ratio_to_icon(ratio):\n",
    "    if ratio <= 0.5:\n",
    "        return '🌗'  # Half sun (replace with your own icon)\n",
    "    elif ratio <= 1:\n",
    "        return '🌞'  # Full sun (replace with your own icon)\n",
    "    else:\n",
    "        return f'{ratio:.1f}🌞'  # More than 1 full sun\n",
    "\n",
    "df_merged['indiv_sun_exposure_icon'] = df_merged['indiv_affordability_to_rent_ratio'].apply(map_ratio_to_icon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "3219d3cc",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
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       "      <th>beds</th>\n",
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       "      <th>sun_exposure</th>\n",
       "      <th>...</th>\n",
       "      <th>per capita income</th>\n",
       "      <th>median household income</th>\n",
       "      <th>affordable_rent_single</th>\n",
       "      <th>affordable_rent_couple</th>\n",
       "      <th>is_affordable_individual</th>\n",
       "      <th>is_affordable_couple</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <td>l-2g3vm2ptsq8i</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3726</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3726</td>\n",
       "      <td>...</td>\n",
       "      <td>41497</td>\n",
       "      <td>68542</td>\n",
       "      <td>1037.425</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>44712</td>\n",
       "      <td>0.278429</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>l-2in0401r3l0j</td>\n",
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       "      <td>1B</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4500</td>\n",
       "      <td>...</td>\n",
       "      <td>87707</td>\n",
       "      <td>156930</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2307.325</td>\n",
       "      <td>54000</td>\n",
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       "      <th>2</th>\n",
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       "      <td>3.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4750</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4750</td>\n",
       "      <td>...</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2604.675</td>\n",
       "      <td>57000</td>\n",
       "      <td>0.451647</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
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       "      <td>False</td>\n",
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       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200</td>\n",
       "      <td>l-ok0278ecbrpc</td>\n",
       "      <td>11217</td>\n",
       "      <td>312</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>...</td>\n",
       "      <td>85813</td>\n",
       "      <td>133269</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <th>166</th>\n",
       "      <td>734</td>\n",
       "      <td>l-ue6jib37qqnf</td>\n",
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       "      <td>4</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
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       "      <td>114427</td>\n",
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       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>0.485357</td>\n",
       "      <td>🌗</td>\n",
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       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>757</td>\n",
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       "      <td>6B</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4000</td>\n",
       "      <td>...</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
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       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
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       "      <td>504</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 3500</td>\n",
       "      <td>...</td>\n",
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       "      <td>False</td>\n",
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       "      <td>42000</td>\n",
       "      <td>0.485357</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>782</td>\n",
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       "      <td>11238</td>\n",
       "      <td>501</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4200</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 4200</td>\n",
       "      <td>...</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2501.250</td>\n",
       "      <td>50400</td>\n",
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       "      <td>🌗</td>\n",
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       "    <tr>\n",
       "      <th>170</th>\n",
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       "      <td>404</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2995</td>\n",
       "      <td>No sunlight data</td>\n",
       "      <td>No sunlight data available and the rent is 2995</td>\n",
       "      <td>...</td>\n",
       "      <td>67950</td>\n",
       "      <td>114427</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1296.250</td>\n",
       "      <td>35940</td>\n",
       "      <td>0.567195</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>171 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds   size  \\\n",
       "0        0  l-2g3vm2ptsq8i   11225           2    rental unit   3.0    NaN   \n",
       "1        1  l-2in0401r3l0j   11215          1B    rental unit   2.0    NaN   \n",
       "2        3  l-dgbncnljpk2t   11217          B2    rental unit   3.0  900.0   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0    NaN   \n",
       "4      200  l-ok0278ecbrpc   11217         312    rental unit   1.0    NaN   \n",
       "..     ...             ...     ...         ...            ...   ...    ...   \n",
       "166    734  l-ue6jib37qqnf   11238           4    rental unit   1.0    NaN   \n",
       "167    757  l-metf0tnqb3oa   11238          6B    rental unit   2.0    NaN   \n",
       "168    781  l-qtrv180v4kc8   11238         504    rental unit   1.0    NaN   \n",
       "169    782  l-v22eed67chvl   11238         501    rental unit   2.0    NaN   \n",
       "170    783  l-rk0ue9fad9jb   11238         404    rental unit   0.0    NaN   \n",
       "\n",
       "     rent   sun_exposure_cat  \\\n",
       "0    3726   No sunlight data   \n",
       "1    4500   No sunlight data   \n",
       "2    4750   No sunlight data   \n",
       "3    3750  Moderate sunlight   \n",
       "4    4000   No sunlight data   \n",
       "..    ...                ...   \n",
       "166  3500   No sunlight data   \n",
       "167  4000   No sunlight data   \n",
       "168  3500   No sunlight data   \n",
       "169  4200   No sunlight data   \n",
       "170  2995   No sunlight data   \n",
       "\n",
       "                                          sun_exposure  ... per capita income  \\\n",
       "0      No sunlight data available and the rent is 3726  ...             41497   \n",
       "1      No sunlight data available and the rent is 4500  ...             87707   \n",
       "2      No sunlight data available and the rent is 4750  ...             85813   \n",
       "3    This apartment has moderate sunlight and the r...  ...             87707   \n",
       "4      No sunlight data available and the rent is 4000  ...             85813   \n",
       "..                                                 ...  ...               ...   \n",
       "166    No sunlight data available and the rent is 3500  ...             67950   \n",
       "167    No sunlight data available and the rent is 4000  ...             67950   \n",
       "168    No sunlight data available and the rent is 3500  ...             67950   \n",
       "169    No sunlight data available and the rent is 4200  ...             67950   \n",
       "170    No sunlight data available and the rent is 2995  ...             67950   \n",
       "\n",
       "     median household income  affordable_rent_single  affordable_rent_couple  \\\n",
       "0                      68542                1037.425                1713.550   \n",
       "1                     156930                2192.675                3923.250   \n",
       "2                     133269                2145.325                3331.725   \n",
       "3                     156930                2192.675                3923.250   \n",
       "4                     133269                2145.325                3331.725   \n",
       "..                       ...                     ...                     ...   \n",
       "166                   114427                1698.750                2860.675   \n",
       "167                   114427                1698.750                2860.675   \n",
       "168                   114427                1698.750                2860.675   \n",
       "169                   114427                1698.750                2860.675   \n",
       "170                   114427                1698.750                2860.675   \n",
       "\n",
       "     is_affordable_individual  is_affordable_couple  rent_difference_single  \\\n",
       "0                       False                 False                2688.575   \n",
       "1                       False                 False                2307.325   \n",
       "2                       False                 False                2604.675   \n",
       "3                       False                  True                1557.325   \n",
       "4                       False                 False                1854.675   \n",
       "..                        ...                   ...                     ...   \n",
       "166                     False                 False                1801.250   \n",
       "167                     False                 False                2301.250   \n",
       "168                     False                 False                1801.250   \n",
       "169                     False                 False                2501.250   \n",
       "170                     False                 False                1296.250   \n",
       "\n",
       "     annualized_rent  indiv_affordability_to_rent_ratio  \\\n",
       "0              44712                           0.278429   \n",
       "1              54000                           0.487261   \n",
       "2              57000                           0.451647   \n",
       "3              45000                           0.584713   \n",
       "4              48000                           0.536331   \n",
       "..               ...                                ...   \n",
       "166            42000                           0.485357   \n",
       "167            48000                           0.424687   \n",
       "168            42000                           0.485357   \n",
       "169            50400                           0.404464   \n",
       "170            35940                           0.567195   \n",
       "\n",
       "     indiv_sun_exposure_icon  \n",
       "0                          🌗  \n",
       "1                          🌗  \n",
       "2                          🌗  \n",
       "3                          🌞  \n",
       "4                          🌞  \n",
       "..                       ...  \n",
       "166                        🌗  \n",
       "167                        🌗  \n",
       "168                        🌗  \n",
       "169                        🌗  \n",
       "170                        🌞  \n",
       "\n",
       "[171 rows x 22 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "0497bc84",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th>indiv_sun_exposure_icon</th>\n",
       "      <th>zipcode</th>\n",
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       "    <tr>\n",
       "      <th>1.0🌞</th>\n",
       "      <th>11215</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.1🌞</th>\n",
       "      <th>11215</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">🌗</th>\n",
       "      <th>11215</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11217</th>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11218</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11225</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11226</th>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11238</th>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>6</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">🌞</th>\n",
       "      <th>11215</th>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>9</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11217</th>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11225</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11238</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 index  listing_path  unit_number  \\\n",
       "indiv_sun_exposure_icon zipcode                                     \n",
       "1.0🌞                    11215        1             1            1   \n",
       "1.1🌞                    11215        3             3            3   \n",
       "🌗                       11215       14            14           14   \n",
       "                        11217       17            17           17   \n",
       "                        11218        2             2            2   \n",
       "                        11225        8             8            8   \n",
       "                        11226       30            30           30   \n",
       "                        11238       28            28           28   \n",
       "🌞                       11215       33            33           33   \n",
       "                        11217       25            25           25   \n",
       "                        11225        2             2            2   \n",
       "                        11238        8             8            8   \n",
       "\n",
       "                                 building_class  beds  size  rent  \\\n",
       "indiv_sun_exposure_icon zipcode                                     \n",
       "1.0🌞                    11215                 1     1     0     1   \n",
       "1.1🌞                    11215                 3     3     3     3   \n",
       "🌗                       11215                14    14     3    14   \n",
       "                        11217                17    17     4    17   \n",
       "                        11218                 2     2     0     2   \n",
       "                        11225                 8     8     4     8   \n",
       "                        11226                30    30     1    30   \n",
       "                        11238                28    28     6    28   \n",
       "🌞                       11215                33    33     9    33   \n",
       "                        11217                25    25     5    25   \n",
       "                        11225                 2     2     0     2   \n",
       "                        11238                 8     8     0     8   \n",
       "\n",
       "                                 sun_exposure_cat  sun_exposure  floor  \\\n",
       "indiv_sun_exposure_icon zipcode                                          \n",
       "1.0🌞                    11215                   1             1      1   \n",
       "1.1🌞                    11215                   3             3      3   \n",
       "🌗                       11215                  14            14     14   \n",
       "                        11217                  17            17     16   \n",
       "                        11218                   2             2      2   \n",
       "                        11225                   8             8      8   \n",
       "                        11226                  30            30     30   \n",
       "                        11238                  28            28     28   \n",
       "🌞                       11215                  33            33     33   \n",
       "                        11217                  25            25     24   \n",
       "                        11225                   2             2      2   \n",
       "                        11238                   8             8      8   \n",
       "\n",
       "                                 median age  per capita income  \\\n",
       "indiv_sun_exposure_icon zipcode                                  \n",
       "1.0🌞                    11215             1                  1   \n",
       "1.1🌞                    11215             3                  3   \n",
       "🌗                       11215            14                 14   \n",
       "                        11217            17                 17   \n",
       "                        11218             2                  2   \n",
       "                        11225             8                  8   \n",
       "                        11226            30                 30   \n",
       "                        11238            28                 28   \n",
       "🌞                       11215            33                 33   \n",
       "                        11217            25                 25   \n",
       "                        11225             2                  2   \n",
       "                        11238             8                  8   \n",
       "\n",
       "                                 median household income  \\\n",
       "indiv_sun_exposure_icon zipcode                            \n",
       "1.0🌞                    11215                          1   \n",
       "1.1🌞                    11215                          3   \n",
       "🌗                       11215                         14   \n",
       "                        11217                         17   \n",
       "                        11218                          2   \n",
       "                        11225                          8   \n",
       "                        11226                         30   \n",
       "                        11238                         28   \n",
       "🌞                       11215                         33   \n",
       "                        11217                         25   \n",
       "                        11225                          2   \n",
       "                        11238                          8   \n",
       "\n",
       "                                 affordable_rent_single  \\\n",
       "indiv_sun_exposure_icon zipcode                           \n",
       "1.0🌞                    11215                         1   \n",
       "1.1🌞                    11215                         3   \n",
       "🌗                       11215                        14   \n",
       "                        11217                        17   \n",
       "                        11218                         2   \n",
       "                        11225                         8   \n",
       "                        11226                        30   \n",
       "                        11238                        28   \n",
       "🌞                       11215                        33   \n",
       "                        11217                        25   \n",
       "                        11225                         2   \n",
       "                        11238                         8   \n",
       "\n",
       "                                 affordable_rent_couple  \\\n",
       "indiv_sun_exposure_icon zipcode                           \n",
       "1.0🌞                    11215                         1   \n",
       "1.1🌞                    11215                         3   \n",
       "🌗                       11215                        14   \n",
       "                        11217                        17   \n",
       "                        11218                         2   \n",
       "                        11225                         8   \n",
       "                        11226                        30   \n",
       "                        11238                        28   \n",
       "🌞                       11215                        33   \n",
       "                        11217                        25   \n",
       "                        11225                         2   \n",
       "                        11238                         8   \n",
       "\n",
       "                                 is_affordable_individual  \\\n",
       "indiv_sun_exposure_icon zipcode                             \n",
       "1.0🌞                    11215                           1   \n",
       "1.1🌞                    11215                           3   \n",
       "🌗                       11215                          14   \n",
       "                        11217                          17   \n",
       "                        11218                           2   \n",
       "                        11225                           8   \n",
       "                        11226                          30   \n",
       "                        11238                          28   \n",
       "🌞                       11215                          33   \n",
       "                        11217                          25   \n",
       "                        11225                           2   \n",
       "                        11238                           8   \n",
       "\n",
       "                                 is_affordable_couple  rent_difference_single  \\\n",
       "indiv_sun_exposure_icon zipcode                                                 \n",
       "1.0🌞                    11215                       1                       1   \n",
       "1.1🌞                    11215                       3                       3   \n",
       "🌗                       11215                      14                      14   \n",
       "                        11217                      17                      17   \n",
       "                        11218                       2                       2   \n",
       "                        11225                       8                       8   \n",
       "                        11226                      30                      30   \n",
       "                        11238                      28                      28   \n",
       "🌞                       11215                      33                      33   \n",
       "                        11217                      25                      25   \n",
       "                        11225                       2                       2   \n",
       "                        11238                       8                       8   \n",
       "\n",
       "                                 annualized_rent  \\\n",
       "indiv_sun_exposure_icon zipcode                    \n",
       "1.0🌞                    11215                  1   \n",
       "1.1🌞                    11215                  3   \n",
       "🌗                       11215                 14   \n",
       "                        11217                 17   \n",
       "                        11218                  2   \n",
       "                        11225                  8   \n",
       "                        11226                 30   \n",
       "                        11238                 28   \n",
       "🌞                       11215                 33   \n",
       "                        11217                 25   \n",
       "                        11225                  2   \n",
       "                        11238                  8   \n",
       "\n",
       "                                 indiv_affordability_to_rent_ratio  \n",
       "indiv_sun_exposure_icon zipcode                                     \n",
       "1.0🌞                    11215                                    1  \n",
       "1.1🌞                    11215                                    3  \n",
       "🌗                       11215                                   14  \n",
       "                        11217                                   17  \n",
       "                        11218                                    2  \n",
       "                        11225                                    8  \n",
       "                        11226                                   30  \n",
       "                        11238                                   28  \n",
       "🌞                       11215                                   33  \n",
       "                        11217                                   25  \n",
       "                        11225                                    2  \n",
       "                        11238                                    8  "
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged.groupby(['indiv_sun_exposure_icon','zipcode']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "9e6b0d9c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "indiv_sun_exposure_icon  zipcode\n",
       "🌗                        11215      4\n",
       "                         11217      3\n",
       "                         11225      1\n",
       "                         11238      8\n",
       "🌞                        11215      9\n",
       "                         11217      4\n",
       "                         11225      2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_merged[df_merged['sun_exposure_cat']!= 'No sunlight data']\n",
    "     .groupby(['indiv_sun_exposure_icon','zipcode'])\n",
    "     .size()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "a3e0e5b8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/km/gmzkf_4n5qn6c84ksf3bzy0c0000gn/T/ipykernel_84608/3218241592.py:11: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  df_grouped = df_merged.groupby('zipcode').mean()\n"
     ]
    }
   ],
   "source": [
    "def map_ratio_to_icon(ratio):\n",
    "    if ratio < 0:\n",
    "        return '☔'  # Using umbrella icon to denote negative rent difference\n",
    "    elif ratio <= 0.5:\n",
    "        return '🌗'  # Half sun (replace with your own icon)\n",
    "    elif ratio <= 1:\n",
    "        return '🌞'  # Full sun (replace with your own icon)\n",
    "    else:\n",
    "        return f'{ratio:.1f}🌞'  # More than 1 full sun\n",
    "\n",
    "df_grouped = df_merged.groupby('zipcode').mean()\n",
    "df_grouped['indiv_sun_exposure_icon'] = df_grouped['indiv_affordability_to_rent_ratio'].apply(map_ratio_to_icon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "901be464",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>median age</th>\n",
       "      <th>per capita income</th>\n",
       "      <th>median household income</th>\n",
       "      <th>affordable_rent_single</th>\n",
       "      <th>affordable_rent_couple</th>\n",
       "      <th>is_affordable_individual</th>\n",
       "      <th>is_affordable_couple</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "      <th>indiv_sun_exposure_icon</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zipcode</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11215</th>\n",
       "      <td>329.529412</td>\n",
       "      <td>1.431373</td>\n",
       "      <td>667.600000</td>\n",
       "      <td>3790.000000</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
       "      <td>156930.0</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>0.078431</td>\n",
       "      <td>0.627451</td>\n",
       "      <td>1597.325000</td>\n",
       "      <td>45480.000000</td>\n",
       "      <td>0.659563</td>\n",
       "      <td>-133.250000</td>\n",
       "      <td>1.180126</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11217</th>\n",
       "      <td>401.047619</td>\n",
       "      <td>1.023810</td>\n",
       "      <td>963.888889</td>\n",
       "      <td>4167.023810</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813.0</td>\n",
       "      <td>133269.0</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.261905</td>\n",
       "      <td>2021.698810</td>\n",
       "      <td>50004.285714</td>\n",
       "      <td>0.547054</td>\n",
       "      <td>835.298810</td>\n",
       "      <td>0.849584</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11218</th>\n",
       "      <td>324.500000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3050.000000</td>\n",
       "      <td>36.4</td>\n",
       "      <td>43113.0</td>\n",
       "      <td>81857.0</td>\n",
       "      <td>1077.825</td>\n",
       "      <td>2046.425</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1972.175000</td>\n",
       "      <td>36600.000000</td>\n",
       "      <td>0.354911</td>\n",
       "      <td>1003.575000</td>\n",
       "      <td>0.673857</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11225</th>\n",
       "      <td>248.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1173.750000</td>\n",
       "      <td>3277.100000</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497.0</td>\n",
       "      <td>68542.0</td>\n",
       "      <td>1037.425</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2239.675000</td>\n",
       "      <td>39325.200000</td>\n",
       "      <td>0.358370</td>\n",
       "      <td>1563.550000</td>\n",
       "      <td>0.591932</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11226</th>\n",
       "      <td>255.433333</td>\n",
       "      <td>1.266667</td>\n",
       "      <td>1077.000000</td>\n",
       "      <td>3073.200000</td>\n",
       "      <td>35.4</td>\n",
       "      <td>34323.0</td>\n",
       "      <td>66173.0</td>\n",
       "      <td>858.075</td>\n",
       "      <td>1654.325</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2215.125000</td>\n",
       "      <td>36878.400000</td>\n",
       "      <td>0.284774</td>\n",
       "      <td>1418.875000</td>\n",
       "      <td>0.549031</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11238</th>\n",
       "      <td>481.138889</td>\n",
       "      <td>1.472222</td>\n",
       "      <td>950.000000</td>\n",
       "      <td>4231.305556</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950.0</td>\n",
       "      <td>114427.0</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>2532.555556</td>\n",
       "      <td>50775.666667</td>\n",
       "      <td>0.421898</td>\n",
       "      <td>1370.630556</td>\n",
       "      <td>0.710471</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              index      beds         size         rent  median age  \\\n",
       "zipcode                                                               \n",
       "11215    329.529412  1.431373   667.600000  3790.000000        37.0   \n",
       "11217    401.047619  1.023810   963.888889  4167.023810        35.5   \n",
       "11218    324.500000  1.500000          NaN  3050.000000        36.4   \n",
       "11225    248.000000  1.500000  1173.750000  3277.100000        36.1   \n",
       "11226    255.433333  1.266667  1077.000000  3073.200000        35.4   \n",
       "11238    481.138889  1.472222   950.000000  4231.305556        35.3   \n",
       "\n",
       "         per capita income  median household income  affordable_rent_single  \\\n",
       "zipcode                                                                       \n",
       "11215              87707.0                 156930.0                2192.675   \n",
       "11217              85813.0                 133269.0                2145.325   \n",
       "11218              43113.0                  81857.0                1077.825   \n",
       "11225              41497.0                  68542.0                1037.425   \n",
       "11226              34323.0                  66173.0                 858.075   \n",
       "11238              67950.0                 114427.0                1698.750   \n",
       "\n",
       "         affordable_rent_couple  is_affordable_individual  \\\n",
       "zipcode                                                     \n",
       "11215                  3923.250                  0.078431   \n",
       "11217                  3331.725                  0.000000   \n",
       "11218                  2046.425                  0.000000   \n",
       "11225                  1713.550                  0.000000   \n",
       "11226                  1654.325                  0.000000   \n",
       "11238                  2860.675                  0.000000   \n",
       "\n",
       "         is_affordable_couple  rent_difference_single  annualized_rent  \\\n",
       "zipcode                                                                  \n",
       "11215                0.627451             1597.325000     45480.000000   \n",
       "11217                0.261905             2021.698810     50004.285714   \n",
       "11218                0.000000             1972.175000     36600.000000   \n",
       "11225                0.000000             2239.675000     39325.200000   \n",
       "11226                0.000000             2215.125000     36878.400000   \n",
       "11238                0.055556             2532.555556     50775.666667   \n",
       "\n",
       "         indiv_affordability_to_rent_ratio  rent_difference_couple  \\\n",
       "zipcode                                                              \n",
       "11215                             0.659563             -133.250000   \n",
       "11217                             0.547054              835.298810   \n",
       "11218                             0.354911             1003.575000   \n",
       "11225                             0.358370             1563.550000   \n",
       "11226                             0.284774             1418.875000   \n",
       "11238                             0.421898             1370.630556   \n",
       "\n",
       "         coup_affordability_to_rent_ratio indiv_sun_exposure_icon  \n",
       "zipcode                                                            \n",
       "11215                            1.180126                       🌞  \n",
       "11217                            0.849584                       🌞  \n",
       "11218                            0.673857                       🌗  \n",
       "11225                            0.591932                       🌗  \n",
       "11226                            0.549031                       🌗  \n",
       "11238                            0.710471                       🌗  "
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_grouped"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e873c50f",
   "metadata": {},
   "source": [
    "## Affordability for Couples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "c2aa76a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    156930.0\n",
       "11217    133269.0\n",
       "11225     68542.0\n",
       "11238    114427.0\n",
       "Name: median household income, dtype: float64"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(filtered_sun_exposure\n",
    "     .groupby(['zipcode'])['median household income']\n",
    "     .median()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "2ea24cf9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    0.627451\n",
       "11217    0.261905\n",
       "11218    0.000000\n",
       "11225    0.000000\n",
       "11226    0.000000\n",
       "11238    0.055556\n",
       "Name: is_affordable_couple, dtype: float64"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coup_affordability_by_zipcode = df_merged.groupby('zipcode')['is_affordable_couple'].mean()\n",
    "coup_affordability_by_zipcode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "85d7b8c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged['rent_difference_couple'] = df_merged['rent'] - df_merged['affordable_rent_couple']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "c61622fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "coup_average_rent_difference_by_zipcode = df_merged.groupby('zipcode')['rent_difference_couple'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "e5b57e97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    -133.250000\n",
       "11217     835.298810\n",
       "11218    1003.575000\n",
       "11225    1563.550000\n",
       "11226    1418.875000\n",
       "11238    1370.630556\n",
       "Name: rent_difference_couple, dtype: float64"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coup_average_rent_difference_by_zipcode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "50c7e984",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode\n",
       "11215    -133.0\n",
       "11217     835.0\n",
       "11218    1004.0\n",
       "11225    1564.0\n",
       "11226    1419.0\n",
       "11238    1371.0\n",
       "Name: rent_difference_couple, dtype: float64"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coup_average_rent_difference_by_zipcode.round()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "11314102",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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       "      \"vega\": \"https://cdn.jsdelivr.net/npm/vega@5?noext\",\n",
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       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
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       "  })({\"config\": {\"view\": {\"continuousWidth\": 300, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-c3291ca3c4bb4b65f6f2e7c37b22a88f\"}, \"mark\": {\"type\": \"bar\"}, \"encoding\": {\"color\": {\"field\": \"variable\", \"type\": \"nominal\"}, \"column\": {\"field\": \"zipcode\", \"type\": \"nominal\"}, \"x\": {\"field\": \"variable\", \"type\": \"nominal\"}, \"y\": {\"field\": \"value\", \"type\": \"quantitative\"}}, \"height\": 200, \"width\": 200, \"$schema\": \"https://vega.github.io/schema/vega-lite/v5.8.0.json\", \"datasets\": {\"data-c3291ca3c4bb4b65f6f2e7c37b22a88f\": [{\"zipcode\": \"11215\", \"variable\": \"rent\", \"value\": 3790.0}, {\"zipcode\": \"11217\", \"variable\": \"rent\", \"value\": 4167.023809523809}, {\"zipcode\": \"11218\", \"variable\": \"rent\", \"value\": 3050.0}, {\"zipcode\": \"11225\", \"variable\": \"rent\", \"value\": 3277.1}, {\"zipcode\": \"11226\", \"variable\": \"rent\", \"value\": 3073.2}, {\"zipcode\": \"11238\", \"variable\": \"rent\", \"value\": 4231.305555555556}, {\"zipcode\": \"11215\", \"variable\": \"affordable_rent_couple\", \"value\": 3923.25}, {\"zipcode\": \"11217\", \"variable\": \"affordable_rent_couple\", \"value\": 3331.7249999999995}, {\"zipcode\": \"11218\", \"variable\": \"affordable_rent_couple\", \"value\": 2046.425}, {\"zipcode\": \"11225\", \"variable\": \"affordable_rent_couple\", \"value\": 1713.55}, {\"zipcode\": \"11226\", \"variable\": \"affordable_rent_couple\", \"value\": 1654.325}, {\"zipcode\": \"11238\", \"variable\": \"affordable_rent_couple\", \"value\": 2860.675}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate average rent and rent_difference for each zipcode\n",
    "df_avg_couple = df_merged.groupby('zipcode')[['rent', 'affordable_rent_couple']].mean().reset_index()\n",
    "\n",
    "# Melt the DataFrame to long format\n",
    "df_melted_couple = df_avg_couple.melt(id_vars='zipcode', value_vars=['rent', 'affordable_rent_couple'])\n",
    "\n",
    "# Create small multiple bar charts\n",
    "chart = alt.Chart(df_melted_couple).mark_bar().encode(\n",
    "    x='variable:N',  # variable column contains 'rent' and 'rent_difference'\n",
    "    y='value:Q',  # value column contains the corresponding values\n",
    "    color='variable:N',\n",
    "    column='zipcode:N'\n",
    ").properties(\n",
    "    width=200,\n",
    "    height=200\n",
    ")\n",
    "\n",
    "chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "0637cf58",
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"5.8.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 300, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-a45282c6bf2a0427149bac015eb41dbb\"}, \"mark\": {\"type\": \"bar\"}, \"encoding\": {\"color\": {\"field\": \"variable\", \"type\": \"nominal\"}, \"column\": {\"field\": \"zipcode\", \"type\": \"nominal\"}, \"x\": {\"field\": \"variable\", \"type\": \"nominal\"}, \"y\": {\"field\": \"value\", \"type\": \"quantitative\"}}, \"height\": 200, \"width\": 200, \"$schema\": \"https://vega.github.io/schema/vega-lite/v5.8.0.json\", \"datasets\": {\"data-a45282c6bf2a0427149bac015eb41dbb\": [{\"zipcode\": \"11215\", \"variable\": \"rent\", \"value\": 3790.0}, {\"zipcode\": \"11217\", \"variable\": \"rent\", \"value\": 4167.023809523809}, {\"zipcode\": \"11218\", \"variable\": \"rent\", \"value\": 3050.0}, {\"zipcode\": \"11225\", \"variable\": \"rent\", \"value\": 3277.1}, {\"zipcode\": \"11226\", \"variable\": \"rent\", \"value\": 3073.2}, {\"zipcode\": \"11238\", \"variable\": \"rent\", \"value\": 4231.305555555556}, {\"zipcode\": \"11215\", \"variable\": \"affordable_rent_couple\", \"value\": 3923.25}, {\"zipcode\": \"11217\", \"variable\": \"affordable_rent_couple\", \"value\": 3331.7249999999995}, {\"zipcode\": \"11218\", \"variable\": \"affordable_rent_couple\", \"value\": 2046.425}, {\"zipcode\": \"11225\", \"variable\": \"affordable_rent_couple\", \"value\": 1713.55}, {\"zipcode\": \"11226\", \"variable\": \"affordable_rent_couple\", \"value\": 1654.325}, {\"zipcode\": \"11238\", \"variable\": \"affordable_rent_couple\", \"value\": 2860.675}, {\"zipcode\": \"11215\", \"variable\": \"rent_difference_couple\", \"value\": -133.25}, {\"zipcode\": \"11217\", \"variable\": \"rent_difference_couple\", \"value\": 835.2988095238096}, {\"zipcode\": \"11218\", \"variable\": \"rent_difference_couple\", \"value\": 1003.575}, {\"zipcode\": \"11225\", \"variable\": \"rent_difference_couple\", \"value\": 1563.55}, {\"zipcode\": \"11226\", \"variable\": \"rent_difference_couple\", \"value\": 1418.875}, {\"zipcode\": \"11238\", \"variable\": \"rent_difference_couple\", \"value\": 1370.6305555555555}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate average rent, affordable rent and rent_difference for each zipcode\n",
    "df_avg_couple = df_merged.groupby('zipcode')[['rent', 'affordable_rent_couple', 'rent_difference_couple']].mean().reset_index()\n",
    "\n",
    "# Melt the DataFrame to long format\n",
    "df_melted_couple = df_avg_couple.melt(id_vars='zipcode', value_vars=['rent', 'affordable_rent_couple', 'rent_difference_couple'])\n",
    "\n",
    "# Create small multiple grouped bar charts\n",
    "chart = alt.Chart(df_melted_couple).mark_bar().encode(\n",
    "    x='variable:N',  # variable column contains 'rent', 'affordable_rent' and 'rent_difference'\n",
    "    y='value:Q',  # value column contains the corresponding values\n",
    "    color='variable:N',\n",
    "    column='zipcode:N'\n",
    ").properties(\n",
    "    width=200,\n",
    "    height=200\n",
    ")\n",
    "\n",
    "chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "2b705db1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged['coup_affordability_to_rent_ratio'] = df_merged['affordable_rent_couple']/(df_merged['rent']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "0b4675b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def map_ratio_to_icon(ratio):\n",
    "    if ratio < 0:\n",
    "        return '☔'  # Using umbrella icon to denote negative rent difference\n",
    "    elif ratio <= 0.5:\n",
    "        return '🌗'  # Half sun (replace with your own icon)\n",
    "    elif ratio <= 1:\n",
    "        return '🌞'  # Full sun (replace with your own icon)\n",
    "    else:\n",
    "        return f'{ratio:.1f}🌞'  # More than 1 full sun\n",
    "\n",
    "df_merged['coup_sun_exposure_icon'] = df_merged['coup_affordability_to_rent_ratio'].apply(map_ratio_to_icon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "871557b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>floor</th>\n",
       "      <th>...</th>\n",
       "      <th>affordable_rent_single</th>\n",
       "      <th>affordable_rent_couple</th>\n",
       "      <th>is_affordable_individual</th>\n",
       "      <th>is_affordable_couple</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "      <th>indiv_sun_exposure_icon</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zipcode</th>\n",
       "      <th>coup_sun_exposure_icon</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"11\" valign=\"top\">11215</th>\n",
       "      <th>1.0🌞</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.1🌞</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.2🌞</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.3🌞</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.4🌞</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.5🌞</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.6🌞</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.8🌞</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.9🌞</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>🌗</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>🌞</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">11217</th>\n",
       "      <th>1.0🌞</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.1🌞</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.2🌞</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>🌗</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>🌞</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>27</td>\n",
       "      <td>...</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11218</th>\n",
       "      <th>🌞</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">11225</th>\n",
       "      <th>🌗</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>🌞</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">11226</th>\n",
       "      <th>🌗</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>🌞</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">11238</th>\n",
       "      <th>1.0🌞</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>🌗</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>🌞</th>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>6</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>...</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                index  listing_path  unit_number  \\\n",
       "zipcode coup_sun_exposure_icon                                     \n",
       "11215   1.0🌞                        1             1            1   \n",
       "        1.1🌞                        3             3            3   \n",
       "        1.2🌞                        8             8            8   \n",
       "        1.3🌞                        4             4            4   \n",
       "        1.4🌞                        1             1            1   \n",
       "        1.5🌞                        6             6            6   \n",
       "        1.6🌞                        5             5            5   \n",
       "        1.8🌞                        1             1            1   \n",
       "        1.9🌞                        3             3            3   \n",
       "        🌗                           3             3            3   \n",
       "        🌞                          16            16           16   \n",
       "11217   1.0🌞                        4             4            4   \n",
       "        1.1🌞                        3             3            3   \n",
       "        1.2🌞                        4             4            4   \n",
       "        🌗                           2             2            2   \n",
       "        🌞                          29            29           29   \n",
       "11218   🌞                           2             2            2   \n",
       "11225   🌗                           4             4            4   \n",
       "        🌞                           6             6            6   \n",
       "11226   🌗                           7             7            7   \n",
       "        🌞                          23            23           23   \n",
       "11238   1.0🌞                        2             2            2   \n",
       "        🌗                           4             4            4   \n",
       "        🌞                          30            30           30   \n",
       "\n",
       "                                building_class  beds  size  rent  \\\n",
       "zipcode coup_sun_exposure_icon                                     \n",
       "11215   1.0🌞                                 1     1     0     1   \n",
       "        1.1🌞                                 3     3     0     3   \n",
       "        1.2🌞                                 8     8     2     8   \n",
       "        1.3🌞                                 4     4     0     4   \n",
       "        1.4🌞                                 1     1     1     1   \n",
       "        1.5🌞                                 6     6     2     6   \n",
       "        1.6🌞                                 5     5     2     5   \n",
       "        1.8🌞                                 1     1     0     1   \n",
       "        1.9🌞                                 3     3     3     3   \n",
       "        🌗                                    3     3     1     3   \n",
       "        🌞                                   16    16     4    16   \n",
       "11217   1.0🌞                                 4     4     0     4   \n",
       "        1.1🌞                                 3     3     0     3   \n",
       "        1.2🌞                                 4     4     3     4   \n",
       "        🌗                                    2     2     1     2   \n",
       "        🌞                                   29    29     5    29   \n",
       "11218   🌞                                    2     2     0     2   \n",
       "11225   🌗                                    4     4     3     4   \n",
       "        🌞                                    6     6     1     6   \n",
       "11226   🌗                                    7     7     1     7   \n",
       "        🌞                                   23    23     0    23   \n",
       "11238   1.0🌞                                 2     2     0     2   \n",
       "        🌗                                    4     4     0     4   \n",
       "        🌞                                   30    30     6    30   \n",
       "\n",
       "                                sun_exposure_cat  sun_exposure  floor  ...  \\\n",
       "zipcode coup_sun_exposure_icon                                         ...   \n",
       "11215   1.0🌞                                   1             1      1  ...   \n",
       "        1.1🌞                                   3             3      3  ...   \n",
       "        1.2🌞                                   8             8      8  ...   \n",
       "        1.3🌞                                   4             4      4  ...   \n",
       "        1.4🌞                                   1             1      1  ...   \n",
       "        1.5🌞                                   6             6      6  ...   \n",
       "        1.6🌞                                   5             5      5  ...   \n",
       "        1.8🌞                                   1             1      1  ...   \n",
       "        1.9🌞                                   3             3      3  ...   \n",
       "        🌗                                      3             3      3  ...   \n",
       "        🌞                                     16            16     16  ...   \n",
       "11217   1.0🌞                                   4             4      4  ...   \n",
       "        1.1🌞                                   3             3      3  ...   \n",
       "        1.2🌞                                   4             4      4  ...   \n",
       "        🌗                                      2             2      2  ...   \n",
       "        🌞                                     29            29     27  ...   \n",
       "11218   🌞                                      2             2      2  ...   \n",
       "11225   🌗                                      4             4      4  ...   \n",
       "        🌞                                      6             6      6  ...   \n",
       "11226   🌗                                      7             7      7  ...   \n",
       "        🌞                                     23            23     23  ...   \n",
       "11238   1.0🌞                                   2             2      2  ...   \n",
       "        🌗                                      4             4      4  ...   \n",
       "        🌞                                     30            30     30  ...   \n",
       "\n",
       "                                affordable_rent_single  \\\n",
       "zipcode coup_sun_exposure_icon                           \n",
       "11215   1.0🌞                                         1   \n",
       "        1.1🌞                                         3   \n",
       "        1.2🌞                                         8   \n",
       "        1.3🌞                                         4   \n",
       "        1.4🌞                                         1   \n",
       "        1.5🌞                                         6   \n",
       "        1.6🌞                                         5   \n",
       "        1.8🌞                                         1   \n",
       "        1.9🌞                                         3   \n",
       "        🌗                                            3   \n",
       "        🌞                                           16   \n",
       "11217   1.0🌞                                         4   \n",
       "        1.1🌞                                         3   \n",
       "        1.2🌞                                         4   \n",
       "        🌗                                            2   \n",
       "        🌞                                           29   \n",
       "11218   🌞                                            2   \n",
       "11225   🌗                                            4   \n",
       "        🌞                                            6   \n",
       "11226   🌗                                            7   \n",
       "        🌞                                           23   \n",
       "11238   1.0🌞                                         2   \n",
       "        🌗                                            4   \n",
       "        🌞                                           30   \n",
       "\n",
       "                                affordable_rent_couple  \\\n",
       "zipcode coup_sun_exposure_icon                           \n",
       "11215   1.0🌞                                         1   \n",
       "        1.1🌞                                         3   \n",
       "        1.2🌞                                         8   \n",
       "        1.3🌞                                         4   \n",
       "        1.4🌞                                         1   \n",
       "        1.5🌞                                         6   \n",
       "        1.6🌞                                         5   \n",
       "        1.8🌞                                         1   \n",
       "        1.9🌞                                         3   \n",
       "        🌗                                            3   \n",
       "        🌞                                           16   \n",
       "11217   1.0🌞                                         4   \n",
       "        1.1🌞                                         3   \n",
       "        1.2🌞                                         4   \n",
       "        🌗                                            2   \n",
       "        🌞                                           29   \n",
       "11218   🌞                                            2   \n",
       "11225   🌗                                            4   \n",
       "        🌞                                            6   \n",
       "11226   🌗                                            7   \n",
       "        🌞                                           23   \n",
       "11238   1.0🌞                                         2   \n",
       "        🌗                                            4   \n",
       "        🌞                                           30   \n",
       "\n",
       "                                is_affordable_individual  \\\n",
       "zipcode coup_sun_exposure_icon                             \n",
       "11215   1.0🌞                                           1   \n",
       "        1.1🌞                                           3   \n",
       "        1.2🌞                                           8   \n",
       "        1.3🌞                                           4   \n",
       "        1.4🌞                                           1   \n",
       "        1.5🌞                                           6   \n",
       "        1.6🌞                                           5   \n",
       "        1.8🌞                                           1   \n",
       "        1.9🌞                                           3   \n",
       "        🌗                                              3   \n",
       "        🌞                                             16   \n",
       "11217   1.0🌞                                           4   \n",
       "        1.1🌞                                           3   \n",
       "        1.2🌞                                           4   \n",
       "        🌗                                              2   \n",
       "        🌞                                             29   \n",
       "11218   🌞                                              2   \n",
       "11225   🌗                                              4   \n",
       "        🌞                                              6   \n",
       "11226   🌗                                              7   \n",
       "        🌞                                             23   \n",
       "11238   1.0🌞                                           2   \n",
       "        🌗                                              4   \n",
       "        🌞                                             30   \n",
       "\n",
       "                                is_affordable_couple  rent_difference_single  \\\n",
       "zipcode coup_sun_exposure_icon                                                 \n",
       "11215   1.0🌞                                       1                       1   \n",
       "        1.1🌞                                       3                       3   \n",
       "        1.2🌞                                       8                       8   \n",
       "        1.3🌞                                       4                       4   \n",
       "        1.4🌞                                       1                       1   \n",
       "        1.5🌞                                       6                       6   \n",
       "        1.6🌞                                       5                       5   \n",
       "        1.8🌞                                       1                       1   \n",
       "        1.9🌞                                       3                       3   \n",
       "        🌗                                          3                       3   \n",
       "        🌞                                         16                      16   \n",
       "11217   1.0🌞                                       4                       4   \n",
       "        1.1🌞                                       3                       3   \n",
       "        1.2🌞                                       4                       4   \n",
       "        🌗                                          2                       2   \n",
       "        🌞                                         29                      29   \n",
       "11218   🌞                                          2                       2   \n",
       "11225   🌗                                          4                       4   \n",
       "        🌞                                          6                       6   \n",
       "11226   🌗                                          7                       7   \n",
       "        🌞                                         23                      23   \n",
       "11238   1.0🌞                                       2                       2   \n",
       "        🌗                                          4                       4   \n",
       "        🌞                                         30                      30   \n",
       "\n",
       "                                annualized_rent  \\\n",
       "zipcode coup_sun_exposure_icon                    \n",
       "11215   1.0🌞                                  1   \n",
       "        1.1🌞                                  3   \n",
       "        1.2🌞                                  8   \n",
       "        1.3🌞                                  4   \n",
       "        1.4🌞                                  1   \n",
       "        1.5🌞                                  6   \n",
       "        1.6🌞                                  5   \n",
       "        1.8🌞                                  1   \n",
       "        1.9🌞                                  3   \n",
       "        🌗                                     3   \n",
       "        🌞                                    16   \n",
       "11217   1.0🌞                                  4   \n",
       "        1.1🌞                                  3   \n",
       "        1.2🌞                                  4   \n",
       "        🌗                                     2   \n",
       "        🌞                                    29   \n",
       "11218   🌞                                     2   \n",
       "11225   🌗                                     4   \n",
       "        🌞                                     6   \n",
       "11226   🌗                                     7   \n",
       "        🌞                                    23   \n",
       "11238   1.0🌞                                  2   \n",
       "        🌗                                     4   \n",
       "        🌞                                    30   \n",
       "\n",
       "                                indiv_affordability_to_rent_ratio  \\\n",
       "zipcode coup_sun_exposure_icon                                      \n",
       "11215   1.0🌞                                                    1   \n",
       "        1.1🌞                                                    3   \n",
       "        1.2🌞                                                    8   \n",
       "        1.3🌞                                                    4   \n",
       "        1.4🌞                                                    1   \n",
       "        1.5🌞                                                    6   \n",
       "        1.6🌞                                                    5   \n",
       "        1.8🌞                                                    1   \n",
       "        1.9🌞                                                    3   \n",
       "        🌗                                                       3   \n",
       "        🌞                                                      16   \n",
       "11217   1.0🌞                                                    4   \n",
       "        1.1🌞                                                    3   \n",
       "        1.2🌞                                                    4   \n",
       "        🌗                                                       2   \n",
       "        🌞                                                      29   \n",
       "11218   🌞                                                       2   \n",
       "11225   🌗                                                       4   \n",
       "        🌞                                                       6   \n",
       "11226   🌗                                                       7   \n",
       "        🌞                                                      23   \n",
       "11238   1.0🌞                                                    2   \n",
       "        🌗                                                       4   \n",
       "        🌞                                                      30   \n",
       "\n",
       "                                indiv_sun_exposure_icon  \\\n",
       "zipcode coup_sun_exposure_icon                            \n",
       "11215   1.0🌞                                          1   \n",
       "        1.1🌞                                          3   \n",
       "        1.2🌞                                          8   \n",
       "        1.3🌞                                          4   \n",
       "        1.4🌞                                          1   \n",
       "        1.5🌞                                          6   \n",
       "        1.6🌞                                          5   \n",
       "        1.8🌞                                          1   \n",
       "        1.9🌞                                          3   \n",
       "        🌗                                             3   \n",
       "        🌞                                            16   \n",
       "11217   1.0🌞                                          4   \n",
       "        1.1🌞                                          3   \n",
       "        1.2🌞                                          4   \n",
       "        🌗                                             2   \n",
       "        🌞                                            29   \n",
       "11218   🌞                                             2   \n",
       "11225   🌗                                             4   \n",
       "        🌞                                             6   \n",
       "11226   🌗                                             7   \n",
       "        🌞                                            23   \n",
       "11238   1.0🌞                                          2   \n",
       "        🌗                                             4   \n",
       "        🌞                                            30   \n",
       "\n",
       "                                rent_difference_couple  \\\n",
       "zipcode coup_sun_exposure_icon                           \n",
       "11215   1.0🌞                                         1   \n",
       "        1.1🌞                                         3   \n",
       "        1.2🌞                                         8   \n",
       "        1.3🌞                                         4   \n",
       "        1.4🌞                                         1   \n",
       "        1.5🌞                                         6   \n",
       "        1.6🌞                                         5   \n",
       "        1.8🌞                                         1   \n",
       "        1.9🌞                                         3   \n",
       "        🌗                                            3   \n",
       "        🌞                                           16   \n",
       "11217   1.0🌞                                         4   \n",
       "        1.1🌞                                         3   \n",
       "        1.2🌞                                         4   \n",
       "        🌗                                            2   \n",
       "        🌞                                           29   \n",
       "11218   🌞                                            2   \n",
       "11225   🌗                                            4   \n",
       "        🌞                                            6   \n",
       "11226   🌗                                            7   \n",
       "        🌞                                           23   \n",
       "11238   1.0🌞                                         2   \n",
       "        🌗                                            4   \n",
       "        🌞                                           30   \n",
       "\n",
       "                                coup_affordability_to_rent_ratio  \n",
       "zipcode coup_sun_exposure_icon                                    \n",
       "11215   1.0🌞                                                   1  \n",
       "        1.1🌞                                                   3  \n",
       "        1.2🌞                                                   8  \n",
       "        1.3🌞                                                   4  \n",
       "        1.4🌞                                                   1  \n",
       "        1.5🌞                                                   6  \n",
       "        1.6🌞                                                   5  \n",
       "        1.8🌞                                                   1  \n",
       "        1.9🌞                                                   3  \n",
       "        🌗                                                      3  \n",
       "        🌞                                                     16  \n",
       "11217   1.0🌞                                                   4  \n",
       "        1.1🌞                                                   3  \n",
       "        1.2🌞                                                   4  \n",
       "        🌗                                                      2  \n",
       "        🌞                                                     29  \n",
       "11218   🌞                                                      2  \n",
       "11225   🌗                                                      4  \n",
       "        🌞                                                      6  \n",
       "11226   🌗                                                      7  \n",
       "        🌞                                                     23  \n",
       "11238   1.0🌞                                                   2  \n",
       "        🌗                                                      4  \n",
       "        🌞                                                     30  \n",
       "\n",
       "[24 rows x 23 columns]"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged.groupby(['zipcode','coup_sun_exposure_icon']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "4c646524",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_merged.to_csv('merged_sun_exposure.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "c3df90da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode  coup_sun_exposure_icon\n",
       "11215    1.0🌞                      1\n",
       "         1.1🌞                      1\n",
       "         1.3🌞                      3\n",
       "         1.5🌞                      2\n",
       "         🌞                         6\n",
       "11217    1.2🌞                      4\n",
       "         🌗                         2\n",
       "         🌞                         1\n",
       "11225    🌗                         1\n",
       "         🌞                         2\n",
       "11238    🌗                         1\n",
       "         🌞                         7\n",
       "dtype: int64"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_merged[df_merged['sun_exposure_cat']!= 'No sunlight data']\n",
    "     .groupby(['zipcode','coup_sun_exposure_icon'])\n",
    "     .size()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "baa33e48",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged_filtered =df_merged[df_merged['sun_exposure_cat']!='No sunlight data']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "c5289e8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged_filtered.to_csv('filtered_merged_sun_exposure.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "5b6434ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>...</th>\n",
       "      <th>affordable_rent_couple</th>\n",
       "      <th>is_affordable_individual</th>\n",
       "      <th>is_affordable_couple</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "      <th>indiv_sun_exposure_icon</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "      <th>coup_sun_exposure_icon</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>213</td>\n",
       "      <td>l-4vkr066dfpsq</td>\n",
       "      <td>11217</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>654.675</td>\n",
       "      <td>33600</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-531.725</td>\n",
       "      <td>1.189902</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>216</td>\n",
       "      <td>l-jlm1f9thn9hb</td>\n",
       "      <td>11225</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>4795</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3757.575</td>\n",
       "      <td>57540</td>\n",
       "      <td>0.216356</td>\n",
       "      <td>🌗</td>\n",
       "      <td>3081.450</td>\n",
       "      <td>0.357362</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>227</td>\n",
       "      <td>l-mmegr1flhf1d</td>\n",
       "      <td>11225</td>\n",
       "      <td>2F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>857.575</td>\n",
       "      <td>22740</td>\n",
       "      <td>0.547454</td>\n",
       "      <td>🌞</td>\n",
       "      <td>181.450</td>\n",
       "      <td>0.904248</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>241</td>\n",
       "      <td>l-155vl5l7p3mt</td>\n",
       "      <td>11215</td>\n",
       "      <td>3R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.5</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1807.325</td>\n",
       "      <td>48000</td>\n",
       "      <td>0.548169</td>\n",
       "      <td>🌞</td>\n",
       "      <td>76.750</td>\n",
       "      <td>0.980812</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>242</td>\n",
       "      <td>l-4b0n1hfp83tg</td>\n",
       "      <td>11215</td>\n",
       "      <td>5</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2307.325</td>\n",
       "      <td>54000</td>\n",
       "      <td>0.487261</td>\n",
       "      <td>🌗</td>\n",
       "      <td>576.750</td>\n",
       "      <td>0.871833</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>245</td>\n",
       "      <td>l-52b5rnl1erg8</td>\n",
       "      <td>11215</td>\n",
       "      <td>5F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4995</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2802.325</td>\n",
       "      <td>59940</td>\n",
       "      <td>0.438974</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1071.750</td>\n",
       "      <td>0.785435</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>250</td>\n",
       "      <td>l-phubtn46t7vj</td>\n",
       "      <td>11215</td>\n",
       "      <td>2C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3802.325</td>\n",
       "      <td>71940</td>\n",
       "      <td>0.365751</td>\n",
       "      <td>🌗</td>\n",
       "      <td>2071.750</td>\n",
       "      <td>0.654420</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>252</td>\n",
       "      <td>l-mmegr1flhf1d</td>\n",
       "      <td>11225</td>\n",
       "      <td>2F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>857.575</td>\n",
       "      <td>22740</td>\n",
       "      <td>0.547454</td>\n",
       "      <td>🌞</td>\n",
       "      <td>181.450</td>\n",
       "      <td>0.904248</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>273</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3001.250</td>\n",
       "      <td>56400</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1839.325</td>\n",
       "      <td>0.608654</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>289</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3001.250</td>\n",
       "      <td>56400</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1839.325</td>\n",
       "      <td>0.608654</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>306</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3001.250</td>\n",
       "      <td>56400</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1839.325</td>\n",
       "      <td>0.608654</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>318</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>757.325</td>\n",
       "      <td>35400</td>\n",
       "      <td>0.743280</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-973.250</td>\n",
       "      <td>1.329915</td>\n",
       "      <td>1.3🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>320</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>757.325</td>\n",
       "      <td>35400</td>\n",
       "      <td>0.743280</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-973.250</td>\n",
       "      <td>1.329915</td>\n",
       "      <td>1.3🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>334</td>\n",
       "      <td>l-cpa3tvjh3aer</td>\n",
       "      <td>11215</td>\n",
       "      <td>7H</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3422</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>1229.325</td>\n",
       "      <td>41064</td>\n",
       "      <td>0.640758</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-501.250</td>\n",
       "      <td>1.146479</td>\n",
       "      <td>1.1🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>344</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>654.675</td>\n",
       "      <td>33600</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-531.725</td>\n",
       "      <td>1.189902</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>355</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>757.325</td>\n",
       "      <td>35400</td>\n",
       "      <td>0.743280</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-973.250</td>\n",
       "      <td>1.329915</td>\n",
       "      <td>1.3🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>358</td>\n",
       "      <td>l-155vl5l7p3mt</td>\n",
       "      <td>11215</td>\n",
       "      <td>3R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.5</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1807.325</td>\n",
       "      <td>48000</td>\n",
       "      <td>0.548169</td>\n",
       "      <td>🌞</td>\n",
       "      <td>76.750</td>\n",
       "      <td>0.980812</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>365</td>\n",
       "      <td>l-phubtn46t7vj</td>\n",
       "      <td>11215</td>\n",
       "      <td>2C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3802.325</td>\n",
       "      <td>71940</td>\n",
       "      <td>0.365751</td>\n",
       "      <td>🌗</td>\n",
       "      <td>2071.750</td>\n",
       "      <td>0.654420</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>371</td>\n",
       "      <td>l-r51ae16miros</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>407.325</td>\n",
       "      <td>31200</td>\n",
       "      <td>0.843337</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-1323.250</td>\n",
       "      <td>1.508942</td>\n",
       "      <td>1.5🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>372</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>654.675</td>\n",
       "      <td>33600</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-531.725</td>\n",
       "      <td>1.189902</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>390</td>\n",
       "      <td>l-r51ae16miros</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>407.325</td>\n",
       "      <td>31200</td>\n",
       "      <td>0.843337</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-1323.250</td>\n",
       "      <td>1.508942</td>\n",
       "      <td>1.5🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>391</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>654.675</td>\n",
       "      <td>33600</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-531.725</td>\n",
       "      <td>1.189902</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>393</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3001.250</td>\n",
       "      <td>56400</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1839.325</td>\n",
       "      <td>0.608654</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>505</td>\n",
       "      <td>l-u78ca500udu6</td>\n",
       "      <td>11217</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>7000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4854.675</td>\n",
       "      <td>84000</td>\n",
       "      <td>0.306475</td>\n",
       "      <td>🌗</td>\n",
       "      <td>3668.275</td>\n",
       "      <td>0.475961</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>541</td>\n",
       "      <td>l-4lgcsvm0lf5o</td>\n",
       "      <td>11217</td>\n",
       "      <td>GARDEN</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>4995</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2849.675</td>\n",
       "      <td>59940</td>\n",
       "      <td>0.429494</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1663.275</td>\n",
       "      <td>0.667012</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>551</td>\n",
       "      <td>l-ftuu4iri0p65</td>\n",
       "      <td>11217</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6850</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4704.675</td>\n",
       "      <td>82200</td>\n",
       "      <td>0.313186</td>\n",
       "      <td>🌗</td>\n",
       "      <td>3518.275</td>\n",
       "      <td>0.486383</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>579</td>\n",
       "      <td>l-4brn1q68tp8k</td>\n",
       "      <td>11238</td>\n",
       "      <td>1S</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3801.250</td>\n",
       "      <td>66000</td>\n",
       "      <td>0.308864</td>\n",
       "      <td>🌗</td>\n",
       "      <td>2639.325</td>\n",
       "      <td>0.520123</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>632</td>\n",
       "      <td>l-1ts5anpgrdrk</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4201.250</td>\n",
       "      <td>70800</td>\n",
       "      <td>0.287924</td>\n",
       "      <td>🌗</td>\n",
       "      <td>3039.325</td>\n",
       "      <td>0.484860</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>695</td>\n",
       "      <td>l-7u0vaugt03jf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>3850</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2151.250</td>\n",
       "      <td>46200</td>\n",
       "      <td>0.441234</td>\n",
       "      <td>🌗</td>\n",
       "      <td>989.325</td>\n",
       "      <td>0.743032</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>31 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds    size  \\\n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0     NaN   \n",
       "15     213  l-4vkr066dfpsq   11217           1    rental unit   2.0     NaN   \n",
       "18     216  l-jlm1f9thn9hb   11225           1    rental unit   4.0  2000.0   \n",
       "23     227  l-mmegr1flhf1d   11225          2F    rental unit   1.0     NaN   \n",
       "32     241  l-155vl5l7p3mt   11215          3R    rental unit   2.5   900.0   \n",
       "33     242  l-4b0n1hfp83tg   11215           5    rental unit   3.0     NaN   \n",
       "36     245  l-52b5rnl1erg8   11215          5F    rental unit   3.0     NaN   \n",
       "38     250  l-phubtn46t7vj   11215          2C    rental unit   4.0     NaN   \n",
       "39     252  l-mmegr1flhf1d   11225          2F    rental unit   1.0     NaN   \n",
       "57     273  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "68     289  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "77     306  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "85     318  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "87     320  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "97     334  l-cpa3tvjh3aer   11215          7H    rental unit   0.0     NaN   \n",
       "98     344  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "100    355  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "102    358  l-155vl5l7p3mt   11215          3R    rental unit   2.5   900.0   \n",
       "103    365  l-phubtn46t7vj   11215          2C    rental unit   4.0     NaN   \n",
       "105    371  l-r51ae16miros   11215           3    rental unit   1.0   800.0   \n",
       "106    372  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "115    390  l-r51ae16miros   11215           3    rental unit   1.0   800.0   \n",
       "116    391  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "118    393  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "133    505  l-u78ca500udu6   11217           1    rental unit   2.0  1000.0   \n",
       "151    541  l-4lgcsvm0lf5o   11217      GARDEN    rental unit   2.0  1400.0   \n",
       "152    551  l-ftuu4iri0p65   11217           3    rental unit   2.0     NaN   \n",
       "153    579  l-4brn1q68tp8k   11238          1S    rental unit   3.0     NaN   \n",
       "160    632  l-1ts5anpgrdrk   11238           4    rental unit   4.0     NaN   \n",
       "163    695  l-7u0vaugt03jf   11238          4L    rental unit   3.0  1100.0   \n",
       "164    704  l-1akn6ug8021r   11238          2L    rental unit   2.0     NaN   \n",
       "\n",
       "     rent       sun_exposure_cat  \\\n",
       "3    3750      Moderate sunlight   \n",
       "15   2800      Moderate sunlight   \n",
       "18   4795  Limited natural light   \n",
       "23   1895  Limited natural light   \n",
       "32   4000  Limited natural light   \n",
       "33   4500  Limited natural light   \n",
       "36   4995  Limited natural light   \n",
       "38   5995      Moderate sunlight   \n",
       "39   1895  Limited natural light   \n",
       "57   4700  Bright & sun drenched   \n",
       "68   4700  Bright & sun drenched   \n",
       "77   4700  Bright & sun drenched   \n",
       "85   2950      Moderate sunlight   \n",
       "87   2950      Moderate sunlight   \n",
       "97   3422  Bright & sun drenched   \n",
       "98   2800  Limited natural light   \n",
       "100  2950      Moderate sunlight   \n",
       "102  4000  Limited natural light   \n",
       "103  5995      Moderate sunlight   \n",
       "105  2600  Bright & sun drenched   \n",
       "106  2800  Limited natural light   \n",
       "115  2600  Bright & sun drenched   \n",
       "116  2800  Limited natural light   \n",
       "118  4700  Bright & sun drenched   \n",
       "133  7000  Limited natural light   \n",
       "151  4995  Limited natural light   \n",
       "152  6850  Limited natural light   \n",
       "153  5500  Limited natural light   \n",
       "160  5900      Moderate sunlight   \n",
       "163  3850  Bright & sun drenched   \n",
       "164  3900      Moderate sunlight   \n",
       "\n",
       "                                          sun_exposure  ...  \\\n",
       "3    This apartment has moderate sunlight and the r...  ...   \n",
       "15   This apartment has moderate sunlight and the r...  ...   \n",
       "18   This apartment has limited sunlight and the re...  ...   \n",
       "23   This apartment has limited sunlight and the re...  ...   \n",
       "32   This apartment has limited sunlight and the re...  ...   \n",
       "33   This apartment has limited sunlight and the re...  ...   \n",
       "36   This apartment has limited sunlight and the re...  ...   \n",
       "38   This apartment has moderate sunlight and the r...  ...   \n",
       "39   This apartment has limited sunlight and the re...  ...   \n",
       "57   This apartment is bright & sun-drenched and th...  ...   \n",
       "68   This apartment is bright & sun-drenched and th...  ...   \n",
       "77   This apartment is bright & sun-drenched and th...  ...   \n",
       "85   This apartment has moderate sunlight and the r...  ...   \n",
       "87   This apartment has moderate sunlight and the r...  ...   \n",
       "97   This apartment is bright & sun-drenched and th...  ...   \n",
       "98   This apartment has limited sunlight and the re...  ...   \n",
       "100  This apartment has moderate sunlight and the r...  ...   \n",
       "102  This apartment has limited sunlight and the re...  ...   \n",
       "103  This apartment has moderate sunlight and the r...  ...   \n",
       "105  This apartment is bright & sun-drenched and th...  ...   \n",
       "106  This apartment has limited sunlight and the re...  ...   \n",
       "115  This apartment is bright & sun-drenched and th...  ...   \n",
       "116  This apartment has limited sunlight and the re...  ...   \n",
       "118  This apartment is bright & sun-drenched and th...  ...   \n",
       "133  This apartment has limited sunlight and the re...  ...   \n",
       "151  This apartment has limited sunlight and the re...  ...   \n",
       "152  This apartment has limited sunlight and the re...  ...   \n",
       "153  This apartment has limited sunlight and the re...  ...   \n",
       "160  This apartment has moderate sunlight and the r...  ...   \n",
       "163  This apartment is bright & sun-drenched and th...  ...   \n",
       "164  This apartment has moderate sunlight and the r...  ...   \n",
       "\n",
       "    affordable_rent_couple  is_affordable_individual  is_affordable_couple  \\\n",
       "3                 3923.250                     False                  True   \n",
       "15                3331.725                     False                  True   \n",
       "18                1713.550                     False                 False   \n",
       "23                1713.550                     False                 False   \n",
       "32                3923.250                     False                 False   \n",
       "33                3923.250                     False                 False   \n",
       "36                3923.250                     False                 False   \n",
       "38                3923.250                     False                 False   \n",
       "39                1713.550                     False                 False   \n",
       "57                2860.675                     False                 False   \n",
       "68                2860.675                     False                 False   \n",
       "77                2860.675                     False                 False   \n",
       "85                3923.250                     False                  True   \n",
       "87                3923.250                     False                  True   \n",
       "97                3923.250                     False                  True   \n",
       "98                3331.725                     False                  True   \n",
       "100               3923.250                     False                  True   \n",
       "102               3923.250                     False                 False   \n",
       "103               3923.250                     False                 False   \n",
       "105               3923.250                     False                  True   \n",
       "106               3331.725                     False                  True   \n",
       "115               3923.250                     False                  True   \n",
       "116               3331.725                     False                  True   \n",
       "118               2860.675                     False                 False   \n",
       "133               3331.725                     False                 False   \n",
       "151               3331.725                     False                 False   \n",
       "152               3331.725                     False                 False   \n",
       "153               2860.675                     False                 False   \n",
       "160               2860.675                     False                 False   \n",
       "163               2860.675                     False                 False   \n",
       "164               2860.675                     False                 False   \n",
       "\n",
       "     rent_difference_single  annualized_rent  \\\n",
       "3                  1557.325            45000   \n",
       "15                  654.675            33600   \n",
       "18                 3757.575            57540   \n",
       "23                  857.575            22740   \n",
       "32                 1807.325            48000   \n",
       "33                 2307.325            54000   \n",
       "36                 2802.325            59940   \n",
       "38                 3802.325            71940   \n",
       "39                  857.575            22740   \n",
       "57                 3001.250            56400   \n",
       "68                 3001.250            56400   \n",
       "77                 3001.250            56400   \n",
       "85                  757.325            35400   \n",
       "87                  757.325            35400   \n",
       "97                 1229.325            41064   \n",
       "98                  654.675            33600   \n",
       "100                 757.325            35400   \n",
       "102                1807.325            48000   \n",
       "103                3802.325            71940   \n",
       "105                 407.325            31200   \n",
       "106                 654.675            33600   \n",
       "115                 407.325            31200   \n",
       "116                 654.675            33600   \n",
       "118                3001.250            56400   \n",
       "133                4854.675            84000   \n",
       "151                2849.675            59940   \n",
       "152                4704.675            82200   \n",
       "153                3801.250            66000   \n",
       "160                4201.250            70800   \n",
       "163                2151.250            46200   \n",
       "164                2201.250            46800   \n",
       "\n",
       "     indiv_affordability_to_rent_ratio  indiv_sun_exposure_icon  \\\n",
       "3                             0.584713                        🌞   \n",
       "15                            0.766187                        🌞   \n",
       "18                            0.216356                        🌗   \n",
       "23                            0.547454                        🌞   \n",
       "32                            0.548169                        🌞   \n",
       "33                            0.487261                        🌗   \n",
       "36                            0.438974                        🌗   \n",
       "38                            0.365751                        🌗   \n",
       "39                            0.547454                        🌞   \n",
       "57                            0.361436                        🌗   \n",
       "68                            0.361436                        🌗   \n",
       "77                            0.361436                        🌗   \n",
       "85                            0.743280                        🌞   \n",
       "87                            0.743280                        🌞   \n",
       "97                            0.640758                        🌞   \n",
       "98                            0.766187                        🌞   \n",
       "100                           0.743280                        🌞   \n",
       "102                           0.548169                        🌞   \n",
       "103                           0.365751                        🌗   \n",
       "105                           0.843337                        🌞   \n",
       "106                           0.766187                        🌞   \n",
       "115                           0.843337                        🌞   \n",
       "116                           0.766187                        🌞   \n",
       "118                           0.361436                        🌗   \n",
       "133                           0.306475                        🌗   \n",
       "151                           0.429494                        🌗   \n",
       "152                           0.313186                        🌗   \n",
       "153                           0.308864                        🌗   \n",
       "160                           0.287924                        🌗   \n",
       "163                           0.441234                        🌗   \n",
       "164                           0.435577                        🌗   \n",
       "\n",
       "     rent_difference_couple  coup_affordability_to_rent_ratio  \\\n",
       "3                  -173.250                          1.046200   \n",
       "15                 -531.725                          1.189902   \n",
       "18                 3081.450                          0.357362   \n",
       "23                  181.450                          0.904248   \n",
       "32                   76.750                          0.980812   \n",
       "33                  576.750                          0.871833   \n",
       "36                 1071.750                          0.785435   \n",
       "38                 2071.750                          0.654420   \n",
       "39                  181.450                          0.904248   \n",
       "57                 1839.325                          0.608654   \n",
       "68                 1839.325                          0.608654   \n",
       "77                 1839.325                          0.608654   \n",
       "85                 -973.250                          1.329915   \n",
       "87                 -973.250                          1.329915   \n",
       "97                 -501.250                          1.146479   \n",
       "98                 -531.725                          1.189902   \n",
       "100                -973.250                          1.329915   \n",
       "102                  76.750                          0.980812   \n",
       "103                2071.750                          0.654420   \n",
       "105               -1323.250                          1.508942   \n",
       "106                -531.725                          1.189902   \n",
       "115               -1323.250                          1.508942   \n",
       "116                -531.725                          1.189902   \n",
       "118                1839.325                          0.608654   \n",
       "133                3668.275                          0.475961   \n",
       "151                1663.275                          0.667012   \n",
       "152                3518.275                          0.486383   \n",
       "153                2639.325                          0.520123   \n",
       "160                3039.325                          0.484860   \n",
       "163                 989.325                          0.743032   \n",
       "164                1039.325                          0.733506   \n",
       "\n",
       "     coup_sun_exposure_icon  \n",
       "3                      1.0🌞  \n",
       "15                     1.2🌞  \n",
       "18                        🌗  \n",
       "23                        🌞  \n",
       "32                        🌞  \n",
       "33                        🌞  \n",
       "36                        🌞  \n",
       "38                        🌞  \n",
       "39                        🌞  \n",
       "57                        🌞  \n",
       "68                        🌞  \n",
       "77                        🌞  \n",
       "85                     1.3🌞  \n",
       "87                     1.3🌞  \n",
       "97                     1.1🌞  \n",
       "98                     1.2🌞  \n",
       "100                    1.3🌞  \n",
       "102                       🌞  \n",
       "103                       🌞  \n",
       "105                    1.5🌞  \n",
       "106                    1.2🌞  \n",
       "115                    1.5🌞  \n",
       "116                    1.2🌞  \n",
       "118                       🌞  \n",
       "133                       🌗  \n",
       "151                       🌞  \n",
       "152                       🌗  \n",
       "153                       🌞  \n",
       "160                       🌗  \n",
       "163                       🌞  \n",
       "164                       🌞  \n",
       "\n",
       "[31 rows x 25 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_filtered"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "9e07cefa",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
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       "      <th>rent</th>\n",
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       "      <th>sun_exposure</th>\n",
       "      <th>...</th>\n",
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       "      <th>is_affordable_individual</th>\n",
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       "      <th>annualized_rent</th>\n",
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       "      <th>indiv_sun_exposure_icon</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "      <th>coup_sun_exposure_icon</th>\n",
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       "  </thead>\n",
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       "      <th>85</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
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       "      <td>This apartment has moderate sunlight and the r...</td>\n",
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       "      <td>3923.250</td>\n",
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       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>320</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
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       "      <td>35400</td>\n",
       "      <td>0.743280</td>\n",
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       "      <td>1.329915</td>\n",
       "      <td>1.3🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>334</td>\n",
       "      <td>l-cpa3tvjh3aer</td>\n",
       "      <td>11215</td>\n",
       "      <td>7H</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3422</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>1229.325</td>\n",
       "      <td>41064</td>\n",
       "      <td>0.640758</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-501.250</td>\n",
       "      <td>1.146479</td>\n",
       "      <td>1.1🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>355</td>\n",
       "      <td>l-o45jb8pndlm4</td>\n",
       "      <td>11215</td>\n",
       "      <td>1R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2950</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
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       "      <td>1.329915</td>\n",
       "      <td>1.3🌞</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
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       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
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       "      <td>45000</td>\n",
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       "      <td>1.046200</td>\n",
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       "      <th>105</th>\n",
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       "      <td>l-r51ae16miros</td>\n",
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       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>31200</td>\n",
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       "      <td>-1323.250</td>\n",
       "      <td>1.508942</td>\n",
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       "    <tr>\n",
       "      <th>115</th>\n",
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       "      <td>l-r51ae16miros</td>\n",
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       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>31200</td>\n",
       "      <td>0.843337</td>\n",
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       "      <td>-1323.250</td>\n",
       "      <td>1.508942</td>\n",
       "      <td>1.5🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>241</td>\n",
       "      <td>l-155vl5l7p3mt</td>\n",
       "      <td>11215</td>\n",
       "      <td>3R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.5</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1807.325</td>\n",
       "      <td>48000</td>\n",
       "      <td>0.548169</td>\n",
       "      <td>🌞</td>\n",
       "      <td>76.750</td>\n",
       "      <td>0.980812</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>358</td>\n",
       "      <td>l-155vl5l7p3mt</td>\n",
       "      <td>11215</td>\n",
       "      <td>3R</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.5</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1807.325</td>\n",
       "      <td>48000</td>\n",
       "      <td>0.548169</td>\n",
       "      <td>🌞</td>\n",
       "      <td>76.750</td>\n",
       "      <td>0.980812</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>242</td>\n",
       "      <td>l-4b0n1hfp83tg</td>\n",
       "      <td>11215</td>\n",
       "      <td>5</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2307.325</td>\n",
       "      <td>54000</td>\n",
       "      <td>0.487261</td>\n",
       "      <td>🌗</td>\n",
       "      <td>576.750</td>\n",
       "      <td>0.871833</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>245</td>\n",
       "      <td>l-52b5rnl1erg8</td>\n",
       "      <td>11215</td>\n",
       "      <td>5F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4995</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2802.325</td>\n",
       "      <td>59940</td>\n",
       "      <td>0.438974</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1071.750</td>\n",
       "      <td>0.785435</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>250</td>\n",
       "      <td>l-phubtn46t7vj</td>\n",
       "      <td>11215</td>\n",
       "      <td>2C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3802.325</td>\n",
       "      <td>71940</td>\n",
       "      <td>0.365751</td>\n",
       "      <td>🌗</td>\n",
       "      <td>2071.750</td>\n",
       "      <td>0.654420</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>365</td>\n",
       "      <td>l-phubtn46t7vj</td>\n",
       "      <td>11215</td>\n",
       "      <td>2C</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3802.325</td>\n",
       "      <td>71940</td>\n",
       "      <td>0.365751</td>\n",
       "      <td>🌗</td>\n",
       "      <td>2071.750</td>\n",
       "      <td>0.654420</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>344</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>654.675</td>\n",
       "      <td>33600</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-531.725</td>\n",
       "      <td>1.189902</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>372</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>654.675</td>\n",
       "      <td>33600</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-531.725</td>\n",
       "      <td>1.189902</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>391</td>\n",
       "      <td>l-1g19ida1hi7m</td>\n",
       "      <td>11217</td>\n",
       "      <td>1F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>654.675</td>\n",
       "      <td>33600</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-531.725</td>\n",
       "      <td>1.189902</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>213</td>\n",
       "      <td>l-4vkr066dfpsq</td>\n",
       "      <td>11217</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>654.675</td>\n",
       "      <td>33600</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-531.725</td>\n",
       "      <td>1.189902</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>505</td>\n",
       "      <td>l-u78ca500udu6</td>\n",
       "      <td>11217</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>7000</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4854.675</td>\n",
       "      <td>84000</td>\n",
       "      <td>0.306475</td>\n",
       "      <td>🌗</td>\n",
       "      <td>3668.275</td>\n",
       "      <td>0.475961</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>541</td>\n",
       "      <td>l-4lgcsvm0lf5o</td>\n",
       "      <td>11217</td>\n",
       "      <td>GARDEN</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>4995</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2849.675</td>\n",
       "      <td>59940</td>\n",
       "      <td>0.429494</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1663.275</td>\n",
       "      <td>0.667012</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>551</td>\n",
       "      <td>l-ftuu4iri0p65</td>\n",
       "      <td>11217</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6850</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4704.675</td>\n",
       "      <td>82200</td>\n",
       "      <td>0.313186</td>\n",
       "      <td>🌗</td>\n",
       "      <td>3518.275</td>\n",
       "      <td>0.486383</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>227</td>\n",
       "      <td>l-mmegr1flhf1d</td>\n",
       "      <td>11225</td>\n",
       "      <td>2F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>857.575</td>\n",
       "      <td>22740</td>\n",
       "      <td>0.547454</td>\n",
       "      <td>🌞</td>\n",
       "      <td>181.450</td>\n",
       "      <td>0.904248</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>252</td>\n",
       "      <td>l-mmegr1flhf1d</td>\n",
       "      <td>11225</td>\n",
       "      <td>2F</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>857.575</td>\n",
       "      <td>22740</td>\n",
       "      <td>0.547454</td>\n",
       "      <td>🌞</td>\n",
       "      <td>181.450</td>\n",
       "      <td>0.904248</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>216</td>\n",
       "      <td>l-jlm1f9thn9hb</td>\n",
       "      <td>11225</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>4795</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3757.575</td>\n",
       "      <td>57540</td>\n",
       "      <td>0.216356</td>\n",
       "      <td>🌗</td>\n",
       "      <td>3081.450</td>\n",
       "      <td>0.357362</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>273</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3001.250</td>\n",
       "      <td>56400</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1839.325</td>\n",
       "      <td>0.608654</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>289</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3001.250</td>\n",
       "      <td>56400</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1839.325</td>\n",
       "      <td>0.608654</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>306</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3001.250</td>\n",
       "      <td>56400</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1839.325</td>\n",
       "      <td>0.608654</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>393</td>\n",
       "      <td>l-ce404lar05gn</td>\n",
       "      <td>11238</td>\n",
       "      <td>1</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3001.250</td>\n",
       "      <td>56400</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1839.325</td>\n",
       "      <td>0.608654</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>579</td>\n",
       "      <td>l-4brn1q68tp8k</td>\n",
       "      <td>11238</td>\n",
       "      <td>1S</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500</td>\n",
       "      <td>Limited natural light</td>\n",
       "      <td>This apartment has limited sunlight and the re...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3801.250</td>\n",
       "      <td>66000</td>\n",
       "      <td>0.308864</td>\n",
       "      <td>🌗</td>\n",
       "      <td>2639.325</td>\n",
       "      <td>0.520123</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>695</td>\n",
       "      <td>l-7u0vaugt03jf</td>\n",
       "      <td>11238</td>\n",
       "      <td>4L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>3850</td>\n",
       "      <td>Bright &amp; sun drenched</td>\n",
       "      <td>This apartment is bright &amp; sun-drenched and th...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2151.250</td>\n",
       "      <td>46200</td>\n",
       "      <td>0.441234</td>\n",
       "      <td>🌗</td>\n",
       "      <td>989.325</td>\n",
       "      <td>0.743032</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>632</td>\n",
       "      <td>l-1ts5anpgrdrk</td>\n",
       "      <td>11238</td>\n",
       "      <td>4</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4201.250</td>\n",
       "      <td>70800</td>\n",
       "      <td>0.287924</td>\n",
       "      <td>🌗</td>\n",
       "      <td>3039.325</td>\n",
       "      <td>0.484860</td>\n",
       "      <td>🌗</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>31 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds    size  \\\n",
       "85     318  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "87     320  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "97     334  l-cpa3tvjh3aer   11215          7H    rental unit   0.0     NaN   \n",
       "100    355  l-o45jb8pndlm4   11215          1R    rental unit   0.0     NaN   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0     NaN   \n",
       "105    371  l-r51ae16miros   11215           3    rental unit   1.0   800.0   \n",
       "115    390  l-r51ae16miros   11215           3    rental unit   1.0   800.0   \n",
       "32     241  l-155vl5l7p3mt   11215          3R    rental unit   2.5   900.0   \n",
       "102    358  l-155vl5l7p3mt   11215          3R    rental unit   2.5   900.0   \n",
       "33     242  l-4b0n1hfp83tg   11215           5    rental unit   3.0     NaN   \n",
       "36     245  l-52b5rnl1erg8   11215          5F    rental unit   3.0     NaN   \n",
       "38     250  l-phubtn46t7vj   11215          2C    rental unit   4.0     NaN   \n",
       "103    365  l-phubtn46t7vj   11215          2C    rental unit   4.0     NaN   \n",
       "98     344  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "106    372  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "116    391  l-1g19ida1hi7m   11217          1F    rental unit   1.0   925.0   \n",
       "15     213  l-4vkr066dfpsq   11217           1    rental unit   2.0     NaN   \n",
       "133    505  l-u78ca500udu6   11217           1    rental unit   2.0  1000.0   \n",
       "151    541  l-4lgcsvm0lf5o   11217      GARDEN    rental unit   2.0  1400.0   \n",
       "152    551  l-ftuu4iri0p65   11217           3    rental unit   2.0     NaN   \n",
       "23     227  l-mmegr1flhf1d   11225          2F    rental unit   1.0     NaN   \n",
       "39     252  l-mmegr1flhf1d   11225          2F    rental unit   1.0     NaN   \n",
       "18     216  l-jlm1f9thn9hb   11225           1    rental unit   4.0  2000.0   \n",
       "57     273  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "68     289  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "77     306  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "118    393  l-ce404lar05gn   11238           1    rental unit   2.0   850.0   \n",
       "164    704  l-1akn6ug8021r   11238          2L    rental unit   2.0     NaN   \n",
       "153    579  l-4brn1q68tp8k   11238          1S    rental unit   3.0     NaN   \n",
       "163    695  l-7u0vaugt03jf   11238          4L    rental unit   3.0  1100.0   \n",
       "160    632  l-1ts5anpgrdrk   11238           4    rental unit   4.0     NaN   \n",
       "\n",
       "     rent       sun_exposure_cat  \\\n",
       "85   2950      Moderate sunlight   \n",
       "87   2950      Moderate sunlight   \n",
       "97   3422  Bright & sun drenched   \n",
       "100  2950      Moderate sunlight   \n",
       "3    3750      Moderate sunlight   \n",
       "105  2600  Bright & sun drenched   \n",
       "115  2600  Bright & sun drenched   \n",
       "32   4000  Limited natural light   \n",
       "102  4000  Limited natural light   \n",
       "33   4500  Limited natural light   \n",
       "36   4995  Limited natural light   \n",
       "38   5995      Moderate sunlight   \n",
       "103  5995      Moderate sunlight   \n",
       "98   2800  Limited natural light   \n",
       "106  2800  Limited natural light   \n",
       "116  2800  Limited natural light   \n",
       "15   2800      Moderate sunlight   \n",
       "133  7000  Limited natural light   \n",
       "151  4995  Limited natural light   \n",
       "152  6850  Limited natural light   \n",
       "23   1895  Limited natural light   \n",
       "39   1895  Limited natural light   \n",
       "18   4795  Limited natural light   \n",
       "57   4700  Bright & sun drenched   \n",
       "68   4700  Bright & sun drenched   \n",
       "77   4700  Bright & sun drenched   \n",
       "118  4700  Bright & sun drenched   \n",
       "164  3900      Moderate sunlight   \n",
       "153  5500  Limited natural light   \n",
       "163  3850  Bright & sun drenched   \n",
       "160  5900      Moderate sunlight   \n",
       "\n",
       "                                          sun_exposure  ...  \\\n",
       "85   This apartment has moderate sunlight and the r...  ...   \n",
       "87   This apartment has moderate sunlight and the r...  ...   \n",
       "97   This apartment is bright & sun-drenched and th...  ...   \n",
       "100  This apartment has moderate sunlight and the r...  ...   \n",
       "3    This apartment has moderate sunlight and the r...  ...   \n",
       "105  This apartment is bright & sun-drenched and th...  ...   \n",
       "115  This apartment is bright & sun-drenched and th...  ...   \n",
       "32   This apartment has limited sunlight and the re...  ...   \n",
       "102  This apartment has limited sunlight and the re...  ...   \n",
       "33   This apartment has limited sunlight and the re...  ...   \n",
       "36   This apartment has limited sunlight and the re...  ...   \n",
       "38   This apartment has moderate sunlight and the r...  ...   \n",
       "103  This apartment has moderate sunlight and the r...  ...   \n",
       "98   This apartment has limited sunlight and the re...  ...   \n",
       "106  This apartment has limited sunlight and the re...  ...   \n",
       "116  This apartment has limited sunlight and the re...  ...   \n",
       "15   This apartment has moderate sunlight and the r...  ...   \n",
       "133  This apartment has limited sunlight and the re...  ...   \n",
       "151  This apartment has limited sunlight and the re...  ...   \n",
       "152  This apartment has limited sunlight and the re...  ...   \n",
       "23   This apartment has limited sunlight and the re...  ...   \n",
       "39   This apartment has limited sunlight and the re...  ...   \n",
       "18   This apartment has limited sunlight and the re...  ...   \n",
       "57   This apartment is bright & sun-drenched and th...  ...   \n",
       "68   This apartment is bright & sun-drenched and th...  ...   \n",
       "77   This apartment is bright & sun-drenched and th...  ...   \n",
       "118  This apartment is bright & sun-drenched and th...  ...   \n",
       "164  This apartment has moderate sunlight and the r...  ...   \n",
       "153  This apartment has limited sunlight and the re...  ...   \n",
       "163  This apartment is bright & sun-drenched and th...  ...   \n",
       "160  This apartment has moderate sunlight and the r...  ...   \n",
       "\n",
       "    affordable_rent_couple  is_affordable_individual  is_affordable_couple  \\\n",
       "85                3923.250                     False                  True   \n",
       "87                3923.250                     False                  True   \n",
       "97                3923.250                     False                  True   \n",
       "100               3923.250                     False                  True   \n",
       "3                 3923.250                     False                  True   \n",
       "105               3923.250                     False                  True   \n",
       "115               3923.250                     False                  True   \n",
       "32                3923.250                     False                 False   \n",
       "102               3923.250                     False                 False   \n",
       "33                3923.250                     False                 False   \n",
       "36                3923.250                     False                 False   \n",
       "38                3923.250                     False                 False   \n",
       "103               3923.250                     False                 False   \n",
       "98                3331.725                     False                  True   \n",
       "106               3331.725                     False                  True   \n",
       "116               3331.725                     False                  True   \n",
       "15                3331.725                     False                  True   \n",
       "133               3331.725                     False                 False   \n",
       "151               3331.725                     False                 False   \n",
       "152               3331.725                     False                 False   \n",
       "23                1713.550                     False                 False   \n",
       "39                1713.550                     False                 False   \n",
       "18                1713.550                     False                 False   \n",
       "57                2860.675                     False                 False   \n",
       "68                2860.675                     False                 False   \n",
       "77                2860.675                     False                 False   \n",
       "118               2860.675                     False                 False   \n",
       "164               2860.675                     False                 False   \n",
       "153               2860.675                     False                 False   \n",
       "163               2860.675                     False                 False   \n",
       "160               2860.675                     False                 False   \n",
       "\n",
       "     rent_difference_single  annualized_rent  \\\n",
       "85                  757.325            35400   \n",
       "87                  757.325            35400   \n",
       "97                 1229.325            41064   \n",
       "100                 757.325            35400   \n",
       "3                  1557.325            45000   \n",
       "105                 407.325            31200   \n",
       "115                 407.325            31200   \n",
       "32                 1807.325            48000   \n",
       "102                1807.325            48000   \n",
       "33                 2307.325            54000   \n",
       "36                 2802.325            59940   \n",
       "38                 3802.325            71940   \n",
       "103                3802.325            71940   \n",
       "98                  654.675            33600   \n",
       "106                 654.675            33600   \n",
       "116                 654.675            33600   \n",
       "15                  654.675            33600   \n",
       "133                4854.675            84000   \n",
       "151                2849.675            59940   \n",
       "152                4704.675            82200   \n",
       "23                  857.575            22740   \n",
       "39                  857.575            22740   \n",
       "18                 3757.575            57540   \n",
       "57                 3001.250            56400   \n",
       "68                 3001.250            56400   \n",
       "77                 3001.250            56400   \n",
       "118                3001.250            56400   \n",
       "164                2201.250            46800   \n",
       "153                3801.250            66000   \n",
       "163                2151.250            46200   \n",
       "160                4201.250            70800   \n",
       "\n",
       "     indiv_affordability_to_rent_ratio  indiv_sun_exposure_icon  \\\n",
       "85                            0.743280                        🌞   \n",
       "87                            0.743280                        🌞   \n",
       "97                            0.640758                        🌞   \n",
       "100                           0.743280                        🌞   \n",
       "3                             0.584713                        🌞   \n",
       "105                           0.843337                        🌞   \n",
       "115                           0.843337                        🌞   \n",
       "32                            0.548169                        🌞   \n",
       "102                           0.548169                        🌞   \n",
       "33                            0.487261                        🌗   \n",
       "36                            0.438974                        🌗   \n",
       "38                            0.365751                        🌗   \n",
       "103                           0.365751                        🌗   \n",
       "98                            0.766187                        🌞   \n",
       "106                           0.766187                        🌞   \n",
       "116                           0.766187                        🌞   \n",
       "15                            0.766187                        🌞   \n",
       "133                           0.306475                        🌗   \n",
       "151                           0.429494                        🌗   \n",
       "152                           0.313186                        🌗   \n",
       "23                            0.547454                        🌞   \n",
       "39                            0.547454                        🌞   \n",
       "18                            0.216356                        🌗   \n",
       "57                            0.361436                        🌗   \n",
       "68                            0.361436                        🌗   \n",
       "77                            0.361436                        🌗   \n",
       "118                           0.361436                        🌗   \n",
       "164                           0.435577                        🌗   \n",
       "153                           0.308864                        🌗   \n",
       "163                           0.441234                        🌗   \n",
       "160                           0.287924                        🌗   \n",
       "\n",
       "     rent_difference_couple  coup_affordability_to_rent_ratio  \\\n",
       "85                 -973.250                          1.329915   \n",
       "87                 -973.250                          1.329915   \n",
       "97                 -501.250                          1.146479   \n",
       "100                -973.250                          1.329915   \n",
       "3                  -173.250                          1.046200   \n",
       "105               -1323.250                          1.508942   \n",
       "115               -1323.250                          1.508942   \n",
       "32                   76.750                          0.980812   \n",
       "102                  76.750                          0.980812   \n",
       "33                  576.750                          0.871833   \n",
       "36                 1071.750                          0.785435   \n",
       "38                 2071.750                          0.654420   \n",
       "103                2071.750                          0.654420   \n",
       "98                 -531.725                          1.189902   \n",
       "106                -531.725                          1.189902   \n",
       "116                -531.725                          1.189902   \n",
       "15                 -531.725                          1.189902   \n",
       "133                3668.275                          0.475961   \n",
       "151                1663.275                          0.667012   \n",
       "152                3518.275                          0.486383   \n",
       "23                  181.450                          0.904248   \n",
       "39                  181.450                          0.904248   \n",
       "18                 3081.450                          0.357362   \n",
       "57                 1839.325                          0.608654   \n",
       "68                 1839.325                          0.608654   \n",
       "77                 1839.325                          0.608654   \n",
       "118                1839.325                          0.608654   \n",
       "164                1039.325                          0.733506   \n",
       "153                2639.325                          0.520123   \n",
       "163                 989.325                          0.743032   \n",
       "160                3039.325                          0.484860   \n",
       "\n",
       "     coup_sun_exposure_icon  \n",
       "85                     1.3🌞  \n",
       "87                     1.3🌞  \n",
       "97                     1.1🌞  \n",
       "100                    1.3🌞  \n",
       "3                      1.0🌞  \n",
       "105                    1.5🌞  \n",
       "115                    1.5🌞  \n",
       "32                        🌞  \n",
       "102                       🌞  \n",
       "33                        🌞  \n",
       "36                        🌞  \n",
       "38                        🌞  \n",
       "103                       🌞  \n",
       "98                     1.2🌞  \n",
       "106                    1.2🌞  \n",
       "116                    1.2🌞  \n",
       "15                     1.2🌞  \n",
       "133                       🌗  \n",
       "151                       🌞  \n",
       "152                       🌗  \n",
       "23                        🌞  \n",
       "39                        🌞  \n",
       "18                        🌗  \n",
       "57                        🌞  \n",
       "68                        🌞  \n",
       "77                        🌞  \n",
       "118                       🌞  \n",
       "164                       🌞  \n",
       "153                       🌞  \n",
       "163                       🌞  \n",
       "160                       🌗  \n",
       "\n",
       "[31 rows x 25 columns]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_merged_filtered\n",
    "     .sort_values(['zipcode','beds'])\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "a61bd2df",
   "metadata": {},
   "outputs": [],
   "source": [
    "def map_ratio_to_icon(ratio):\n",
    "    if ratio < 0:\n",
    "        return '☔'  # Using umbrella icon to denote negative rent difference\n",
    "    elif ratio <= 0.5:\n",
    "        return '🌗'  # Half sun (replace with your own icon)\n",
    "    elif ratio <= 1:\n",
    "        return '🌞'  # Full sun (replace with your own icon)\n",
    "    else:\n",
    "        return f'{ratio:.1f}🌞'  # More than 1 full sun\n",
    "\n",
    "# df_grouped = df_merged.groupby('zipcode').mean()\n",
    "df_grouped['coup_sun_exposure_icon'] = df_grouped['coup_affordability_to_rent_ratio'].apply(map_ratio_to_icon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "610245ca",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>median age</th>\n",
       "      <th>per capita income</th>\n",
       "      <th>median household income</th>\n",
       "      <th>affordable_rent_single</th>\n",
       "      <th>affordable_rent_couple</th>\n",
       "      <th>is_affordable_individual</th>\n",
       "      <th>is_affordable_couple</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "      <th>coup_sun_exposure_icon</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zipcode</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11215</th>\n",
       "      <td>329.529412</td>\n",
       "      <td>1.431373</td>\n",
       "      <td>667.600000</td>\n",
       "      <td>3790.000000</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
       "      <td>156930.0</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>0.078431</td>\n",
       "      <td>0.627451</td>\n",
       "      <td>1597.325000</td>\n",
       "      <td>45480.000000</td>\n",
       "      <td>0.659563</td>\n",
       "      <td>-133.250000</td>\n",
       "      <td>1.180126</td>\n",
       "      <td>1.2🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11217</th>\n",
       "      <td>401.047619</td>\n",
       "      <td>1.023810</td>\n",
       "      <td>963.888889</td>\n",
       "      <td>4167.023810</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813.0</td>\n",
       "      <td>133269.0</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.261905</td>\n",
       "      <td>2021.698810</td>\n",
       "      <td>50004.285714</td>\n",
       "      <td>0.547054</td>\n",
       "      <td>835.298810</td>\n",
       "      <td>0.849584</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11218</th>\n",
       "      <td>324.500000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3050.000000</td>\n",
       "      <td>36.4</td>\n",
       "      <td>43113.0</td>\n",
       "      <td>81857.0</td>\n",
       "      <td>1077.825</td>\n",
       "      <td>2046.425</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1972.175000</td>\n",
       "      <td>36600.000000</td>\n",
       "      <td>0.354911</td>\n",
       "      <td>1003.575000</td>\n",
       "      <td>0.673857</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11225</th>\n",
       "      <td>248.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1173.750000</td>\n",
       "      <td>3277.100000</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497.0</td>\n",
       "      <td>68542.0</td>\n",
       "      <td>1037.425</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2239.675000</td>\n",
       "      <td>39325.200000</td>\n",
       "      <td>0.358370</td>\n",
       "      <td>1563.550000</td>\n",
       "      <td>0.591932</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11226</th>\n",
       "      <td>255.433333</td>\n",
       "      <td>1.266667</td>\n",
       "      <td>1077.000000</td>\n",
       "      <td>3073.200000</td>\n",
       "      <td>35.4</td>\n",
       "      <td>34323.0</td>\n",
       "      <td>66173.0</td>\n",
       "      <td>858.075</td>\n",
       "      <td>1654.325</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2215.125000</td>\n",
       "      <td>36878.400000</td>\n",
       "      <td>0.284774</td>\n",
       "      <td>1418.875000</td>\n",
       "      <td>0.549031</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11238</th>\n",
       "      <td>481.138889</td>\n",
       "      <td>1.472222</td>\n",
       "      <td>950.000000</td>\n",
       "      <td>4231.305556</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950.0</td>\n",
       "      <td>114427.0</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>2532.555556</td>\n",
       "      <td>50775.666667</td>\n",
       "      <td>0.421898</td>\n",
       "      <td>1370.630556</td>\n",
       "      <td>0.710471</td>\n",
       "      <td>🌞</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              index      beds         size         rent  median age  \\\n",
       "zipcode                                                               \n",
       "11215    329.529412  1.431373   667.600000  3790.000000        37.0   \n",
       "11217    401.047619  1.023810   963.888889  4167.023810        35.5   \n",
       "11218    324.500000  1.500000          NaN  3050.000000        36.4   \n",
       "11225    248.000000  1.500000  1173.750000  3277.100000        36.1   \n",
       "11226    255.433333  1.266667  1077.000000  3073.200000        35.4   \n",
       "11238    481.138889  1.472222   950.000000  4231.305556        35.3   \n",
       "\n",
       "         per capita income  median household income  affordable_rent_single  \\\n",
       "zipcode                                                                       \n",
       "11215              87707.0                 156930.0                2192.675   \n",
       "11217              85813.0                 133269.0                2145.325   \n",
       "11218              43113.0                  81857.0                1077.825   \n",
       "11225              41497.0                  68542.0                1037.425   \n",
       "11226              34323.0                  66173.0                 858.075   \n",
       "11238              67950.0                 114427.0                1698.750   \n",
       "\n",
       "         affordable_rent_couple  is_affordable_individual  \\\n",
       "zipcode                                                     \n",
       "11215                  3923.250                  0.078431   \n",
       "11217                  3331.725                  0.000000   \n",
       "11218                  2046.425                  0.000000   \n",
       "11225                  1713.550                  0.000000   \n",
       "11226                  1654.325                  0.000000   \n",
       "11238                  2860.675                  0.000000   \n",
       "\n",
       "         is_affordable_couple  rent_difference_single  annualized_rent  \\\n",
       "zipcode                                                                  \n",
       "11215                0.627451             1597.325000     45480.000000   \n",
       "11217                0.261905             2021.698810     50004.285714   \n",
       "11218                0.000000             1972.175000     36600.000000   \n",
       "11225                0.000000             2239.675000     39325.200000   \n",
       "11226                0.000000             2215.125000     36878.400000   \n",
       "11238                0.055556             2532.555556     50775.666667   \n",
       "\n",
       "         indiv_affordability_to_rent_ratio  rent_difference_couple  \\\n",
       "zipcode                                                              \n",
       "11215                             0.659563             -133.250000   \n",
       "11217                             0.547054              835.298810   \n",
       "11218                             0.354911             1003.575000   \n",
       "11225                             0.358370             1563.550000   \n",
       "11226                             0.284774             1418.875000   \n",
       "11238                             0.421898             1370.630556   \n",
       "\n",
       "         coup_affordability_to_rent_ratio coup_sun_exposure_icon  \n",
       "zipcode                                                           \n",
       "11215                            1.180126                   1.2🌞  \n",
       "11217                            0.849584                      🌞  \n",
       "11218                            0.673857                      🌞  \n",
       "11225                            0.591932                      🌞  \n",
       "11226                            0.549031                      🌞  \n",
       "11238                            0.710471                      🌞  "
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "df7379bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zipcode  indiv_sun_exposure_icon  coup_sun_exposure_icon\n",
       "11215    🌞                        1.2🌞                      1\n",
       "11217    🌞                        🌞                         1\n",
       "11218    🌗                        🌞                         1\n",
       "11225    🌗                        🌞                         1\n",
       "11226    🌗                        🌞                         1\n",
       "11238    🌗                        🌞                         1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_grouped.groupby(['zipcode', 'indiv_sun_exposure_icon','coup_sun_exposure_icon' ]).size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "9b36bf11",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/km/gmzkf_4n5qn6c84ksf3bzy0c0000gn/T/ipykernel_84608/3235621760.py:2: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  .groupby(['zipcode']).mean()\n"
     ]
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>beds</th>\n",
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       "      <th>is_affordable_couple</th>\n",
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       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zipcode</th>\n",
       "      <th></th>\n",
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       "      <td>175.083333</td>\n",
       "      <td>1.057464</td>\n",
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       "    <tr>\n",
       "      <th>11217</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>35.5</td>\n",
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       "      <td>4900.000000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950.0</td>\n",
       "      <td>114427.0</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3201.250000</td>\n",
       "      <td>58800.0</td>\n",
       "      <td>0.361750</td>\n",
       "      <td>2039.325000</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "              index  beds  size         rent  median age  per capita income  \\\n",
       "zipcode                                                                       \n",
       "11215    301.166667   1.5   NaN  4098.333333        37.0            87707.0   \n",
       "11217    213.000000   2.0   NaN  2800.000000        35.5            85813.0   \n",
       "11238    668.000000   3.0   NaN  4900.000000        35.3            67950.0   \n",
       "\n",
       "         median household income  affordable_rent_single  \\\n",
       "zipcode                                                    \n",
       "11215                   156930.0                2192.675   \n",
       "11217                   133269.0                2145.325   \n",
       "11238                   114427.0                1698.750   \n",
       "\n",
       "         affordable_rent_couple  is_affordable_individual  \\\n",
       "zipcode                                                     \n",
       "11215                  3923.250                       0.0   \n",
       "11217                  3331.725                       0.0   \n",
       "11238                  2860.675                       0.0   \n",
       "\n",
       "         is_affordable_couple  rent_difference_single  annualized_rent  \\\n",
       "zipcode                                                                  \n",
       "11215                0.666667             1905.658333          49180.0   \n",
       "11217                1.000000              654.675000          33600.0   \n",
       "11238                0.000000             3201.250000          58800.0   \n",
       "\n",
       "         indiv_affordability_to_rent_ratio  rent_difference_couple  \\\n",
       "zipcode                                                              \n",
       "11215                             0.591009              175.083333   \n",
       "11217                             0.766187             -531.725000   \n",
       "11238                             0.361750             2039.325000   \n",
       "\n",
       "         coup_affordability_to_rent_ratio  \n",
       "zipcode                                    \n",
       "11215                            1.057464  \n",
       "11217                            1.189902  \n",
       "11238                            0.609183  "
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_merged_filtered[df_merged_filtered['sun_exposure_cat']== 'Moderate sunlight' ]\n",
    " .groupby(['zipcode']).mean()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "3da85454",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/km/gmzkf_4n5qn6c84ksf3bzy0c0000gn/T/ipykernel_84608/4250093208.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_merged_filtered['beds'] = df_merged_filtered['beds'].astype(str)\n"
     ]
    }
   ],
   "source": [
    "df_merged_filtered['beds'] = df_merged_filtered['beds'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "93b74f28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "index                                  int64\n",
       "listing_path                          object\n",
       "zipcode                               object\n",
       "unit_number                           object\n",
       "building_class                        object\n",
       "beds                                  object\n",
       "size                                 float64\n",
       "rent                                   int64\n",
       "sun_exposure_cat                      object\n",
       "sun_exposure                          object\n",
       "floor                                 object\n",
       "median age                           float64\n",
       "per capita income                      int64\n",
       "median household income                int64\n",
       "affordable_rent_single               float64\n",
       "affordable_rent_couple               float64\n",
       "is_affordable_individual                bool\n",
       "is_affordable_couple                    bool\n",
       "rent_difference_single               float64\n",
       "annualized_rent                        int64\n",
       "indiv_affordability_to_rent_ratio    float64\n",
       "indiv_sun_exposure_icon               object\n",
       "rent_difference_couple               float64\n",
       "coup_affordability_to_rent_ratio     float64\n",
       "coup_sun_exposure_icon                object\n",
       "dtype: object"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_filtered.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "6ef6003b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/km/gmzkf_4n5qn6c84ksf3bzy0c0000gn/T/ipykernel_84608/188013714.py:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  df_merged_filtered.groupby(['zipcode','beds','sun_exposure_cat']).mean()\n"
     ]
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       "      <th>coup_affordability_to_rent_ratio</th>\n",
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       "      <th>zipcode</th>\n",
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       "      <th rowspan=\"7\" valign=\"top\">11215</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">0</th>\n",
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       "      <td>334.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3422.000000</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
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       "      <td>41064.0</td>\n",
       "      <td>0.640758</td>\n",
       "      <td>-501.250000</td>\n",
       "      <td>1.146479</td>\n",
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       "    <tr>\n",
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       "      <td>NaN</td>\n",
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       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>757.325000</td>\n",
       "      <td>35400.0</td>\n",
       "      <td>0.743280</td>\n",
       "      <td>-973.250000</td>\n",
       "      <td>1.329915</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
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       "      <td>380.500000</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2600.000000</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
       "      <td>156930.0</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>407.325000</td>\n",
       "      <td>31200.0</td>\n",
       "      <td>0.843337</td>\n",
       "      <td>-1323.250000</td>\n",
       "      <td>1.508942</td>\n",
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       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>199.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750.000000</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
       "      <td>156930.0</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1557.325000</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>-173.250000</td>\n",
       "      <td>1.046200</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>299.500000</td>\n",
       "      <td>900.0</td>\n",
       "      <td>4000.000000</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
       "      <td>156930.0</td>\n",
       "      <td>2192.675</td>\n",
       "      <td>3923.250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1807.325000</td>\n",
       "      <td>48000.0</td>\n",
       "      <td>0.548169</td>\n",
       "      <td>76.750000</td>\n",
       "      <td>0.980812</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>243.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4747.500000</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2554.825000</td>\n",
       "      <td>56970.0</td>\n",
       "      <td>0.463118</td>\n",
       "      <td>824.250000</td>\n",
       "      <td>0.828634</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>307.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5995.000000</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87707.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3802.325000</td>\n",
       "      <td>71940.0</td>\n",
       "      <td>0.365751</td>\n",
       "      <td>2071.750000</td>\n",
       "      <td>0.654420</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">11217</th>\n",
       "      <th>1</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>369.000000</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813.0</td>\n",
       "      <td>133269.0</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>654.675000</td>\n",
       "      <td>33600.0</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>-531.725000</td>\n",
       "      <td>1.189902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>532.333333</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>6281.666667</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813.0</td>\n",
       "      <td>133269.0</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4136.341667</td>\n",
       "      <td>75380.0</td>\n",
       "      <td>0.349719</td>\n",
       "      <td>2949.941667</td>\n",
       "      <td>0.543119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>213.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>35.5</td>\n",
       "      <td>85813.0</td>\n",
       "      <td>133269.0</td>\n",
       "      <td>2145.325</td>\n",
       "      <td>3331.725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>654.675000</td>\n",
       "      <td>33600.0</td>\n",
       "      <td>0.766187</td>\n",
       "      <td>-531.725000</td>\n",
       "      <td>1.189902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">11225</th>\n",
       "      <th>1</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>239.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895.000000</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497.0</td>\n",
       "      <td>68542.0</td>\n",
       "      <td>1037.425</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>857.575000</td>\n",
       "      <td>22740.0</td>\n",
       "      <td>0.547454</td>\n",
       "      <td>181.450000</td>\n",
       "      <td>0.904248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>216.000000</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>4795.000000</td>\n",
       "      <td>36.1</td>\n",
       "      <td>41497.0</td>\n",
       "      <td>68542.0</td>\n",
       "      <td>1037.425</td>\n",
       "      <td>1713.550</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3757.575000</td>\n",
       "      <td>57540.0</td>\n",
       "      <td>0.216356</td>\n",
       "      <td>3081.450000</td>\n",
       "      <td>0.357362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">11238</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">2</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>315.250000</td>\n",
       "      <td>850.0</td>\n",
       "      <td>4700.000000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950.0</td>\n",
       "      <td>114427.0</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3001.250000</td>\n",
       "      <td>56400.0</td>\n",
       "      <td>0.361436</td>\n",
       "      <td>1839.325000</td>\n",
       "      <td>0.608654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>704.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900.000000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950.0</td>\n",
       "      <td>114427.0</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2201.250000</td>\n",
       "      <td>46800.0</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>1039.325000</td>\n",
       "      <td>0.733506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">3</th>\n",
       "      <th>Bright &amp; sun drenched</th>\n",
       "      <td>695.000000</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>3850.000000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950.0</td>\n",
       "      <td>114427.0</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2151.250000</td>\n",
       "      <td>46200.0</td>\n",
       "      <td>0.441234</td>\n",
       "      <td>989.325000</td>\n",
       "      <td>0.743032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Limited natural light</th>\n",
       "      <td>579.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500.000000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950.0</td>\n",
       "      <td>114427.0</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3801.250000</td>\n",
       "      <td>66000.0</td>\n",
       "      <td>0.308864</td>\n",
       "      <td>2639.325000</td>\n",
       "      <td>0.520123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>Moderate sunlight</th>\n",
       "      <td>632.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5900.000000</td>\n",
       "      <td>35.3</td>\n",
       "      <td>67950.0</td>\n",
       "      <td>114427.0</td>\n",
       "      <td>1698.750</td>\n",
       "      <td>2860.675</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4201.250000</td>\n",
       "      <td>70800.0</td>\n",
       "      <td>0.287924</td>\n",
       "      <td>3039.325000</td>\n",
       "      <td>0.484860</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         index    size         rent  \\\n",
       "zipcode beds sun_exposure_cat                                         \n",
       "11215   0    Bright & sun drenched  334.000000     NaN  3422.000000   \n",
       "             Moderate sunlight      331.000000     NaN  2950.000000   \n",
       "        1    Bright & sun drenched  380.500000   800.0  2600.000000   \n",
       "             Moderate sunlight      199.000000     NaN  3750.000000   \n",
       "        2    Limited natural light  299.500000   900.0  4000.000000   \n",
       "        3    Limited natural light  243.500000     NaN  4747.500000   \n",
       "        4    Moderate sunlight      307.500000     NaN  5995.000000   \n",
       "11217   1    Limited natural light  369.000000   925.0  2800.000000   \n",
       "        2    Limited natural light  532.333333  1200.0  6281.666667   \n",
       "             Moderate sunlight      213.000000     NaN  2800.000000   \n",
       "11225   1    Limited natural light  239.500000     NaN  1895.000000   \n",
       "        4    Limited natural light  216.000000  2000.0  4795.000000   \n",
       "11238   2    Bright & sun drenched  315.250000   850.0  4700.000000   \n",
       "             Moderate sunlight      704.000000     NaN  3900.000000   \n",
       "        3    Bright & sun drenched  695.000000  1100.0  3850.000000   \n",
       "             Limited natural light  579.000000     NaN  5500.000000   \n",
       "        4    Moderate sunlight      632.000000     NaN  5900.000000   \n",
       "\n",
       "                                    median age  per capita income  \\\n",
       "zipcode beds sun_exposure_cat                                       \n",
       "11215   0    Bright & sun drenched        37.0            87707.0   \n",
       "             Moderate sunlight            37.0            87707.0   \n",
       "        1    Bright & sun drenched        37.0            87707.0   \n",
       "             Moderate sunlight            37.0            87707.0   \n",
       "        2    Limited natural light        37.0            87707.0   \n",
       "        3    Limited natural light        37.0            87707.0   \n",
       "        4    Moderate sunlight            37.0            87707.0   \n",
       "11217   1    Limited natural light        35.5            85813.0   \n",
       "        2    Limited natural light        35.5            85813.0   \n",
       "             Moderate sunlight            35.5            85813.0   \n",
       "11225   1    Limited natural light        36.1            41497.0   \n",
       "        4    Limited natural light        36.1            41497.0   \n",
       "11238   2    Bright & sun drenched        35.3            67950.0   \n",
       "             Moderate sunlight            35.3            67950.0   \n",
       "        3    Bright & sun drenched        35.3            67950.0   \n",
       "             Limited natural light        35.3            67950.0   \n",
       "        4    Moderate sunlight            35.3            67950.0   \n",
       "\n",
       "                                    median household income  \\\n",
       "zipcode beds sun_exposure_cat                                 \n",
       "11215   0    Bright & sun drenched                 156930.0   \n",
       "             Moderate sunlight                     156930.0   \n",
       "        1    Bright & sun drenched                 156930.0   \n",
       "             Moderate sunlight                     156930.0   \n",
       "        2    Limited natural light                 156930.0   \n",
       "        3    Limited natural light                 156930.0   \n",
       "        4    Moderate sunlight                     156930.0   \n",
       "11217   1    Limited natural light                 133269.0   \n",
       "        2    Limited natural light                 133269.0   \n",
       "             Moderate sunlight                     133269.0   \n",
       "11225   1    Limited natural light                  68542.0   \n",
       "        4    Limited natural light                  68542.0   \n",
       "11238   2    Bright & sun drenched                 114427.0   \n",
       "             Moderate sunlight                     114427.0   \n",
       "        3    Bright & sun drenched                 114427.0   \n",
       "             Limited natural light                 114427.0   \n",
       "        4    Moderate sunlight                     114427.0   \n",
       "\n",
       "                                    affordable_rent_single  \\\n",
       "zipcode beds sun_exposure_cat                                \n",
       "11215   0    Bright & sun drenched                2192.675   \n",
       "             Moderate sunlight                    2192.675   \n",
       "        1    Bright & sun drenched                2192.675   \n",
       "             Moderate sunlight                    2192.675   \n",
       "        2    Limited natural light                2192.675   \n",
       "        3    Limited natural light                2192.675   \n",
       "        4    Moderate sunlight                    2192.675   \n",
       "11217   1    Limited natural light                2145.325   \n",
       "        2    Limited natural light                2145.325   \n",
       "             Moderate sunlight                    2145.325   \n",
       "11225   1    Limited natural light                1037.425   \n",
       "        4    Limited natural light                1037.425   \n",
       "11238   2    Bright & sun drenched                1698.750   \n",
       "             Moderate sunlight                    1698.750   \n",
       "        3    Bright & sun drenched                1698.750   \n",
       "             Limited natural light                1698.750   \n",
       "        4    Moderate sunlight                    1698.750   \n",
       "\n",
       "                                    affordable_rent_couple  \\\n",
       "zipcode beds sun_exposure_cat                                \n",
       "11215   0    Bright & sun drenched                3923.250   \n",
       "             Moderate sunlight                    3923.250   \n",
       "        1    Bright & sun drenched                3923.250   \n",
       "             Moderate sunlight                    3923.250   \n",
       "        2    Limited natural light                3923.250   \n",
       "        3    Limited natural light                3923.250   \n",
       "        4    Moderate sunlight                    3923.250   \n",
       "11217   1    Limited natural light                3331.725   \n",
       "        2    Limited natural light                3331.725   \n",
       "             Moderate sunlight                    3331.725   \n",
       "11225   1    Limited natural light                1713.550   \n",
       "        4    Limited natural light                1713.550   \n",
       "11238   2    Bright & sun drenched                2860.675   \n",
       "             Moderate sunlight                    2860.675   \n",
       "        3    Bright & sun drenched                2860.675   \n",
       "             Limited natural light                2860.675   \n",
       "        4    Moderate sunlight                    2860.675   \n",
       "\n",
       "                                    is_affordable_individual  \\\n",
       "zipcode beds sun_exposure_cat                                  \n",
       "11215   0    Bright & sun drenched                       0.0   \n",
       "             Moderate sunlight                           0.0   \n",
       "        1    Bright & sun drenched                       0.0   \n",
       "             Moderate sunlight                           0.0   \n",
       "        2    Limited natural light                       0.0   \n",
       "        3    Limited natural light                       0.0   \n",
       "        4    Moderate sunlight                           0.0   \n",
       "11217   1    Limited natural light                       0.0   \n",
       "        2    Limited natural light                       0.0   \n",
       "             Moderate sunlight                           0.0   \n",
       "11225   1    Limited natural light                       0.0   \n",
       "        4    Limited natural light                       0.0   \n",
       "11238   2    Bright & sun drenched                       0.0   \n",
       "             Moderate sunlight                           0.0   \n",
       "        3    Bright & sun drenched                       0.0   \n",
       "             Limited natural light                       0.0   \n",
       "        4    Moderate sunlight                           0.0   \n",
       "\n",
       "                                    is_affordable_couple  \\\n",
       "zipcode beds sun_exposure_cat                              \n",
       "11215   0    Bright & sun drenched                   1.0   \n",
       "             Moderate sunlight                       1.0   \n",
       "        1    Bright & sun drenched                   1.0   \n",
       "             Moderate sunlight                       1.0   \n",
       "        2    Limited natural light                   0.0   \n",
       "        3    Limited natural light                   0.0   \n",
       "        4    Moderate sunlight                       0.0   \n",
       "11217   1    Limited natural light                   1.0   \n",
       "        2    Limited natural light                   0.0   \n",
       "             Moderate sunlight                       1.0   \n",
       "11225   1    Limited natural light                   0.0   \n",
       "        4    Limited natural light                   0.0   \n",
       "11238   2    Bright & sun drenched                   0.0   \n",
       "             Moderate sunlight                       0.0   \n",
       "        3    Bright & sun drenched                   0.0   \n",
       "             Limited natural light                   0.0   \n",
       "        4    Moderate sunlight                       0.0   \n",
       "\n",
       "                                    rent_difference_single  annualized_rent  \\\n",
       "zipcode beds sun_exposure_cat                                                 \n",
       "11215   0    Bright & sun drenched             1229.325000          41064.0   \n",
       "             Moderate sunlight                  757.325000          35400.0   \n",
       "        1    Bright & sun drenched              407.325000          31200.0   \n",
       "             Moderate sunlight                 1557.325000          45000.0   \n",
       "        2    Limited natural light             1807.325000          48000.0   \n",
       "        3    Limited natural light             2554.825000          56970.0   \n",
       "        4    Moderate sunlight                 3802.325000          71940.0   \n",
       "11217   1    Limited natural light              654.675000          33600.0   \n",
       "        2    Limited natural light             4136.341667          75380.0   \n",
       "             Moderate sunlight                  654.675000          33600.0   \n",
       "11225   1    Limited natural light              857.575000          22740.0   \n",
       "        4    Limited natural light             3757.575000          57540.0   \n",
       "11238   2    Bright & sun drenched             3001.250000          56400.0   \n",
       "             Moderate sunlight                 2201.250000          46800.0   \n",
       "        3    Bright & sun drenched             2151.250000          46200.0   \n",
       "             Limited natural light             3801.250000          66000.0   \n",
       "        4    Moderate sunlight                 4201.250000          70800.0   \n",
       "\n",
       "                                    indiv_affordability_to_rent_ratio  \\\n",
       "zipcode beds sun_exposure_cat                                           \n",
       "11215   0    Bright & sun drenched                           0.640758   \n",
       "             Moderate sunlight                               0.743280   \n",
       "        1    Bright & sun drenched                           0.843337   \n",
       "             Moderate sunlight                               0.584713   \n",
       "        2    Limited natural light                           0.548169   \n",
       "        3    Limited natural light                           0.463118   \n",
       "        4    Moderate sunlight                               0.365751   \n",
       "11217   1    Limited natural light                           0.766187   \n",
       "        2    Limited natural light                           0.349719   \n",
       "             Moderate sunlight                               0.766187   \n",
       "11225   1    Limited natural light                           0.547454   \n",
       "        4    Limited natural light                           0.216356   \n",
       "11238   2    Bright & sun drenched                           0.361436   \n",
       "             Moderate sunlight                               0.435577   \n",
       "        3    Bright & sun drenched                           0.441234   \n",
       "             Limited natural light                           0.308864   \n",
       "        4    Moderate sunlight                               0.287924   \n",
       "\n",
       "                                    rent_difference_couple  \\\n",
       "zipcode beds sun_exposure_cat                                \n",
       "11215   0    Bright & sun drenched             -501.250000   \n",
       "             Moderate sunlight                 -973.250000   \n",
       "        1    Bright & sun drenched            -1323.250000   \n",
       "             Moderate sunlight                 -173.250000   \n",
       "        2    Limited natural light               76.750000   \n",
       "        3    Limited natural light              824.250000   \n",
       "        4    Moderate sunlight                 2071.750000   \n",
       "11217   1    Limited natural light             -531.725000   \n",
       "        2    Limited natural light             2949.941667   \n",
       "             Moderate sunlight                 -531.725000   \n",
       "11225   1    Limited natural light              181.450000   \n",
       "        4    Limited natural light             3081.450000   \n",
       "11238   2    Bright & sun drenched             1839.325000   \n",
       "             Moderate sunlight                 1039.325000   \n",
       "        3    Bright & sun drenched              989.325000   \n",
       "             Limited natural light             2639.325000   \n",
       "        4    Moderate sunlight                 3039.325000   \n",
       "\n",
       "                                    coup_affordability_to_rent_ratio  \n",
       "zipcode beds sun_exposure_cat                                         \n",
       "11215   0    Bright & sun drenched                          1.146479  \n",
       "             Moderate sunlight                              1.329915  \n",
       "        1    Bright & sun drenched                          1.508942  \n",
       "             Moderate sunlight                              1.046200  \n",
       "        2    Limited natural light                          0.980812  \n",
       "        3    Limited natural light                          0.828634  \n",
       "        4    Moderate sunlight                              0.654420  \n",
       "11217   1    Limited natural light                          1.189902  \n",
       "        2    Limited natural light                          0.543119  \n",
       "             Moderate sunlight                              1.189902  \n",
       "11225   1    Limited natural light                          0.904248  \n",
       "        4    Limited natural light                          0.357362  \n",
       "11238   2    Bright & sun drenched                          0.608654  \n",
       "             Moderate sunlight                              0.733506  \n",
       "        3    Bright & sun drenched                          0.743032  \n",
       "             Limited natural light                          0.520123  \n",
       "        4    Moderate sunlight                              0.484860  "
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_filtered.groupby(['zipcode','beds','sun_exposure_cat']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "07ddabd7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['index', 'listing_path', 'zipcode', 'unit_number', 'building_class',\n",
       "       'beds', 'size', 'rent', 'sun_exposure_cat', 'sun_exposure', 'floor',\n",
       "       'median age', 'per capita income', 'median household income',\n",
       "       'affordable_rent_single', 'affordable_rent_couple',\n",
       "       'is_affordable_individual', 'is_affordable_couple',\n",
       "       'rent_difference_single', 'annualized_rent',\n",
       "       'indiv_affordability_to_rent_ratio', 'indiv_sun_exposure_icon',\n",
       "       'rent_difference_couple', 'coup_affordability_to_rent_ratio',\n",
       "       'coup_sun_exposure_icon'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_filtered.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "76ad2d22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['zipcode', 'living_arrangement', 'count', 'age_group'], dtype='object')"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_35_64.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "b908c4f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>...</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "      <th>indiv_sun_exposure_icon</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "      <th>coup_sun_exposure_icon</th>\n",
       "      <th>living_arrangement</th>\n",
       "      <th>count</th>\n",
       "      <th>age_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>lives alone</td>\n",
       "      <td>3958</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>householder with spouse</td>\n",
       "      <td>21217</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>householder with partner</td>\n",
       "      <td>2368</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>child of householder</td>\n",
       "      <td>672</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>other relatives</td>\n",
       "      <td>2357</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>181</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>householder with spouse</td>\n",
       "      <td>11089</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>householder with partner</td>\n",
       "      <td>1909</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>704</td>\n",
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       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>child of householder</td>\n",
       "      <td>1062</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>other relatives</td>\n",
       "      <td>2441</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>other nonrelatives</td>\n",
       "      <td>1544</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>186 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds  size  \\\n",
       "0      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "1      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "2      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "4      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "..     ...             ...     ...         ...            ...   ...   ...   \n",
       "181    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "182    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "183    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "184    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "185    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "\n",
       "     rent   sun_exposure_cat  \\\n",
       "0    3750  Moderate sunlight   \n",
       "1    3750  Moderate sunlight   \n",
       "2    3750  Moderate sunlight   \n",
       "3    3750  Moderate sunlight   \n",
       "4    3750  Moderate sunlight   \n",
       "..    ...                ...   \n",
       "181  3900  Moderate sunlight   \n",
       "182  3900  Moderate sunlight   \n",
       "183  3900  Moderate sunlight   \n",
       "184  3900  Moderate sunlight   \n",
       "185  3900  Moderate sunlight   \n",
       "\n",
       "                                          sun_exposure  ...  \\\n",
       "0    This apartment has moderate sunlight and the r...  ...   \n",
       "1    This apartment has moderate sunlight and the r...  ...   \n",
       "2    This apartment has moderate sunlight and the r...  ...   \n",
       "3    This apartment has moderate sunlight and the r...  ...   \n",
       "4    This apartment has moderate sunlight and the r...  ...   \n",
       "..                                                 ...  ...   \n",
       "181  This apartment has moderate sunlight and the r...  ...   \n",
       "182  This apartment has moderate sunlight and the r...  ...   \n",
       "183  This apartment has moderate sunlight and the r...  ...   \n",
       "184  This apartment has moderate sunlight and the r...  ...   \n",
       "185  This apartment has moderate sunlight and the r...  ...   \n",
       "\n",
       "    rent_difference_single  annualized_rent  \\\n",
       "0                 1557.325            45000   \n",
       "1                 1557.325            45000   \n",
       "2                 1557.325            45000   \n",
       "3                 1557.325            45000   \n",
       "4                 1557.325            45000   \n",
       "..                     ...              ...   \n",
       "181               2201.250            46800   \n",
       "182               2201.250            46800   \n",
       "183               2201.250            46800   \n",
       "184               2201.250            46800   \n",
       "185               2201.250            46800   \n",
       "\n",
       "     indiv_affordability_to_rent_ratio  indiv_sun_exposure_icon  \\\n",
       "0                             0.584713                        🌞   \n",
       "1                             0.584713                        🌞   \n",
       "2                             0.584713                        🌞   \n",
       "3                             0.584713                        🌞   \n",
       "4                             0.584713                        🌞   \n",
       "..                                 ...                      ...   \n",
       "181                           0.435577                        🌗   \n",
       "182                           0.435577                        🌗   \n",
       "183                           0.435577                        🌗   \n",
       "184                           0.435577                        🌗   \n",
       "185                           0.435577                        🌗   \n",
       "\n",
       "     rent_difference_couple  coup_affordability_to_rent_ratio  \\\n",
       "0                  -173.250                          1.046200   \n",
       "1                  -173.250                          1.046200   \n",
       "2                  -173.250                          1.046200   \n",
       "3                  -173.250                          1.046200   \n",
       "4                  -173.250                          1.046200   \n",
       "..                      ...                               ...   \n",
       "181                1039.325                          0.733506   \n",
       "182                1039.325                          0.733506   \n",
       "183                1039.325                          0.733506   \n",
       "184                1039.325                          0.733506   \n",
       "185                1039.325                          0.733506   \n",
       "\n",
       "     coup_sun_exposure_icon        living_arrangement  count  age_group  \n",
       "0                      1.0🌞               lives alone   3958      35-64  \n",
       "1                      1.0🌞   householder with spouse  21217      35-64  \n",
       "2                      1.0🌞  householder with partner   2368      35-64  \n",
       "3                      1.0🌞      child of householder    672      35-64  \n",
       "4                      1.0🌞           other relatives   2357      35-64  \n",
       "..                      ...                       ...    ...        ...  \n",
       "181                       🌞   householder with spouse  11089      35-64  \n",
       "182                       🌞  householder with partner   1909      35-64  \n",
       "183                       🌞      child of householder   1062      35-64  \n",
       "184                       🌞           other relatives   2441      35-64  \n",
       "185                       🌞        other nonrelatives   1544      35-64  \n",
       "\n",
       "[186 rows x 28 columns]"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge df_merged_filtered and df_35_64 on 'zipcode' with a left join\n",
    "df_merged_living = df_merged_filtered.merge(df_35_64, on='zipcode', how='left')\n",
    "df_merged_living"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "e5f8e1f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_merged_living.to_csv(\"merged_living.csv\", index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "09f75172",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/km/gmzkf_4n5qn6c84ksf3bzy0c0000gn/T/ipykernel_84608/3177684498.py:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  df_merged_living[df_merged_living['zipcode']=='11225'].groupby('living_arrangement').sum()\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>beds</th>\n",
       "      <th>size</th>\n",
       "      <th>rent</th>\n",
       "      <th>median age</th>\n",
       "      <th>per capita income</th>\n",
       "      <th>median household income</th>\n",
       "      <th>affordable_rent_single</th>\n",
       "      <th>affordable_rent_couple</th>\n",
       "      <th>is_affordable_individual</th>\n",
       "      <th>is_affordable_couple</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "      <th>count</th>\n",
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       "    <tr>\n",
       "      <th>living_arrangement</th>\n",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>child of householder</th>\n",
       "      <td>695</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>8585</td>\n",
       "      <td>108.3</td>\n",
       "      <td>124491</td>\n",
       "      <td>205626</td>\n",
       "      <td>3112.275</td>\n",
       "      <td>5140.65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5472.725</td>\n",
       "      <td>103020</td>\n",
       "      <td>1.311263</td>\n",
       "      <td>3444.35</td>\n",
       "      <td>2.165858</td>\n",
       "      <td>5445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>householder with partner</th>\n",
       "      <td>695</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>8585</td>\n",
       "      <td>108.3</td>\n",
       "      <td>124491</td>\n",
       "      <td>205626</td>\n",
       "      <td>3112.275</td>\n",
       "      <td>5140.65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5472.725</td>\n",
       "      <td>103020</td>\n",
       "      <td>1.311263</td>\n",
       "      <td>3444.35</td>\n",
       "      <td>2.165858</td>\n",
       "      <td>4803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>householder with spouse</th>\n",
       "      <td>695</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>8585</td>\n",
       "      <td>108.3</td>\n",
       "      <td>124491</td>\n",
       "      <td>205626</td>\n",
       "      <td>3112.275</td>\n",
       "      <td>5140.65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5472.725</td>\n",
       "      <td>103020</td>\n",
       "      <td>1.311263</td>\n",
       "      <td>3444.35</td>\n",
       "      <td>2.165858</td>\n",
       "      <td>23829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lives alone</th>\n",
       "      <td>695</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>8585</td>\n",
       "      <td>108.3</td>\n",
       "      <td>124491</td>\n",
       "      <td>205626</td>\n",
       "      <td>3112.275</td>\n",
       "      <td>5140.65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5472.725</td>\n",
       "      <td>103020</td>\n",
       "      <td>1.311263</td>\n",
       "      <td>3444.35</td>\n",
       "      <td>2.165858</td>\n",
       "      <td>12564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other nonrelatives</th>\n",
       "      <td>695</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>8585</td>\n",
       "      <td>108.3</td>\n",
       "      <td>124491</td>\n",
       "      <td>205626</td>\n",
       "      <td>3112.275</td>\n",
       "      <td>5140.65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5472.725</td>\n",
       "      <td>103020</td>\n",
       "      <td>1.311263</td>\n",
       "      <td>3444.35</td>\n",
       "      <td>2.165858</td>\n",
       "      <td>3873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other relatives</th>\n",
       "      <td>695</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>8585</td>\n",
       "      <td>108.3</td>\n",
       "      <td>124491</td>\n",
       "      <td>205626</td>\n",
       "      <td>3112.275</td>\n",
       "      <td>5140.65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5472.725</td>\n",
       "      <td>103020</td>\n",
       "      <td>1.311263</td>\n",
       "      <td>3444.35</td>\n",
       "      <td>2.165858</td>\n",
       "      <td>13074</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          index  beds    size  rent  median age  \\\n",
       "living_arrangement                                                \n",
       "child of householder        695   6.0  2000.0  8585       108.3   \n",
       "householder with partner    695   6.0  2000.0  8585       108.3   \n",
       "householder with spouse     695   6.0  2000.0  8585       108.3   \n",
       "lives alone                 695   6.0  2000.0  8585       108.3   \n",
       "other nonrelatives          695   6.0  2000.0  8585       108.3   \n",
       "other relatives             695   6.0  2000.0  8585       108.3   \n",
       "\n",
       "                          per capita income  median household income  \\\n",
       "living_arrangement                                                     \n",
       "child of householder                 124491                   205626   \n",
       "householder with partner             124491                   205626   \n",
       "householder with spouse              124491                   205626   \n",
       "lives alone                          124491                   205626   \n",
       "other nonrelatives                   124491                   205626   \n",
       "other relatives                      124491                   205626   \n",
       "\n",
       "                          affordable_rent_single  affordable_rent_couple  \\\n",
       "living_arrangement                                                         \n",
       "child of householder                    3112.275                 5140.65   \n",
       "householder with partner                3112.275                 5140.65   \n",
       "householder with spouse                 3112.275                 5140.65   \n",
       "lives alone                             3112.275                 5140.65   \n",
       "other nonrelatives                      3112.275                 5140.65   \n",
       "other relatives                         3112.275                 5140.65   \n",
       "\n",
       "                          is_affordable_individual  is_affordable_couple  \\\n",
       "living_arrangement                                                         \n",
       "child of householder                             0                     0   \n",
       "householder with partner                         0                     0   \n",
       "householder with spouse                          0                     0   \n",
       "lives alone                                      0                     0   \n",
       "other nonrelatives                               0                     0   \n",
       "other relatives                                  0                     0   \n",
       "\n",
       "                          rent_difference_single  annualized_rent  \\\n",
       "living_arrangement                                                  \n",
       "child of householder                    5472.725           103020   \n",
       "householder with partner                5472.725           103020   \n",
       "householder with spouse                 5472.725           103020   \n",
       "lives alone                             5472.725           103020   \n",
       "other nonrelatives                      5472.725           103020   \n",
       "other relatives                         5472.725           103020   \n",
       "\n",
       "                          indiv_affordability_to_rent_ratio  \\\n",
       "living_arrangement                                            \n",
       "child of householder                               1.311263   \n",
       "householder with partner                           1.311263   \n",
       "householder with spouse                            1.311263   \n",
       "lives alone                                        1.311263   \n",
       "other nonrelatives                                 1.311263   \n",
       "other relatives                                    1.311263   \n",
       "\n",
       "                          rent_difference_couple  \\\n",
       "living_arrangement                                 \n",
       "child of householder                     3444.35   \n",
       "householder with partner                 3444.35   \n",
       "householder with spouse                  3444.35   \n",
       "lives alone                              3444.35   \n",
       "other nonrelatives                       3444.35   \n",
       "other relatives                          3444.35   \n",
       "\n",
       "                          coup_affordability_to_rent_ratio  count  \n",
       "living_arrangement                                                 \n",
       "child of householder                              2.165858   5445  \n",
       "householder with partner                          2.165858   4803  \n",
       "householder with spouse                           2.165858  23829  \n",
       "lives alone                                       2.165858  12564  \n",
       "other nonrelatives                                2.165858   3873  \n",
       "other relatives                                   2.165858  13074  "
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_living[df_merged_living['zipcode']=='11225'].groupby('living_arrangement').sum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "81b93977",
   "metadata": {},
   "outputs": [],
   "source": [
    "arrangement_order = ['householder with spouse', 'lives alone', 'householder with partner', \n",
    "                     'child of householder', 'other relatives', 'other nonrelatives']\n",
    "\n",
    "df_merged_living['living_arrangement'] = pd.Categorical(df_merged_living['living_arrangement'], \n",
    "                                                 categories=arrangement_order, \n",
    "                                                 ordered=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "5c8f9c5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>listing_path</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>unit_number</th>\n",
       "      <th>building_class</th>\n",
       "      <th>beds</th>\n",
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       "      <th>rent</th>\n",
       "      <th>sun_exposure_cat</th>\n",
       "      <th>sun_exposure</th>\n",
       "      <th>...</th>\n",
       "      <th>rent_difference_single</th>\n",
       "      <th>annualized_rent</th>\n",
       "      <th>indiv_affordability_to_rent_ratio</th>\n",
       "      <th>indiv_sun_exposure_icon</th>\n",
       "      <th>rent_difference_couple</th>\n",
       "      <th>coup_affordability_to_rent_ratio</th>\n",
       "      <th>coup_sun_exposure_icon</th>\n",
       "      <th>living_arrangement</th>\n",
       "      <th>count</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
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       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>lives alone</td>\n",
       "      <td>3958</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>householder with spouse</td>\n",
       "      <td>21217</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>householder with partner</td>\n",
       "      <td>2368</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>child of householder</td>\n",
       "      <td>672</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>199</td>\n",
       "      <td>l-k5pmp1c6dcau</td>\n",
       "      <td>11215</td>\n",
       "      <td>3</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3750</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>1557.325</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.584713</td>\n",
       "      <td>🌞</td>\n",
       "      <td>-173.250</td>\n",
       "      <td>1.046200</td>\n",
       "      <td>1.0🌞</td>\n",
       "      <td>other relatives</td>\n",
       "      <td>2357</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>householder with spouse</td>\n",
       "      <td>11089</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>householder with partner</td>\n",
       "      <td>1909</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
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       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>child of householder</td>\n",
       "      <td>1062</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>other relatives</td>\n",
       "      <td>2441</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>704</td>\n",
       "      <td>l-1akn6ug8021r</td>\n",
       "      <td>11238</td>\n",
       "      <td>2L</td>\n",
       "      <td>rental unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3900</td>\n",
       "      <td>Moderate sunlight</td>\n",
       "      <td>This apartment has moderate sunlight and the r...</td>\n",
       "      <td>...</td>\n",
       "      <td>2201.250</td>\n",
       "      <td>46800</td>\n",
       "      <td>0.435577</td>\n",
       "      <td>🌗</td>\n",
       "      <td>1039.325</td>\n",
       "      <td>0.733506</td>\n",
       "      <td>🌞</td>\n",
       "      <td>other nonrelatives</td>\n",
       "      <td>1544</td>\n",
       "      <td>35-64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>186 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index    listing_path zipcode unit_number building_class  beds  size  \\\n",
       "0      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "1      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "2      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "3      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "4      199  l-k5pmp1c6dcau   11215           3    rental unit   1.0   NaN   \n",
       "..     ...             ...     ...         ...            ...   ...   ...   \n",
       "181    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "182    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "183    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "184    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "185    704  l-1akn6ug8021r   11238          2L    rental unit   2.0   NaN   \n",
       "\n",
       "     rent   sun_exposure_cat  \\\n",
       "0    3750  Moderate sunlight   \n",
       "1    3750  Moderate sunlight   \n",
       "2    3750  Moderate sunlight   \n",
       "3    3750  Moderate sunlight   \n",
       "4    3750  Moderate sunlight   \n",
       "..    ...                ...   \n",
       "181  3900  Moderate sunlight   \n",
       "182  3900  Moderate sunlight   \n",
       "183  3900  Moderate sunlight   \n",
       "184  3900  Moderate sunlight   \n",
       "185  3900  Moderate sunlight   \n",
       "\n",
       "                                          sun_exposure  ...  \\\n",
       "0    This apartment has moderate sunlight and the r...  ...   \n",
       "1    This apartment has moderate sunlight and the r...  ...   \n",
       "2    This apartment has moderate sunlight and the r...  ...   \n",
       "3    This apartment has moderate sunlight and the r...  ...   \n",
       "4    This apartment has moderate sunlight and the r...  ...   \n",
       "..                                                 ...  ...   \n",
       "181  This apartment has moderate sunlight and the r...  ...   \n",
       "182  This apartment has moderate sunlight and the r...  ...   \n",
       "183  This apartment has moderate sunlight and the r...  ...   \n",
       "184  This apartment has moderate sunlight and the r...  ...   \n",
       "185  This apartment has moderate sunlight and the r...  ...   \n",
       "\n",
       "    rent_difference_single  annualized_rent  \\\n",
       "0                 1557.325            45000   \n",
       "1                 1557.325            45000   \n",
       "2                 1557.325            45000   \n",
       "3                 1557.325            45000   \n",
       "4                 1557.325            45000   \n",
       "..                     ...              ...   \n",
       "181               2201.250            46800   \n",
       "182               2201.250            46800   \n",
       "183               2201.250            46800   \n",
       "184               2201.250            46800   \n",
       "185               2201.250            46800   \n",
       "\n",
       "     indiv_affordability_to_rent_ratio  indiv_sun_exposure_icon  \\\n",
       "0                             0.584713                        🌞   \n",
       "1                             0.584713                        🌞   \n",
       "2                             0.584713                        🌞   \n",
       "3                             0.584713                        🌞   \n",
       "4                             0.584713                        🌞   \n",
       "..                                 ...                      ...   \n",
       "181                           0.435577                        🌗   \n",
       "182                           0.435577                        🌗   \n",
       "183                           0.435577                        🌗   \n",
       "184                           0.435577                        🌗   \n",
       "185                           0.435577                        🌗   \n",
       "\n",
       "     rent_difference_couple  coup_affordability_to_rent_ratio  \\\n",
       "0                  -173.250                          1.046200   \n",
       "1                  -173.250                          1.046200   \n",
       "2                  -173.250                          1.046200   \n",
       "3                  -173.250                          1.046200   \n",
       "4                  -173.250                          1.046200   \n",
       "..                      ...                               ...   \n",
       "181                1039.325                          0.733506   \n",
       "182                1039.325                          0.733506   \n",
       "183                1039.325                          0.733506   \n",
       "184                1039.325                          0.733506   \n",
       "185                1039.325                          0.733506   \n",
       "\n",
       "     coup_sun_exposure_icon        living_arrangement  count  age_group  \n",
       "0                      1.0🌞               lives alone   3958      35-64  \n",
       "1                      1.0🌞   householder with spouse  21217      35-64  \n",
       "2                      1.0🌞  householder with partner   2368      35-64  \n",
       "3                      1.0🌞      child of householder    672      35-64  \n",
       "4                      1.0🌞           other relatives   2357      35-64  \n",
       "..                      ...                       ...    ...        ...  \n",
       "181                       🌞   householder with spouse  11089      35-64  \n",
       "182                       🌞  householder with partner   1909      35-64  \n",
       "183                       🌞      child of householder   1062      35-64  \n",
       "184                       🌞           other relatives   2441      35-64  \n",
       "185                       🌞        other nonrelatives   1544      35-64  \n",
       "\n",
       "[186 rows x 28 columns]"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged_living"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "85f22cfd",
   "metadata": {},
   "outputs": [],
   "source": [
    "(df_merged_living[df_merged_living['zipcode']=='11217'][['living_arrangement', 'count']].groupby('living_arrangement').sum()).to_csv('11217.csv', index = True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1df7ac87",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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