Cellar Defenders_Vivino_Reds_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c38edcc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "332d5faa",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_red_wine = pd.read_csv('vivino_red_wine_072121.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "58bac6cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cellar_defenders = pd.read_csv('cellar defender_reds.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a6a1bfb2",
   "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>winery</th>\n",
       "      <th>wine_type</th>\n",
       "      <th>city</th>\n",
       "      <th>country</th>\n",
       "      <th>wine_name</th>\n",
       "      <th>year</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>overall_rating_count</th>\n",
       "      <th>price</th>\n",
       "      <th>light_bold</th>\n",
       "      <th>smooth_tannic</th>\n",
       "      <th>dry_sweet</th>\n",
       "      <th>soft_acidic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ch?eau Mouton Rothschild</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Pauillac</td>\n",
       "      <td>France</td>\n",
       "      <td>Pauillac (Premier Grand Cru Class?)</td>\n",
       "      <td>1967</td>\n",
       "      <td>4.4</td>\n",
       "      <td>208</td>\n",
       "      <td>4499.97</td>\n",
       "      <td>66.8377</td>\n",
       "      <td>68.8474</td>\n",
       "      <td>7.95159</td>\n",
       "      <td>67.8875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Dujac Fils et P?e</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Gevrey-Chambertin</td>\n",
       "      <td>France</td>\n",
       "      <td>Gevrey-Chambertin</td>\n",
       "      <td>2013</td>\n",
       "      <td>3.8</td>\n",
       "      <td>81</td>\n",
       "      <td>3262.50</td>\n",
       "      <td>38.4608</td>\n",
       "      <td>27.7903</td>\n",
       "      <td>1.16921</td>\n",
       "      <td>67.7236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ch?eau Pichon Longueville Comtesse de Lalande</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Pauillac</td>\n",
       "      <td>France</td>\n",
       "      <td>Pauillac (Grand Cru Class?)</td>\n",
       "      <td>1985</td>\n",
       "      <td>4.5</td>\n",
       "      <td>598</td>\n",
       "      <td>1799.99</td>\n",
       "      <td>66.6542</td>\n",
       "      <td>68.1138</td>\n",
       "      <td>4.89307</td>\n",
       "      <td>69.4560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ch?eau Pichon Longueville Comtesse de Lalande</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Pauillac</td>\n",
       "      <td>France</td>\n",
       "      <td>Pauillac (Grand Cru Class?)</td>\n",
       "      <td>1986</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1064</td>\n",
       "      <td>1799.99</td>\n",
       "      <td>66.6538</td>\n",
       "      <td>68.1144</td>\n",
       "      <td>4.89312</td>\n",
       "      <td>69.4560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ch?eau Pichon Longueville Comtesse de Lalande</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Pauillac</td>\n",
       "      <td>France</td>\n",
       "      <td>Pauillac (Grand Cru Class?)</td>\n",
       "      <td>1967</td>\n",
       "      <td>4.4</td>\n",
       "      <td>32</td>\n",
       "      <td>1799.99</td>\n",
       "      <td>66.6538</td>\n",
       "      <td>68.1144</td>\n",
       "      <td>4.89312</td>\n",
       "      <td>69.4560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          winery wine_type               city  \\\n",
       "0                       Ch?eau Mouton Rothschild  Red wine           Pauillac   \n",
       "1                              Dujac Fils et P?e  Red wine  Gevrey-Chambertin   \n",
       "2  Ch?eau Pichon Longueville Comtesse de Lalande  Red wine           Pauillac   \n",
       "3  Ch?eau Pichon Longueville Comtesse de Lalande  Red wine           Pauillac   \n",
       "4  Ch?eau Pichon Longueville Comtesse de Lalande  Red wine           Pauillac   \n",
       "\n",
       "  country                            wine_name  year  overall_rating  \\\n",
       "0  France  Pauillac (Premier Grand Cru Class?)  1967             4.4   \n",
       "1  France                    Gevrey-Chambertin  2013             3.8   \n",
       "2  France          Pauillac (Grand Cru Class?)  1985             4.5   \n",
       "3  France          Pauillac (Grand Cru Class?)  1986             4.5   \n",
       "4  France          Pauillac (Grand Cru Class?)  1967             4.4   \n",
       "\n",
       "   overall_rating_count    price  light_bold  smooth_tannic  dry_sweet  \\\n",
       "0                   208  4499.97     66.8377        68.8474    7.95159   \n",
       "1                    81  3262.50     38.4608        27.7903    1.16921   \n",
       "2                   598  1799.99     66.6542        68.1138    4.89307   \n",
       "3                  1064  1799.99     66.6538        68.1144    4.89312   \n",
       "4                    32  1799.99     66.6538        68.1144    4.89312   \n",
       "\n",
       "   soft_acidic  \n",
       "0      67.8875  \n",
       "1      67.7236  \n",
       "2      69.4560  \n",
       "3      69.4560  \n",
       "4      69.4560  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_red_wine.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6d447a68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(44933, 13)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_red_wine.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f023ed96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "winery                   object\n",
       "wine_type                object\n",
       "city                     object\n",
       "country                  object\n",
       "wine_name                object\n",
       "year                      int64\n",
       "overall_rating          float64\n",
       "overall_rating_count      int64\n",
       "price                   float64\n",
       "light_bold              float64\n",
       "smooth_tannic           float64\n",
       "dry_sweet               float64\n",
       "soft_acidic             float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_red_wine.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2a3e439a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 44933 entries, 0 to 44932\n",
      "Data columns (total 13 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   winery                44932 non-null  object \n",
      " 1   wine_type             44932 non-null  object \n",
      " 2   city                  44928 non-null  object \n",
      " 3   country               44928 non-null  object \n",
      " 4   wine_name             44927 non-null  object \n",
      " 5   year                  44933 non-null  int64  \n",
      " 6   overall_rating        44933 non-null  float64\n",
      " 7   overall_rating_count  44933 non-null  int64  \n",
      " 8   price                 44933 non-null  float64\n",
      " 9   light_bold            44933 non-null  float64\n",
      " 10  smooth_tannic         44933 non-null  float64\n",
      " 11  dry_sweet             44933 non-null  float64\n",
      " 12  soft_acidic           44933 non-null  float64\n",
      "dtypes: float64(6), int64(2), object(5)\n",
      "memory usage: 4.5+ MB\n"
     ]
    }
   ],
   "source": [
    "df_red_wine.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fbd36448",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               year  overall_rating  overall_rating_count         price  \\\n",
      "count  44933.000000    44933.000000          44933.000000  44933.000000   \n",
      "mean    2009.791445        3.998122            426.470345     75.365922   \n",
      "std       86.163109        0.338457           1242.434541    108.794727   \n",
      "min       -1.000000       -1.000000             -1.000000     -1.000000   \n",
      "25%     2012.000000        3.800000             56.000000     18.990000   \n",
      "50%     2015.000000        4.000000            129.000000     40.000000   \n",
      "75%     2017.000000        4.200000            361.000000     82.990000   \n",
      "max     2020.000000        4.900000         134439.000000   4499.970000   \n",
      "\n",
      "         light_bold  smooth_tannic    dry_sweet   soft_acidic  \n",
      "count  44933.000000   44933.000000  44933.00000  44933.000000  \n",
      "mean      57.657922      41.819262      7.07189     48.690204  \n",
      "std       22.172399      19.220620      7.65284     19.457715  \n",
      "min       -1.000000      -1.000000     -1.00000     -1.000000  \n",
      "25%       44.732400      27.993300      1.74544     41.200100  \n",
      "50%       62.650900      46.465100      5.32136     50.815800  \n",
      "75%       77.118900      54.253300      9.68328     61.890800  \n",
      "max       80.000000      80.000000     55.52860     80.000000  \n"
     ]
    }
   ],
   "source": [
    "print(df_red_wine.describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a2ef7dc4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "winery                  1\n",
      "wine_type               1\n",
      "city                    5\n",
      "country                 5\n",
      "wine_name               6\n",
      "year                    0\n",
      "overall_rating          0\n",
      "overall_rating_count    0\n",
      "price                   0\n",
      "light_bold              0\n",
      "smooth_tannic           0\n",
      "dry_sweet               0\n",
      "soft_acidic             0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df_red_wine.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "eb12520a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_red_wine= df_red_wine.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f16a3ea0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_red_wine = df_red_wine[df_red_wine['price'] >= 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2deffdd3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_red_wine['price'].plot(kind='hist', edgecolor='black', bins=10)\n",
    "plt.title('Distribution of Wine Prices')\n",
    "plt.xlabel('Price')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9ed3ab4c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame._add_numeric_operations.<locals>.max of 0        4499.97\n",
       "1        3262.50\n",
       "2        1799.99\n",
       "3        1799.99\n",
       "4        1799.99\n",
       "          ...   \n",
       "44849       3.99\n",
       "44850       3.99\n",
       "44851       3.99\n",
       "44852       3.75\n",
       "44853       1.00\n",
       "Name: price, Length: 44846, dtype: float64>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_red_wine.price.max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7b9b4ffe",
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_prices = df_red_wine[df_red_wine['price'] > 0]['price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d0717a52",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filtered_prices.plot(kind='hist', bins=100, edgecolor='black')\n",
    "plt.xlabel('Price')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of Wine Prices')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1a829859",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))  # Set the figure size\n",
    "sns.boxplot(data=df_red_wine, x='country', y='price')\n",
    "plt.xlabel('Country')\n",
    "plt.ylabel('Price')\n",
    "plt.title('Distribution of Wine Prices by Country')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "514c3829",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['winery', 'wine_type', 'city', 'country', 'wine_name', 'year',\n",
       "       'overall_rating', 'overall_rating_count', 'price', 'light_bold',\n",
       "       'smooth_tannic', 'dry_sweet', 'soft_acidic'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_red_wine.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "30c65e79",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x2000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 20))  # Setting the figure size\n",
    "boxplot = df_red_wine.boxplot(column=['price'], by='country', grid=False, vert=False)\n",
    "plt.xlabel('Price')\n",
    "plt.ylabel('Country')\n",
    "plt.title('Distribution of Wine Prices by Country')\n",
    "plt.suptitle('')  # This line is used to clear the automatically generated title\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0f6e874b",
   "metadata": {},
   "outputs": [],
   "source": [
    "boxplot_stats = df_red_wine.groupby('country')['price'].describe()[['min', '25%', '50%', '75%', 'max']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "eccdc454",
   "metadata": {},
   "outputs": [],
   "source": [
    "boxplot_stats.to_csv('boxplot_country_prices_stats.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6eceb6d7",
   "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>winery</th>\n",
       "      <th>wine_type</th>\n",
       "      <th>city</th>\n",
       "      <th>country</th>\n",
       "      <th>wine_name</th>\n",
       "      <th>year</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>overall_rating_count</th>\n",
       "      <th>price</th>\n",
       "      <th>light_bold</th>\n",
       "      <th>smooth_tannic</th>\n",
       "      <th>dry_sweet</th>\n",
       "      <th>soft_acidic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Abreu</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>United States</td>\n",
       "      <td>Thorevilos Cabernet Sauvignon</td>\n",
       "      <td>2006</td>\n",
       "      <td>4.9</td>\n",
       "      <td>25</td>\n",
       "      <td>1399.99</td>\n",
       "      <td>80.0000</td>\n",
       "      <td>62.6407</td>\n",
       "      <td>8.52482</td>\n",
       "      <td>52.1362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>Bond</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>United States</td>\n",
       "      <td>Melbury</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.9</td>\n",
       "      <td>34</td>\n",
       "      <td>764.99</td>\n",
       "      <td>80.0000</td>\n",
       "      <td>54.2035</td>\n",
       "      <td>13.83380</td>\n",
       "      <td>55.8395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Sine Qua Non</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Sta. Rita Hills</td>\n",
       "      <td>United States</td>\n",
       "      <td>Rattrapante Grenache</td>\n",
       "      <td>2012</td>\n",
       "      <td>4.9</td>\n",
       "      <td>69</td>\n",
       "      <td>699.95</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.00000</td>\n",
       "      <td>-1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>Peter Michael</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Sonoma Coast</td>\n",
       "      <td>United States</td>\n",
       "      <td>Clos du Ciel Pinot Noir</td>\n",
       "      <td>2014</td>\n",
       "      <td>4.9</td>\n",
       "      <td>29</td>\n",
       "      <td>669.97</td>\n",
       "      <td>47.2299</td>\n",
       "      <td>20.9096</td>\n",
       "      <td>4.04078</td>\n",
       "      <td>52.2205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>679</th>\n",
       "      <td>Realm</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>United States</td>\n",
       "      <td>Cabernet Sauvignon Beckstoffer To Kalon Vineyard</td>\n",
       "      <td>2015</td>\n",
       "      <td>4.9</td>\n",
       "      <td>34</td>\n",
       "      <td>429.00</td>\n",
       "      <td>80.0000</td>\n",
       "      <td>52.7127</td>\n",
       "      <td>5.30010</td>\n",
       "      <td>51.3659</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42764</th>\n",
       "      <td>Ariel</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>United States</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>2017</td>\n",
       "      <td>2.5</td>\n",
       "      <td>31</td>\n",
       "      <td>10.99</td>\n",
       "      <td>58.9665</td>\n",
       "      <td>42.8184</td>\n",
       "      <td>30.75980</td>\n",
       "      <td>44.2779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43660</th>\n",
       "      <td>Mother's Choice</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>California</td>\n",
       "      <td>United States</td>\n",
       "      <td>Red Blend</td>\n",
       "      <td>2018</td>\n",
       "      <td>2.5</td>\n",
       "      <td>47</td>\n",
       "      <td>9.99</td>\n",
       "      <td>80.0000</td>\n",
       "      <td>56.5732</td>\n",
       "      <td>6.33011</td>\n",
       "      <td>62.7790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44158</th>\n",
       "      <td>Our Daily</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>California</td>\n",
       "      <td>United States</td>\n",
       "      <td>Red Blend</td>\n",
       "      <td>2013</td>\n",
       "      <td>2.4</td>\n",
       "      <td>231</td>\n",
       "      <td>8.99</td>\n",
       "      <td>79.4697</td>\n",
       "      <td>54.8779</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>63.4142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27734</th>\n",
       "      <td>Pierre Chavin</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Languedoc</td>\n",
       "      <td>France</td>\n",
       "      <td>Le Petit ?oil? Cabernet Sauvignon</td>\n",
       "      <td>-1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>31</td>\n",
       "      <td>26.00</td>\n",
       "      <td>25.7115</td>\n",
       "      <td>25.7115</td>\n",
       "      <td>23.05770</td>\n",
       "      <td>30.3846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44159</th>\n",
       "      <td>Ariel</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>United States</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>2014</td>\n",
       "      <td>2.0</td>\n",
       "      <td>28</td>\n",
       "      <td>8.99</td>\n",
       "      <td>58.9665</td>\n",
       "      <td>42.8184</td>\n",
       "      <td>30.75980</td>\n",
       "      <td>44.2779</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>44846 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                winery wine_type             city        country  \\\n",
       "16               Abreu  Red wine      Napa Valley  United States   \n",
       "110               Bond  Red wine      Napa Valley  United States   \n",
       "170       Sine Qua Non  Red wine  Sta. Rita Hills  United States   \n",
       "208      Peter Michael  Red wine     Sonoma Coast  United States   \n",
       "679              Realm  Red wine      Napa Valley  United States   \n",
       "...                ...       ...              ...            ...   \n",
       "42764            Ariel  Red wine      Napa Valley  United States   \n",
       "43660  Mother's Choice  Red wine       California  United States   \n",
       "44158        Our Daily  Red wine       California  United States   \n",
       "27734    Pierre Chavin  Red wine        Languedoc         France   \n",
       "44159            Ariel  Red wine      Napa Valley  United States   \n",
       "\n",
       "                                              wine_name  year  overall_rating  \\\n",
       "16                        Thorevilos Cabernet Sauvignon  2006             4.9   \n",
       "110                                             Melbury  2014             4.9   \n",
       "170                                Rattrapante Grenache  2012             4.9   \n",
       "208                             Clos du Ciel Pinot Noir  2014             4.9   \n",
       "679    Cabernet Sauvignon Beckstoffer To Kalon Vineyard  2015             4.9   \n",
       "...                                                 ...   ...             ...   \n",
       "42764                                Cabernet Sauvignon  2017             2.5   \n",
       "43660                                         Red Blend  2018             2.5   \n",
       "44158                                         Red Blend  2013             2.4   \n",
       "27734                 Le Petit ?oil? Cabernet Sauvignon    -1             2.2   \n",
       "44159                                Cabernet Sauvignon  2014             2.0   \n",
       "\n",
       "       overall_rating_count    price  light_bold  smooth_tannic  dry_sweet  \\\n",
       "16                       25  1399.99     80.0000        62.6407    8.52482   \n",
       "110                      34   764.99     80.0000        54.2035   13.83380   \n",
       "170                      69   699.95     -1.0000        -1.0000   -1.00000   \n",
       "208                      29   669.97     47.2299        20.9096    4.04078   \n",
       "679                      34   429.00     80.0000        52.7127    5.30010   \n",
       "...                     ...      ...         ...            ...        ...   \n",
       "42764                    31    10.99     58.9665        42.8184   30.75980   \n",
       "43660                    47     9.99     80.0000        56.5732    6.33011   \n",
       "44158                   231     8.99     79.4697        54.8779    0.00000   \n",
       "27734                    31    26.00     25.7115        25.7115   23.05770   \n",
       "44159                    28     8.99     58.9665        42.8184   30.75980   \n",
       "\n",
       "       soft_acidic  \n",
       "16         52.1362  \n",
       "110        55.8395  \n",
       "170        -1.0000  \n",
       "208        52.2205  \n",
       "679        51.3659  \n",
       "...            ...  \n",
       "42764      44.2779  \n",
       "43660      62.7790  \n",
       "44158      63.4142  \n",
       "27734      30.3846  \n",
       "44159      44.2779  \n",
       "\n",
       "[44846 rows x 13 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_red_wine.sort_values(by=['overall_rating','price'], ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "49be50b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "country\n",
      "Argentina                           30.831254\n",
      "Armenia                             39.983333\n",
      "Australia                           57.667517\n",
      "Austria                             31.915854\n",
      "Bolivia                             18.740000\n",
      "Brazil                              83.660000\n",
      "Bulgaria                            17.902273\n",
      "Canada                              34.078667\n",
      "Chile                               27.237452\n",
      "Croatia                             31.335000\n",
      "Cyprus                              17.430000\n",
      "Czech Republic                      25.740000\n",
      "France                             105.235823\n",
      "Georgia                             22.088000\n",
      "Germany                             34.439322\n",
      "Greece                              22.847282\n",
      "Hungary                             23.522500\n",
      "India                               13.990000\n",
      "Israel                              30.644110\n",
      "Italy                               69.668543\n",
      "Lebanon                             54.502222\n",
      "Macedonia                           22.051250\n",
      "Mexico                              29.427500\n",
      "Moldova                             29.740000\n",
      "Montenegro                          15.990000\n",
      "Morocco                             17.990000\n",
      "New Zealand                         27.004932\n",
      "Palestinian Territory, Occupied     37.214444\n",
      "Peru                                12.815000\n",
      "Portugal                            30.161619\n",
      "Romania                             24.485000\n",
      "Slovakia                            29.000000\n",
      "Slovenia                            17.904444\n",
      "South Africa                        31.288352\n",
      "Spain                               48.044276\n",
      "Switzerland                         91.782222\n",
      "Turkey                              23.851429\n",
      "United States                       79.571472\n",
      "Uruguay                             24.865000\n",
      "Name: price, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "country_avg_price = df_red_wine.groupby('country')['price'].mean()\n",
    "print(country_avg_price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8eb11418",
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped_by_country = df_red_wine.groupby('country')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6f5c14b2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country\n",
       "United States                      14140\n",
       "France                             11675\n",
       "Italy                               9268\n",
       "Spain                               3227\n",
       "Argentina                           1826\n",
       "Australia                           1309\n",
       "Portugal                            1087\n",
       "Chile                               1048\n",
       "South Africa                         437\n",
       "Israel                               163\n",
       "New Zealand                          146\n",
       "Austria                              123\n",
       "Greece                               103\n",
       "Germany                               59\n",
       "Mexico                                32\n",
       "Lebanon                               27\n",
       "Uruguay                               26\n",
       "Bulgaria                              22\n",
       "Hungary                               16\n",
       "Canada                                15\n",
       "Georgia                               10\n",
       "Slovenia                               9\n",
       "Switzerland                            9\n",
       "Palestinian Territory, Occupied        9\n",
       "Croatia                                8\n",
       "Moldova                                8\n",
       "Macedonia                              8\n",
       "Turkey                                 7\n",
       "Armenia                                6\n",
       "Brazil                                 6\n",
       "Peru                                   4\n",
       "India                                  3\n",
       "Romania                                2\n",
       "Czech Republic                         2\n",
       "Bolivia                                2\n",
       "Slovakia                               1\n",
       "Morocco                                1\n",
       "Cyprus                                 1\n",
       "Montenegro                             1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_red_wine.country.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6db8ac1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "country_to_region = {\n",
    "    # Old World\n",
    "    'France': 'Old World',\n",
    "    'Italy': 'Old World',\n",
    "    'Spain': 'Old World',\n",
    "    'Portugal': 'Old World',\n",
    "    'Germany': 'Old World',\n",
    "    'Austria': 'Old World',\n",
    "    'Greece': 'Old World',\n",
    "    'Hungary': 'Old World',\n",
    "    'Bulgaria': 'Old World',\n",
    "    'Moldova': 'Old World',\n",
    "    'Macedonia': 'Old World',\n",
    "    'Romania': 'Old World',\n",
    "    'Czech Republic': 'Old World',\n",
    "    'Slovakia': 'Old World',\n",
    "    'Slovenia': 'Old World',\n",
    "    'Switzerland': 'Old World',\n",
    "    'Cyprus': 'Old World',\n",
    "    'Croatia': 'Old World',\n",
    "\n",
    "    # New World\n",
    "    'United States': 'New World',\n",
    "    'Argentina': 'New World',\n",
    "    'Australia': 'New World',\n",
    "    'Chile': 'New World',\n",
    "    'South Africa': 'New World',\n",
    "    'New Zealand': 'New World',\n",
    "    'Canada': 'New World',\n",
    "    'Mexico': 'New World',\n",
    "    'Brazil': 'New World',\n",
    "    'Uruguay': 'New World',\n",
    "    'Bolivia': 'New World',\n",
    "    'Peru': 'New World',\n",
    "\n",
    "    # Middle East and Others\n",
    "    'Israel': 'Middle East and Others',\n",
    "    'Lebanon': 'Middle East and Others',\n",
    "    'Turkey': 'Middle East and Others',\n",
    "    'Georgia': 'Middle East and Others',\n",
    "    'Armenia': 'Middle East and Others',\n",
    "    'Palestinian Territory, Occupied': 'Middle East and Others',\n",
    "    'Montenegro': 'Middle East and Others',\n",
    "    'India': 'Middle East and Others',\n",
    "    'Morocco': 'Middle East and Others'\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ba2b358e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_red_wine['region'] = df_red_wine['country'].map(country_to_region)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "291f91ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_data = df_red_wine.merge(df_cellar_defenders, on=['winery', 'wine_name'], how='left', indicator=True)\n",
    "\n",
    "merged_data['is_cellar_defender'] = merged_data['_merge'] == 'both'\n",
    "\n",
    "merged_data.drop(columns=['_merge'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "042d756f",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_data.to_csv('wine_data_with_cellar_defenders.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "4660ebef",
   "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>winery</th>\n",
       "      <th>wine_type</th>\n",
       "      <th>city</th>\n",
       "      <th>country</th>\n",
       "      <th>wine_name</th>\n",
       "      <th>year</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>overall_rating_count</th>\n",
       "      <th>price</th>\n",
       "      <th>light_bold</th>\n",
       "      <th>smooth_tannic</th>\n",
       "      <th>dry_sweet</th>\n",
       "      <th>soft_acidic</th>\n",
       "      <th>region</th>\n",
       "      <th>Note</th>\n",
       "      <th>is_cellar_defender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10117</th>\n",
       "      <td>Aldo Conterno</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Il Favot Langhe Nebbiolo</td>\n",
       "      <td>2011</td>\n",
       "      <td>4.3</td>\n",
       "      <td>156</td>\n",
       "      <td>90.00</td>\n",
       "      <td>62.2292</td>\n",
       "      <td>77.9018</td>\n",
       "      <td>4.16623</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10118</th>\n",
       "      <td>Aldo Conterno</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Il Favot Langhe Nebbiolo</td>\n",
       "      <td>2011</td>\n",
       "      <td>4.3</td>\n",
       "      <td>156</td>\n",
       "      <td>90.00</td>\n",
       "      <td>62.2292</td>\n",
       "      <td>77.9018</td>\n",
       "      <td>4.16623</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10119</th>\n",
       "      <td>Aldo Conterno</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Il Favot Langhe Nebbiolo</td>\n",
       "      <td>2011</td>\n",
       "      <td>4.3</td>\n",
       "      <td>156</td>\n",
       "      <td>90.00</td>\n",
       "      <td>62.2292</td>\n",
       "      <td>77.9018</td>\n",
       "      <td>4.16623</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10120</th>\n",
       "      <td>Aldo Conterno</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Il Favot Langhe Nebbiolo</td>\n",
       "      <td>2011</td>\n",
       "      <td>4.3</td>\n",
       "      <td>156</td>\n",
       "      <td>90.00</td>\n",
       "      <td>62.2292</td>\n",
       "      <td>77.9018</td>\n",
       "      <td>4.16623</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10121</th>\n",
       "      <td>Aldo Conterno</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Il Favot Langhe Nebbiolo</td>\n",
       "      <td>2011</td>\n",
       "      <td>4.3</td>\n",
       "      <td>156</td>\n",
       "      <td>90.00</td>\n",
       "      <td>62.2292</td>\n",
       "      <td>77.9018</td>\n",
       "      <td>4.16623</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36688</th>\n",
       "      <td>Tintero Elvio</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Langhe Nebbiolo</td>\n",
       "      <td>2018</td>\n",
       "      <td>3.8</td>\n",
       "      <td>179</td>\n",
       "      <td>15.99</td>\n",
       "      <td>55.7913</td>\n",
       "      <td>80.0000</td>\n",
       "      <td>1.33149</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36937</th>\n",
       "      <td>Jean-Maurice Raffault</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Chinon</td>\n",
       "      <td>France</td>\n",
       "      <td>Chinon Les Picasses</td>\n",
       "      <td>2017</td>\n",
       "      <td>3.7</td>\n",
       "      <td>60</td>\n",
       "      <td>15.99</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.00000</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36938</th>\n",
       "      <td>Jean-Maurice Raffault</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Chinon</td>\n",
       "      <td>France</td>\n",
       "      <td>Chinon Les Picasses</td>\n",
       "      <td>2017</td>\n",
       "      <td>3.7</td>\n",
       "      <td>60</td>\n",
       "      <td>15.99</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.00000</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37473</th>\n",
       "      <td>Domaine Guion</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Bourgueil</td>\n",
       "      <td>France</td>\n",
       "      <td>Cuv? Domaine Bourgueil</td>\n",
       "      <td>2018</td>\n",
       "      <td>3.5</td>\n",
       "      <td>72</td>\n",
       "      <td>15.49</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.00000</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39497</th>\n",
       "      <td>Nada Giuseppe</td>\n",
       "      <td>Red wine</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Langhe Nebbiolo</td>\n",
       "      <td>2019</td>\n",
       "      <td>3.7</td>\n",
       "      <td>44</td>\n",
       "      <td>13.99</td>\n",
       "      <td>56.4105</td>\n",
       "      <td>80.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Old World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>257 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      winery wine_type       city country  \\\n",
       "10117          Aldo Conterno  Red wine     Langhe   Italy   \n",
       "10118          Aldo Conterno  Red wine     Langhe   Italy   \n",
       "10119          Aldo Conterno  Red wine     Langhe   Italy   \n",
       "10120          Aldo Conterno  Red wine     Langhe   Italy   \n",
       "10121          Aldo Conterno  Red wine     Langhe   Italy   \n",
       "...                      ...       ...        ...     ...   \n",
       "36688          Tintero Elvio  Red wine     Langhe   Italy   \n",
       "36937  Jean-Maurice Raffault  Red wine     Chinon  France   \n",
       "36938  Jean-Maurice Raffault  Red wine     Chinon  France   \n",
       "37473          Domaine Guion  Red wine  Bourgueil  France   \n",
       "39497          Nada Giuseppe  Red wine     Langhe   Italy   \n",
       "\n",
       "                      wine_name  year  overall_rating  overall_rating_count  \\\n",
       "10117  Il Favot Langhe Nebbiolo  2011             4.3                   156   \n",
       "10118  Il Favot Langhe Nebbiolo  2011             4.3                   156   \n",
       "10119  Il Favot Langhe Nebbiolo  2011             4.3                   156   \n",
       "10120  Il Favot Langhe Nebbiolo  2011             4.3                   156   \n",
       "10121  Il Favot Langhe Nebbiolo  2011             4.3                   156   \n",
       "...                         ...   ...             ...                   ...   \n",
       "36688           Langhe Nebbiolo  2018             3.8                   179   \n",
       "36937       Chinon Les Picasses  2017             3.7                    60   \n",
       "36938       Chinon Les Picasses  2017             3.7                    60   \n",
       "37473    Cuv? Domaine Bourgueil  2018             3.5                    72   \n",
       "39497           Langhe Nebbiolo  2019             3.7                    44   \n",
       "\n",
       "       price  light_bold  smooth_tannic  dry_sweet  soft_acidic     region  \\\n",
       "10117  90.00     62.2292        77.9018    4.16623         80.0  Old World   \n",
       "10118  90.00     62.2292        77.9018    4.16623         80.0  Old World   \n",
       "10119  90.00     62.2292        77.9018    4.16623         80.0  Old World   \n",
       "10120  90.00     62.2292        77.9018    4.16623         80.0  Old World   \n",
       "10121  90.00     62.2292        77.9018    4.16623         80.0  Old World   \n",
       "...      ...         ...            ...        ...          ...        ...   \n",
       "36688  15.99     55.7913        80.0000    1.33149         80.0  Old World   \n",
       "36937  15.99     -1.0000        -1.0000   -1.00000         -1.0  Old World   \n",
       "36938  15.99     -1.0000        -1.0000   -1.00000         -1.0  Old World   \n",
       "37473  15.49     -1.0000        -1.0000   -1.00000         -1.0  Old World   \n",
       "39497  13.99     56.4105        80.0000    0.00000         80.0  Old World   \n",
       "\n",
       "      Note  is_cellar_defender  \n",
       "10117  NaN                True  \n",
       "10118  NaN                True  \n",
       "10119  NaN                True  \n",
       "10120  NaN                True  \n",
       "10121  NaN                True  \n",
       "...    ...                 ...  \n",
       "36688  NaN                True  \n",
       "36937  NaN                True  \n",
       "36938  NaN                True  \n",
       "37473  NaN                True  \n",
       "39497  NaN                True  \n",
       "\n",
       "[257 rows x 16 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data[merged_data['is_cellar_defender']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5317d633",
   "metadata": {},
   "outputs": [],
   "source": [
    "cellar_defenders = merged_data[merged_data['is_cellar_defender'] == True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c7f009fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The average overall rating for Cellar Defenders is 3.89.\n"
     ]
    }
   ],
   "source": [
    "avg_rating_cellar_defenders = cellar_defenders['overall_rating'].mean()\n",
    "\n",
    "print(f\"The average overall rating for Cellar Defenders is {avg_rating_cellar_defenders:.2f}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "47c22d2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Filters data for cellar defenders and non-cellar defenders\n",
    "cellar_defenders = merged_data[merged_data['is_cellar_defender']]\n",
    "non_cellar_defenders = merged_data[~merged_data['is_cellar_defender']]\n",
    "\n",
    "# Plots non-cellar defenders\n",
    "plt.scatter(non_cellar_defenders['price'], non_cellar_defenders['overall_rating'], label='Other Wines', alpha=0.6)\n",
    "\n",
    "# Plots cellar defenders\n",
    "plt.scatter(cellar_defenders['price'], cellar_defenders['overall_rating'], label='Cellar Defenders', alpha=0.6, color='red')\n",
    "\n",
    "\n",
    "plt.xlabel('Price')\n",
    "plt.ylabel('Rating')\n",
    "plt.title('Price vs Rating of Wines and Cellar Defenders')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ef0a6063",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_columns = merged_data[['wine_name', 'price', 'overall_rating', 'is_cellar_defender']]\n",
    "\n",
    "selected_columns.to_csv('optimized_wine_data.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a47d8975",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_gen_wealth = pd.read_csv('dfa-generation-shares.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "f2e8f97d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'Category', 'Net worth', 'Assets', 'Real estate',\n",
       "       'Consumer durables', 'Corporate equities and mutual fund shares',\n",
       "       'DB pension entitlements', 'DC pension entitlements',\n",
       "       'Private businesses', 'Other assets', 'Liabilities', 'Home mortgages',\n",
       "       'Consumer credit', 'Other liabilities', 'share'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gen_wealth.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f6b7b322",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Category</th>\n",
       "      <th>Net worth</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Real estate</th>\n",
       "      <th>Consumer durables</th>\n",
       "      <th>Corporate equities and mutual fund shares</th>\n",
       "      <th>DB pension entitlements</th>\n",
       "      <th>DC pension entitlements</th>\n",
       "      <th>Private businesses</th>\n",
       "      <th>Other assets</th>\n",
       "      <th>Liabilities</th>\n",
       "      <th>Home mortgages</th>\n",
       "      <th>Consumer credit</th>\n",
       "      <th>Other liabilities</th>\n",
       "      <th>share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1989:Q3</td>\n",
       "      <td>Silent</td>\n",
       "      <td>78.6</td>\n",
       "      <td>73.4</td>\n",
       "      <td>66.6</td>\n",
       "      <td>55.9</td>\n",
       "      <td>81.7</td>\n",
       "      <td>81.9</td>\n",
       "      <td>67.3</td>\n",
       "      <td>73.9</td>\n",
       "      <td>80.8</td>\n",
       "      <td>40.2</td>\n",
       "      <td>37.6</td>\n",
       "      <td>39.4</td>\n",
       "      <td>80.4</td>\n",
       "      <td>67.336174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1989:Q3</td>\n",
       "      <td>BabyBoom</td>\n",
       "      <td>21.1</td>\n",
       "      <td>26.0</td>\n",
       "      <td>32.8</td>\n",
       "      <td>41.7</td>\n",
       "      <td>18.1</td>\n",
       "      <td>18.1</td>\n",
       "      <td>32.5</td>\n",
       "      <td>25.7</td>\n",
       "      <td>18.7</td>\n",
       "      <td>58.1</td>\n",
       "      <td>61.3</td>\n",
       "      <td>56.8</td>\n",
       "      <td>19.4</td>\n",
       "      <td>32.527689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1989:Q3</td>\n",
       "      <td>GenX</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.7</td>\n",
       "      <td>1.1</td>\n",
       "      <td>3.8</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.136137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1989:Q3</td>\n",
       "      <td>Millennial</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1989:Q4</td>\n",
       "      <td>Silent</td>\n",
       "      <td>78.2</td>\n",
       "      <td>73.1</td>\n",
       "      <td>66.6</td>\n",
       "      <td>55.4</td>\n",
       "      <td>81.5</td>\n",
       "      <td>81.1</td>\n",
       "      <td>66.9</td>\n",
       "      <td>73.8</td>\n",
       "      <td>80.1</td>\n",
       "      <td>40.0</td>\n",
       "      <td>37.5</td>\n",
       "      <td>39.2</td>\n",
       "      <td>79.5</td>\n",
       "      <td>66.883400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Date    Category  Net worth  Assets  Real estate  Consumer durables  \\\n",
       "0  1989:Q3      Silent       78.6    73.4         66.6               55.9   \n",
       "1  1989:Q3    BabyBoom       21.1    26.0         32.8               41.7   \n",
       "2  1989:Q3        GenX        0.4     0.6          0.6                2.4   \n",
       "3  1989:Q3  Millennial        0.0     0.0          0.0                0.0   \n",
       "4  1989:Q4      Silent       78.2    73.1         66.6               55.4   \n",
       "\n",
       "   Corporate equities and mutual fund shares  DB pension entitlements  \\\n",
       "0                                       81.7                     81.9   \n",
       "1                                       18.1                     18.1   \n",
       "2                                        0.2                      0.0   \n",
       "3                                        0.0                      0.0   \n",
       "4                                       81.5                     81.1   \n",
       "\n",
       "   DC pension entitlements  Private businesses  Other assets  Liabilities  \\\n",
       "0                     67.3                73.9          80.8         40.2   \n",
       "1                     32.5                25.7          18.7         58.1   \n",
       "2                      0.1                 0.4           0.5          1.7   \n",
       "3                      0.0                 0.0           0.0          0.0   \n",
       "4                     66.9                73.8          80.1         40.0   \n",
       "\n",
       "   Home mortgages  Consumer credit  Other liabilities      share  \n",
       "0            37.6             39.4               80.4  67.336174  \n",
       "1            61.3             56.8               19.4  32.527689  \n",
       "2             1.1              3.8                0.2   0.136137  \n",
       "3             0.0              0.0                0.0   0.000000  \n",
       "4            37.5             39.2               79.5  66.883400  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gen_wealth.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "321277c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_gen_wealth = df_gen_wealth[['Date', 'Category', 'Net worth', 'share']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6d9a493d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>5.7</td>\n",
       "      <td>8.595330</td>\n",
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       "      <th>536</th>\n",
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       "      <td>Silent</td>\n",
       "      <td>12.8</td>\n",
       "      <td>4.004279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>537</th>\n",
       "      <td>2023:Q1</td>\n",
       "      <td>BabyBoom</td>\n",
       "      <td>53.2</td>\n",
       "      <td>48.446299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538</th>\n",
       "      <td>2023:Q1</td>\n",
       "      <td>GenX</td>\n",
       "      <td>28.4</td>\n",
       "      <td>38.693174</td>\n",
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       "    <tr>\n",
       "      <th>539</th>\n",
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       "      <td>Millennial</td>\n",
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       "</table>\n",
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       "</div>"
      ],
      "text/plain": [
       "        Date    Category  Net worth      share\n",
       "0    1989:Q3      Silent       78.6  67.336174\n",
       "1    1989:Q3    BabyBoom       21.1  32.527689\n",
       "2    1989:Q3        GenX        0.4   0.136137\n",
       "3    1989:Q3  Millennial        0.0   0.000000\n",
       "4    1989:Q4      Silent       78.2  66.883400\n",
       "..       ...         ...        ...        ...\n",
       "535  2022:Q4  Millennial        5.7   8.595330\n",
       "536  2023:Q1      Silent       12.8   4.004279\n",
       "537  2023:Q1    BabyBoom       53.2  48.446299\n",
       "538  2023:Q1        GenX       28.4  38.693174\n",
       "539  2023:Q1  Millennial        5.6   8.856248\n",
       "\n",
       "[540 rows x 4 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gen_wealth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "51fb684c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Year    Category      share\n",
      "0    1989    BabyBoom  32.692905\n",
      "1    1989        GenX   0.197308\n",
      "2    1989  Millennial   0.000000\n",
      "3    1989      Silent  67.109787\n",
      "4    1990    BabyBoom  32.773868\n",
      "..    ...         ...        ...\n",
      "131  2021      Silent   4.635245\n",
      "132  2022    BabyBoom  48.739098\n",
      "133  2022        GenX  38.486271\n",
      "134  2022  Millennial   8.509713\n",
      "135  2022      Silent   4.264918\n",
      "\n",
      "[136 rows x 3 columns]\n"
     ]
    }
   ],
   "source": [
    "df_gen_wealth['Year'] = df_gen_wealth['Date'].str.split(':').str[0]\n",
    "\n",
    "df_yearly_share = df_gen_wealth.groupby(['Year', 'Category'])['share'].mean().reset_index()\n",
    "df_yearly_share = df_yearly_share.loc[df_yearly_share['Year'] != '2023']\n",
    "\n",
    "print(df_yearly_share)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "0814a71a",
   "metadata": {},
   "outputs": [
    {
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       "      <td>38.693174</td>\n",
       "      <td>2023</td>\n",
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       "    <tr>\n",
       "      <th>539</th>\n",
       "      <td>2023:Q1</td>\n",
       "      <td>Millennial</td>\n",
       "      <td>5.6</td>\n",
       "      <td>8.856248</td>\n",
       "      <td>2023</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>540 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date    Category  Net worth      share  Year\n",
       "0    1989:Q3      Silent       78.6  67.336174  1989\n",
       "1    1989:Q3    BabyBoom       21.1  32.527689  1989\n",
       "2    1989:Q3        GenX        0.4   0.136137  1989\n",
       "3    1989:Q3  Millennial        0.0   0.000000  1989\n",
       "4    1989:Q4      Silent       78.2  66.883400  1989\n",
       "..       ...         ...        ...        ...   ...\n",
       "535  2022:Q4  Millennial        5.7   8.595330  2022\n",
       "536  2023:Q1      Silent       12.8   4.004279  2023\n",
       "537  2023:Q1    BabyBoom       53.2  48.446299  2023\n",
       "538  2023:Q1        GenX       28.4  38.693174  2023\n",
       "539  2023:Q1  Millennial        5.6   8.856248  2023\n",
       "\n",
       "[540 rows x 5 columns]"
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     "execution_count": 46,
     "metadata": {},
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   "source": [
    "df_gen_wealth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "02c947a0",
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2022</td>\n",
       "      <td>BabyBoom</td>\n",
       "      <td>48.739098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2022</td>\n",
       "      <td>GenX</td>\n",
       "      <td>38.486271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2022</td>\n",
       "      <td>Millennial</td>\n",
       "      <td>8.509713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2022</td>\n",
       "      <td>Silent</td>\n",
       "      <td>4.264918</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year    Category      share\n",
       "0    1989    BabyBoom  32.692905\n",
       "1    1989        GenX   0.197308\n",
       "2    1989  Millennial   0.000000\n",
       "3    1989      Silent  67.109787\n",
       "4    1990    BabyBoom  32.773868\n",
       "..    ...         ...        ...\n",
       "131  2021      Silent   4.635245\n",
       "132  2022    BabyBoom  48.739098\n",
       "133  2022        GenX  38.486271\n",
       "134  2022  Millennial   8.509713\n",
       "135  2022      Silent   4.264918\n",
       "\n",
       "[136 rows x 3 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_yearly_share"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "71a6ace8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_yearly_share.to_csv('generational_wealth_gap.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "8346a078",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_transposed = df_yearly_share.pivot(index='Year', columns='Category', values='share')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "75055bdc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_transposed.to_csv('transposed_data.csv', index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a510a1bf",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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