01-batch-pdf-processing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Batch PDF processing\n",
    "\n",
    "Dan Keemahill ([@dankeemahill](https://twitter.com/dankeemahill))\n",
    "\n",
    "https://github.com/dankeemahill/nicar20-batch-pdf-processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Welcome!\n",
    "\n",
    "In this hourlong session, we will walk through **Python** code that extracts data from **nine PDFs**.\n",
    "\n",
    "### What if I need to parse bigger batches of PDFs, like 1,000 or 10,000 or 1,000,000 or... ?\n",
    "\n",
    "- Check out [how ICIJ mined 715,000 records](https://www.icij.org/investigations/luanda-leaks/how-we-mined-more-than-715000-luanda-leaks-records/) with their open-source tool [Datashare](https://www.icij.org/blog/2019/11/what-is-datashare-frequently-asked-questions-about-our-document-analysis-software/)\n",
    "\n",
    "- Check out Miguel Barbosa's 2018 [presentation](https://docs.google.com/presentation/d/12ShGfr3HhSXdLwK5R1pr1J5cvjLXuEmaXGxErG3gShg/preview)\n",
    "\n",
    "- Check out Jacob Fenton's [session](https://ireapps.github.io/nicar-2020-schedule#20200308_pdf_3_batch_pdf_processing_repeat_2478) on Sunday\n",
    "\n",
    "### Concepts apply no matter how many PDFs you have\n",
    "\n",
    "- Know the types of PDFs\n",
    "- Trial and error\n",
    "- Divide and conquer\n",
    "- Check the facts\n",
    "- [Collaborate!](https://source.opennews.org/articles/news-nerds-against-pdfs/)\n",
    "\n",
    "\n",
    "### The challenge\n",
    "\n",
    "ICE has a [page](https://www.ice.gov/facility-inspections) of detention facility inspections in PDF. Most inspections involve a \"cover letter\" that lists violations standards and their components and a \"summary review form\" that tabulates incidents and provides narratives.\n",
    "\n",
    "For a USA TODAY Network [investigation](https://www.usatoday.com/in-depth/news/nation/2019/12/19/ice-detention-private-prisons-expands-under-trump-administration/4393366002/) of private prisons that detain immigrants, we wanted to count violations from these reports.\n",
    "\n",
    "In this notebook, I'll demonstrate parsing grievances filed from summary forms with [pdfplumber](https://github.com/jsvine/pdfplumber).\n",
    "\n",
    "### Why [pdfplumber](https://github.com/jsvine/pdfplumber)?\n",
    "\n",
    "There are many open-source tools that can work with PDFs! The [2019 Q4 IRE Journal](https://www.ire.org/wp-content/uploads/2019/12/IREJournal_Q4_2019.pdf) had a useful list of tools \n",
    "\n",
    "I turned to pdfplumber for a few reasons: I'm familiar with python, I had previous experience with pdfplumber and because pdfplumber was built by journalist Jeremy Singer-Vine and [contributors](https://github.com/jsvine/pdfplumber#acknowledgments--contributors).\n",
    "\n",
    "Most importantly, I was confident pdfplumber could work for the task because the PDFs were of the \"native\" [type](https://docs.google.com/presentation/d/12ShGfr3HhSXdLwK5R1pr1J5cvjLXuEmaXGxErG3gShg/preview?slide=id.g1ebfd012eb_0_40)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting to know the PDFs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LAWINCI_SIS_10-10-2019.pdf\n",
      "RVRCCLA_SIS_10-24-2019.pdf\n",
      "RWCCMLA_SIS_10-03-2019.pdf\n",
      "RiverCorrectionalCenter_SIS_12-06-2018.pdf\n",
      "allenParishDetFac_SIS_02-14-2019.pdf\n",
      "catahoulaLA_SIS_08-22-2019.pdf\n",
      "jenaLaSalle_SIS_09-26-2019.pdf\n",
      "natchitochesDcLA_SIS_07-03-2019.pdf\n"
     ]
    }
   ],
   "source": [
    "# examine the directory\n",
    "!ls pdf/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pdfplumber"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pdf = pdfplumber.open(\n",
    "    'pdf/jenaLaSalle_SIS_09-26-2019.pdf'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<pdfplumber.page.Page at 0x109fb6af0>,\n",
       " <pdfplumber.page.Page at 0x109fb83d0>,\n",
       " <pdfplumber.page.Page at 0x109fb8ac0>,\n",
       " <pdfplumber.page.Page at 0x109fba1c0>,\n",
       " <pdfplumber.page.Page at 0x109fba790>,\n",
       " <pdfplumber.page.Page at 0x109fbaa00>,\n",
       " <pdfplumber.page.Page at 0x109f2b8b0>,\n",
       " <pdfplumber.page.Page at 0x109f2bb20>,\n",
       " <pdfplumber.page.Page at 0x109f2b7c0>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdf.pages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# how many pages does this PDF have?\n",
    "\n",
    "len(pdf.pages)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get the first page\n",
    "\n",
    "page = pdf.pages[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x1093188b0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# what does the first page look like?\n",
    "\n",
    "page.to_image()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Where are the grievances in this PDF?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x10be378b0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "page = pdf.pages[5]\n",
    "page.to_image()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Find the grievances in a different PDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "pdf = pdfplumber.open(\n",
    "    'pdf/allenParishDetFac_SIS_02-14-2019.pdf'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-10-3ad51dbb9247>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpages\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m: list index out of range"
     ]
    }
   ],
   "source": [
    "page = pdf.pages[5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_Oh snap!_ What happened?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pdf.pages)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Collect metadata about our PDFs\n",
    "\n",
    "We have just learned that different PDFs have different numbers of pages. This is a great chance to learn more about our documents by creating metadata about them.\n",
    "\n",
    "How many pages does each PDF have?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import a python library that helps us find batches of files\n",
    "\n",
    "from glob import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf',\n",
       " 'pdf/catahoulaLA_SIS_08-22-2019.pdf',\n",
       " 'pdf/RVRCCLA_SIS_10-24-2019.pdf',\n",
       " 'pdf/LAWINCI_SIS_10-10-2019.pdf',\n",
       " 'pdf/RWCCMLA_SIS_10-03-2019.pdf',\n",
       " 'pdf/natchitochesDcLA_SIS_07-03-2019.pdf',\n",
       " 'pdf/jenaLaSalle_SIS_09-26-2019.pdf',\n",
       " 'pdf/allenParishDetFac_SIS_02-14-2019.pdf']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glob('pdf/*')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf 4\n",
      "pdf/catahoulaLA_SIS_08-22-2019.pdf 4\n",
      "pdf/RVRCCLA_SIS_10-24-2019.pdf 9\n",
      "pdf/LAWINCI_SIS_10-10-2019.pdf 9\n",
      "pdf/RWCCMLA_SIS_10-03-2019.pdf 9\n",
      "pdf/natchitochesDcLA_SIS_07-03-2019.pdf 4\n",
      "pdf/jenaLaSalle_SIS_09-26-2019.pdf 9\n",
      "pdf/allenParishDetFac_SIS_02-14-2019.pdf 4\n"
     ]
    }
   ],
   "source": [
    "# display each PDF and the number of pages it has\n",
    "\n",
    "for file_name in glob('pdf/*'):\n",
    "    pdf = pdfplumber.open(file_name)\n",
    "    print(\n",
    "        file_name,\n",
    "        len(pdf.pages)\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import a python library that helps us work with data\n",
    "\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'file_name': 'pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf', 'pages': 4},\n",
       " {'file_name': 'pdf/catahoulaLA_SIS_08-22-2019.pdf', 'pages': 4},\n",
       " {'file_name': 'pdf/RVRCCLA_SIS_10-24-2019.pdf', 'pages': 9},\n",
       " {'file_name': 'pdf/LAWINCI_SIS_10-10-2019.pdf', 'pages': 9},\n",
       " {'file_name': 'pdf/RWCCMLA_SIS_10-03-2019.pdf', 'pages': 9},\n",
       " {'file_name': 'pdf/natchitochesDcLA_SIS_07-03-2019.pdf', 'pages': 4},\n",
       " {'file_name': 'pdf/jenaLaSalle_SIS_09-26-2019.pdf', 'pages': 9},\n",
       " {'file_name': 'pdf/allenParishDetFac_SIS_02-14-2019.pdf', 'pages': 4}]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make a list of dictionaries that contain metadata\n",
    "\n",
    "payload = []\n",
    "\n",
    "for file_name in glob('pdf/*'):\n",
    "    pdf = pdfplumber.open(file_name)\n",
    "    payload.append({\n",
    "        'file_name': file_name,\n",
    "        'pages': len(pdf.pages)\n",
    "    })\n",
    "\n",
    "payload"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>file_name</th>\n",
       "      <th>pages</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>pdf/catahoulaLA_SIS_08-22-2019.pdf</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>pdf/RVRCCLA_SIS_10-24-2019.pdf</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pdf/LAWINCI_SIS_10-10-2019.pdf</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pdf/RWCCMLA_SIS_10-03-2019.pdf</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>pdf/natchitochesDcLA_SIS_07-03-2019.pdf</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>pdf/jenaLaSalle_SIS_09-26-2019.pdf</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>pdf/allenParishDetFac_SIS_02-14-2019.pdf</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        file_name  pages\n",
       "0  pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf      4\n",
       "1              pdf/catahoulaLA_SIS_08-22-2019.pdf      4\n",
       "2                  pdf/RVRCCLA_SIS_10-24-2019.pdf      9\n",
       "3                  pdf/LAWINCI_SIS_10-10-2019.pdf      9\n",
       "4                  pdf/RWCCMLA_SIS_10-03-2019.pdf      9\n",
       "5         pdf/natchitochesDcLA_SIS_07-03-2019.pdf      4\n",
       "6              pdf/jenaLaSalle_SIS_09-26-2019.pdf      9\n",
       "7        pdf/allenParishDetFac_SIS_02-14-2019.pdf      4"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make a dataframe of the metadata and display the dataframe\n",
    "\n",
    "pdf_meta = pd.DataFrame(\n",
    "    payload\n",
    ")\n",
    "\n",
    "pdf_meta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We know these records are different page lengths, but where are the grievance tables in each PDF?\n",
    "\n",
    "### Find patterns in text with regular expressions\n",
    "\n",
    "Let's practice!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to find pages that contain \"Grievances:\" `OR` \"grievances\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "pattern_grievance_table = r'Grievances:|grievances'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"Even just learning how to write a simple loop is very helpful to convert PDFs.\" - Todd Wallack, [NICAR 2017](https://www.ire.org/resource-center/audio/1223/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "payload = []\n",
    "\n",
    "# loop over all the PDF files in the directory\n",
    "\n",
    "for file_name in glob('pdf/*'):\n",
    "    pdf = pdfplumber.open(file_name)\n",
    "    \n",
    "    # loop over each page in the opened PDF\n",
    "    \n",
    "    for page_index, page in enumerate(pdf.pages):\n",
    "\n",
    "        if re.search(\n",
    "                pattern_grievance_table,\n",
    "                page.extract_text()\n",
    "            ):\n",
    "            \n",
    "            # add metadata to the list if the grievance pattern is found\n",
    "\n",
    "            payload.append({\n",
    "                'file_name': file_name,\n",
    "                'table_page': page_index\n",
    "            })\n",
    "            \n",
    "            \n",
    "pdf_grievance_pages = pd.DataFrame(payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>file_name</th>\n",
       "      <th>table_page</th>\n",
       "      <th>pages</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>pdf/catahoulaLA_SIS_08-22-2019.pdf</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>pdf/RVRCCLA_SIS_10-24-2019.pdf</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pdf/LAWINCI_SIS_10-10-2019.pdf</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pdf/RWCCMLA_SIS_10-03-2019.pdf</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>pdf/natchitochesDcLA_SIS_07-03-2019.pdf</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>pdf/jenaLaSalle_SIS_09-26-2019.pdf</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>pdf/allenParishDetFac_SIS_02-14-2019.pdf</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        file_name  table_page  pages\n",
       "0  pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf           1      4\n",
       "1              pdf/catahoulaLA_SIS_08-22-2019.pdf           1      4\n",
       "2                  pdf/RVRCCLA_SIS_10-24-2019.pdf           5      9\n",
       "3                  pdf/LAWINCI_SIS_10-10-2019.pdf           5      9\n",
       "4                  pdf/RWCCMLA_SIS_10-03-2019.pdf           5      9\n",
       "5         pdf/natchitochesDcLA_SIS_07-03-2019.pdf           1      4\n",
       "6              pdf/jenaLaSalle_SIS_09-26-2019.pdf           5      9\n",
       "7        pdf/allenParishDetFac_SIS_02-14-2019.pdf           1      4"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdf_meta = pdf_grievance_pages.merge(\n",
    "    pdf_meta,\n",
    "    on='file_name'\n",
    ")\n",
    "\n",
    "pdf_meta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we know where the grievance data are on each document. Time to parse!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parse a single PDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "file_name     pdf/allenParishDetFac_SIS_02-14-2019.pdf\n",
       "table_page                                           1\n",
       "pages                                                4\n",
       "Name: 7, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get metadata for a PDF\n",
    "\n",
    "pdf_row = pdf_meta.loc[\n",
    "    lambda x: x['file_name'] == 'pdf/allenParishDetFac_SIS_02-14-2019.pdf'\n",
    "].iloc[0]\n",
    "\n",
    "pdf_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x11a311be0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdf = pdfplumber.open(pdf_row['file_name'])\n",
    "\n",
    "# use our metadata to open the page with the grievance data and view it\n",
    "\n",
    "page = pdf.pages[\n",
    "    pdf_row['table_page']\n",
    "]\n",
    "\n",
    "page.to_image()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x11a317cd0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use the pdfplumber tablefinder!\n",
    "\n",
    "page.to_image().debug_tablefinder()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The debugger looks messy because the PDF has inconsistent rows.\n",
    "\n",
    "We could parse the whole page and clean it up as a second step, but we can also zoom in to a smaller area and extract it with more accuracy.\n",
    "\n",
    "In this case, we just want the \"Greivances Received\" row. We can `crop` the page using pixel coordinates.\n",
    "\n",
    "pdfplumber can crop pdfs with bounding boxes, which are `\"4-tuple with the values (x0, top, x1, bottom)\"`\n",
    "\n",
    "Another way to remember it: `(left, top, right, bottom)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x11600c520>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crop_coordinates = (0, 300, page.width, page.height)\n",
    "\n",
    "page_cropped = page.crop(crop_coordinates)\n",
    "\n",
    "page_cropped.to_image().debug_tablefinder()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Getting the coordinates exactly right can be tricky.\n",
    "\n",
    "I opened a PDF in Adobe Illustrator and used its interface to find coordinates, but we can also use pdfplumber to find coordinates.\n",
    "\n",
    "pdfplumber provides the coordinates of `words`, we can use those coordinates to determine where we should crop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "page.extract_words()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'x0': Decimal('42.240'),\n",
       " 'x1': Decimal('85.576'),\n",
       " 'top': Decimal('529.795'),\n",
       " 'bottom': Decimal('542.080'),\n",
       " 'text': 'Grievances:'}"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coordinate_grievances = list(filter(\n",
    "    lambda x: x['text'] == 'Grievances:',\n",
    "    page.extract_words()\n",
    "))[0]\n",
    "\n",
    "coordinate_grievances"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Trial and error!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "coordinate_left = coordinate_grievances['x1'] + 100\n",
    "coordinate_right = page.width\n",
    "coordinate_top = coordinate_grievances['top'] - 5\n",
    "coordinate_bottom = coordinate_grievances['top'] + 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Decimal('185.576'),\n",
       " Decimal('524.795'),\n",
       " Decimal('612.000'),\n",
       " Decimal('559.795'))"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crop_coordinates = (coordinate_left, coordinate_top, coordinate_right, coordinate_bottom)\n",
    "\n",
    "crop_coordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAasAAAAjCAIAAACl57I7AAADz0lEQVR4nO2dz27aMBzHP846iYjtKSZtB3qYRCes3vokOey5OPAk3KZEW6Ud4NinKC2HTckOhiwDxp+RjOaX70eVasAYf2LLcZzYdkBRFIi9OOdCwOqxCoKyayOqnOcQNZGoEEK0gqtLZ6AFeA+kZThNL5qbuvE+/E+RXQtR5TyTiEovWmyzLgO//ivfsUBwSVNk10ZUOc8nKorC6vBBXYQzT1oJW0J2rca24H+wu1IH8BCpcz6FAaSQObcgzZyRU23pIrs2EnQ6UjkbQuOAR+HhJ0AfgGgdMEAE/QHLmNyqHRDzNCCaE9uyowvFN2A5J/fQ0IWqOoAHCacf/0j0lo8wASC5YIZqZQKk+AFLq3aQPPJ9TuxXRWnGji4UX4qHJw+jUUED18JOg4AH8Z4sy27gG/3r6+vJ5PdHw+EQuL+/v1jmziZJiB/mxXJh1Q7ozbIlkbv+VLXDimAx+xqTWy2++GH+vFzMYTQaNTEUqBbwKJxzoQ9YrU+hhgVaXc8+JL6YfbVqB7wfvpoTv75fVN80I/hj+Cb0AU0W34fEz2aZ1xPRL5ZQvaoVzhK27bAuaNuuFtQCCiG6i1pAIUR3UQsohOguagHPxcAdtz3YtsO6oG27WtAT0f+O7Ypl2w7rgrbtakR9QCFEd1ELKIToLmoBhRDdZdUCOueOXCRGa8kIIcxwWh9QzZ8QwhLRxi4kZWfQVSg/ulQuhRCiCa44omlT2yeEMMnqKrjsA4bAziZP6+kLIYxxVRTF/i5eGcG5ji6lFbbjugPoJwkba8y1nSQhfhgXLKzaAT2+LImcOTvC+oBMwxrRJosvfhg/s6C5veLK1o0/u37VkcHyze1o5im345pyG1bfTcwswbt2mb77bNhuMmHK7Zg7bNmx1hlzZ7j4pu8+j//DXnElVK52i79Tf0ZeMNUzj7FzLH8aya512BasGmmvuEux2iuuT/7Id4avenx5P7y9dK7qIbj0yCOwagf0yW94WtqyYy0Ymy6+Hrn2irs8HlLw5OHl23XAAMGlA3ZAji07ulR8DV14albcMay2rS/DtpBdq7Et+NuuiUFAwr3gEDryVm812sbT1H+LfzDOkdSY1El4T5at6tZ6w6oTjsALx3ugyLKMjtlhRbAjlZNmhgJd9QHAgwdrewLJ/m+Vg4znF0ONSdX16ztvnbeU7aK0bYchwQ5Wzho5a1bcxhHfWF5hZ3h/+hs/UY28/YsvhD3PkBvAth3WBW3b1ULEcbPidsY5acrwnjg709d8ZCFE00QbZ4mTZsWd9HJn+htpbqew51MhhDiTX/53aEJmpUzUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x1160d12b0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "page.within_bbox(\n",
    "    crop_coordinates\n",
    ").to_image().debug_tablefinder()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Much better, let's get the table!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['0', '0', '0', '0']]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extracted_table = page.within_bbox(\n",
    "    crop_coordinates\n",
    ").extract_table()\n",
    "\n",
    "extracted_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data are just one row, but let's make a pandas DataFrame out of it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>q1</th>\n",
       "      <th>q2</th>\n",
       "      <th>q3</th>\n",
       "      <th>q4</th>\n",
       "      <th>total</th>\n",
       "      <th>file</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>pdf/allenParishDetFac_SIS_02-14-2019.pdf</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   q1  q2  q3  q4  total                                      file\n",
       "0   0   0   0   0      0  pdf/allenParishDetFac_SIS_02-14-2019.pdf"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(\n",
    "    extracted_table,\n",
    "    columns=['q1', 'q2', 'q3', 'q4']\n",
    ").astype(int).assign(\n",
    "    total = lambda x: x.sum(axis=1),\n",
    "    file=file_name\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's extract grievances from a nine-page PDF."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x10c793850>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdf_row = pdf_meta.loc[\n",
    "    lambda x: x['pages'] == 9\n",
    "].iloc[0]\n",
    "\n",
    "pdf = pdfplumber.open(pdf_row['file_name'])\n",
    "\n",
    "page = pdf.pages[\n",
    "    pdf_row['table_page']\n",
    "]\n",
    "\n",
    "page.to_image()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwkAAABICAIAAAAyFS6PAAAMuElEQVR4nO3db0wb9x3H8S+GEBJwJOgaiEiyBE+kFCVSaim2tDxpBHswqVrFirUnnStNAQkpzyKBsudRI/VZq0oQ7QFPIaKTOk2VcmqeVTSNWVrGENFwt2YkWUjx5GAgKdh78IPzcf5ztnGw7+79euS7+3G56vvp+cvd746aVColcIS2trZ33nnn5s2blT4QVF5bW9snn3zy3nvvVfpAUKX6+vpEZGpqqtIHAls6f/78/fv3Hdw/eCp9AAAAAFWkxsF9n3sEgyIiMzMzzc3Np0+fnp7OPkCXOQDVz1REJVetZ2ZmTp061dLSQhjcxrK+asCDBw9EpLOz0zSgwJjBqQrMz+zs7NraWiAQcGo26I3sTc/x9PT2PbXZ2Zv6GtOAzB+BXaiqZf0ay1pZdU/to4/e09cIYXA6y/oaF9U9tUePpjIH5I8ZnKqo/Kh7aoFAyvQjjkFvZGOmc5ZxvpGx98+aWs53NpKnWPqmzDDo840IgxtYhkTRBxjnG5EQFJsf43wjR8aD+Ub2liuO+nrLAahy+c87eX7dN40pZABsbS8BmJuz3kPW221wDE4gRnVffPFFpY8BBdnc3NzY2NAXr127JCK3bn2pr/F4PA8fPrx165Za/Pbbd0Xk1q0/59rhysqlzk65fv3LXANQDVZWLl2//uVOVbO4elXef//dEyfipjB89dVX+iJhcLbMs4FJZgBWVlZERD9dbG6+u7ISz7OHq1fl2rVLeQbAvkrIz+rqqmlMMOioJqmmtbW10seAUqys/LWl5dfGNZ8vL/d6vQ0NDfoAETGNsdwJqk0hNXr6dPHoUZ9xzefLy79pbU0mk/pOhDA4l2XtMgPwl2fPepqaOF1ASsrP58vLF5JJ45wch/VGdU+ePKn0MaAUwaBMT++qXcLj+dvBg6dPndoekDgoItM7i9l3kjiYfwAqrpAaeZ95nuwek3j69O9NTS0tLfpOhDA4l2XtMgOw8eOPdz2eTk4XKCk/a8vLr/igKqyu0geAslmoq3tz5X+Jo9uLyS0RkURie/HQ4pxn7XnysHfd163/SHIrPQDVKbNGmaVMpXaNObQ4t1BXd/bf/0kcbNF3IoTBuUy1y6xvZgB+8HpPxFf1NSTEzUrIz2JDg6yt7fNx7id6IxvLvIb5g/fo6vj2qr9fFBFZ2Fk8Ew42iqz7uvU14bCILz0A1Wk9bK5RZimTFyUo0+Pj6QGyMPOs7eePCYM7rIfNATDVNzMAsvTgX40/WzcM8PnyJUSyRRHOUEp+orPGPThvnj7PqdmV5Z1dn098Posx+v8MqGbhsMVWy0ITBmezrF0hAcgvfwhha2XJj5MmGwm9kd3l6tb1E9muM5phNGc6u1CnLXO9dkqp1mcfs4MwuIRlffMkRH3z5d8D3bOzlZwf5100Et79aHfGF5XO1Nc3NbX+tv2hWmP6vpyWYGOjJBISlGnjANiC8cvpTHhXKfU6Gmu9sDBz7JjvV0fm1RrC4AaW9TUOWFp6sLXVEDr5KHPA+Hg6Ywvj0zRGLlFUfqLR2XNra7wXG1VNdUiJu3draw9svXE+8ywWDsuhxTlPrSS3ZN3XzWnOjvQTU/5SqlqvbyTqDzS87DxHGNzGsr5qwMufNlKpmmTXW6YBKmbGPQiNkZsUmJ+NF2uzySR/Tw02oK4brWoPs241/iK4zweG8rIs5Znw9nWjx5/Nl7YH2FohCVHXjdbvPCptD3CwQvKjrhs5uH9gvhEAAECaRW8Ui8WyfgYAAHCknO83Ghsbi0QisVhscnJyeHi4p6ent7d3eHj4ww8/FJFoNDo2NqZpWnNz8+3bt4v6J2OxmPpZESn2Z4Fc4vH4xx9/HI/Hjx8/Ho/H+/r6urq6Kn1QqDyCgaIQGEiu60aapo2MjIyOjk5MTAwMDKgeqLm5WR/Q0dHR398fiURK+Cebm5v7+/tVbwSURTweHxoaEpEbN25cuXKlp6dnaGhofj77bBu4B8FAUQgMlOy90eTkpN/vV59HR0fv3bvn9/tXVlbURSNFH1CCjo6Okn8WyDQ+Pj4/P//BBx+oxUAg0N7ePjw8XNGDQuURDBSFwEDJ3htFo9F9Pg5gL27fvt3V1dXe3q6vCQQCS0tLXJ50OYKBohAYKObeKBqNapoWi8VisZimaZqm6X1SNBqdnJy03OPk5OTIyMiNGzcyG6xIJKI2Ma0bZTQ/P7+0tGQ8nYnIhQsX1KYKHRQqj2CgKAQGupzPqRnnEkUikVAo5PP5xsbG8uwrFouFQqFYLNbT0xOJREzjBwcHx8bGBgYG+vv7Q6FQWY4ekJ3T1vHjx3NtgjsRDBSFwEBnfk6to6Ojo6NDTbvu6enR14+OjlpeNAqFQv39/QMDAyLi9/vVBSS1ODIyomna4uKivjffHv/yIbBjaWmp0oeAakQwUBQCA13OZ/hNjA+pZaVuxvn9/pGREbWmo6NDX6muGOmDmYsNAACqU6G9kSV1Vcl4qUl99vv96j1Je3muDcjD6/VW+hBQjQgGikJgoCtbb6SmV/v9/swrTGqGP/Ov8YrkeTObaVolXIVgoCgEBrqy/T011RJlzkmKRqNqE+8FwCsSCAQkY7KkmjrAC23djGCgKAQGurL1RuoOmun5/Egkomma2lTI8/9Aafr6+kxntPn5+SNHjhhv8sKFCAaKQmCg5PybIcXuyO/39/T0RKPR3t7eyclJ9VdH1HNq+qbBwUHVOaln+/V3Ke3xvwFQ77GdmppSi/F4XNO0cDh85MiRSh4WKo1goCgEBkqWdz/qD5qNjIyotxyp9xupD+rKkGp0RETTNP1a0cTEhHqzUSgU6u3tjcViExMTalcTExP9/f1jY2MtLS01NTVqpd/v50YbyqK9vf3TTz+dmpqamprSNG1oaKivr09/8T9ci2CgKAQGSk0qlSrvHqPRaDQazTop27gpFotZvhcARZmpr29qal3VHmbdeiYcbGyUREIWxqf3+cD209dffy0iXV1dDv49z7KUZ8LBhYWZY8d8jz/L/sI6l4TByA3B0BWSkKWlB1tbDet3HpW2B8dzVWBMCslPNDp7bm2t7P1D9Sjbc2o69fZIy000RngV1GxKwIRgoCgExuXKf90I+ywY3P6QuHu3tvbA1hvnRWR8PD0gHBYRObQ456mV5Jas+7pNA2ALqo6yu5SmOuq1Xt9I1B9oeNl5TgiDm1jWVx/w8qeNVKom2fVWrgEkxIUKz8/Gi7XZZFJ1kNNOvLZIb2RvqjFS0dTvqan4qkDrn42XSY0DUP1M9cpVSmOt9XtqhME9LOtrHKDfU9NXGkea7qoQEjcoKj/6PTXjd5CTlO0Zfuy/XKHUc5zrjGYMOmwh19eSvt6y1oTB2coSAMuYwalKzo/6AtJvXzgGvZFd5e/Wx8dlcVEWF3dH2TCab0S7CIezfTPtLuXFi9sfsiIMjpfle2t3fbMEwEANMNt9ctEvLMF59pgfR7ZH9EY2lv8yps8nPl++Afwu6CT5q0kYHG+PAci/FY63x/w4754a843sKhg0x3Gmvv7NVI2aiy0iby/+SUTu+P6gFg8tznnWnicPe9X0On2MPgDVKbNGmaVs/ced/775tnHA/c0XZ2vq1FxsIQxOZ6pdZn0zA/DPhgMn4qtqLnbWASTEPUrIz1xN0vQMf+ZXkq2V/xl+VMqZzc3Hr79+unF70VMrItK4syjnuiUY9JzrbjT8iKfWMABVKUuNMkpZU7N7zLnuM3fvPv/FqRbC4A7m2mXUNzMAJyORH454O0kISsqP75tv9vEAK6Du8uXLlT4GlOL7769dvnzduGbQ4/n9a6/98uzZnQGHReTyzmKOnRzOPwAVV0iNXsx4TGMG79374+nTJ0+e1HcihMG5LGuXGYAr3333u7Y2TheQkvIzeO/eKz8soCSWly+nCxuDKldIjZ4XsBPC4GB7PxuQEDcrMT8pg0Ag5SR1KeYb2VMwKCKpPPd3vV4RkefPc9Z350k3AlDVgkHrGnm90t1NGNxr72cDr1e6uy0CUEgUYUfl+jZxEuZi21iex/iNSc0zwElT5xws/yRHtZUwuNzeA5Brqz6GhDgYJxATnuG3sVxvldCTajkAdpHr1zLTtxphcK2yBMAyZnAqTiAmXDeyvaynLWNSLQfAFgqpI2Fwub0HgIS4GfHQ0RsBAACkcU8NAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAgjd4IAAAg7f9u2PR57kDLSQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x116767a30>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coordinate_grievances = list(filter(\n",
    "    lambda x: x['text'] == 'grievances',\n",
    "    page.extract_words()\n",
    "))[0]\n",
    "\n",
    "# I found these exact values after trial and error!\n",
    "coordinate_left = coordinate_grievances['x1']\n",
    "coordinate_right = page.width\n",
    "coordinate_top = coordinate_grievances['top'] - 5\n",
    "coordinate_bottom = coordinate_grievances['top'] + 30\n",
    "\n",
    "crop_coordinates = (coordinate_left, coordinate_top, coordinate_right, coordinate_bottom)\n",
    "\n",
    "page.within_bbox(\n",
    "    crop_coordinates\n",
    ").to_image(resolution=150).debug_tablefinder()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The crop looks close, but notice tablefinder is adding more lines than we need. We can use one of the many pdfplumber [table settings](https://github.com/jsvine/pdfplumber#table-extraction-settings) to fine tune the table. In this case, I found the `snap_tolerance` setting helped with the multiple lines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>ice</th>\n",
       "      <th>non_ice</th>\n",
       "      <th>total</th>\n",
       "      <th>file</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>pdf/allenParishDetFac_SIS_02-14-2019.pdf</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ice  non_ice  total                                      file\n",
       "0    0        0      0  pdf/allenParishDetFac_SIS_02-14-2019.pdf"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(\n",
    "    page.within_bbox(\n",
    "        crop_coordinates\n",
    "    ).extract_table({\n",
    "        'snap_tolerance': 8\n",
    "    }),\n",
    "    columns = [\n",
    "        'ice',\n",
    "        'non_ice',\n",
    "        'total'\n",
    "    ]\n",
    ").astype(int).assign(\n",
    "    file=file_name\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We've extracted data from a 4-page PDF and a 9-page PDF, and we can apply these techniques to our entire batch.\n",
    "\n",
    "\"Even just learning how to write a simple loop is very helpful to convert PDFs.\" - Todd Wallack, [NICAR 2017](https://www.ire.org/resource-center/audio/1223/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_row(row):\n",
    "    pdf = pdfplumber.open(row['file_name'])\n",
    "    page = pdf.pages[row['table_page']]\n",
    "    page_count = row['pages']\n",
    "    \n",
    "    coordinate_grievances = list(filter(\n",
    "        lambda x: re.search(\n",
    "            pattern_grievance_table, x['text']\n",
    "        ),\n",
    "        page.extract_words()\n",
    "    ))[0]\n",
    "    \n",
    "    coordinate_left = coordinate_grievances['x1']\n",
    "    coordinate_right = page.width\n",
    "    \n",
    "    if row['pages'] == 9:\n",
    "        coordinate_top = coordinate_grievances['top'] - 5\n",
    "        coordinate_bottom = coordinate_grievances['top'] + 30\n",
    "        \n",
    "    else:\n",
    "        coordinate_left = coordinate_left + 100\n",
    "        coordinate_top = coordinate_grievances['top'] - 5\n",
    "        coordinate_bottom = coordinate_grievances['top'] + 30\n",
    "\n",
    "    crop_coordinates = (coordinate_left, coordinate_top, coordinate_right, coordinate_bottom)\n",
    "        \n",
    "    page = page.within_bbox(crop_coordinates)\n",
    "    \n",
    "    if page_count == 9:\n",
    "        return pd.DataFrame(\n",
    "            page.extract_table({\n",
    "                'snap_tolerance': 8\n",
    "            }),\n",
    "            columns = [\n",
    "                'ice',\n",
    "                'non_ice',\n",
    "                'total'\n",
    "            ]\n",
    "        ).astype(int).assign(\n",
    "            total=lambda x: x['ice'] + x['non_ice'],\n",
    "            file=row['file_name']\n",
    "        )\n",
    "\n",
    "    else:\n",
    "        return pd.DataFrame(\n",
    "            page.extract_table(),\n",
    "            columns=[\n",
    "                'q1',\n",
    "                'q2',\n",
    "                'q3',\n",
    "                'q4'\n",
    "            ]\n",
    "        ).astype(int).assign(\n",
    "            total=lambda x: x.sum(axis=1),\n",
    "            file=row['file_name']\n",
    "        )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our function is ready, let's run it on all the PDFs!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "invalid literal for int() with base 10: 'N/A'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-37-376cafa7bd79>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrow\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mpdf_meta\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miterrows\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m     \u001b[0mpayload\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprocess_row\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-36-7ed177e9ae1c>\u001b[0m in \u001b[0;36mprocess_row\u001b[0;34m(row)\u001b[0m\n\u001b[1;32m     43\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 45\u001b[0;31m         return pd.DataFrame(\n\u001b[0m\u001b[1;32m     46\u001b[0m             \u001b[0mpage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mextract_table\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     47\u001b[0m             columns=[\n",
      "\u001b[0;32m~/.local/share/virtualenvs/repo-4rE-q4RG/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[1;32m   5695\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5696\u001b[0m             \u001b[0;31m# else, only a single dtype is given\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5697\u001b[0;31m             \u001b[0mnew_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5698\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_constructor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__finalize__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5699\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/share/virtualenvs/repo-4rE-q4RG/lib/python3.8/site-packages/pandas/core/internals/managers.py\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[1;32m    580\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    581\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"raise\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 582\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"astype\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    583\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    584\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mconvert\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/share/virtualenvs/repo-4rE-q4RG/lib/python3.8/site-packages/pandas/core/internals/managers.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self, f, filter, **kwargs)\u001b[0m\n\u001b[1;32m    440\u001b[0m                 \u001b[0mapplied\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    441\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 442\u001b[0;31m                 \u001b[0mapplied\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    443\u001b[0m             \u001b[0mresult_blocks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_extend_blocks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mapplied\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresult_blocks\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    444\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/share/virtualenvs/repo-4rE-q4RG/lib/python3.8/site-packages/pandas/core/internals/blocks.py\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[1;32m    623\u001b[0m             \u001b[0mvals1d\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    624\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 625\u001b[0;31m                 \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mastype_nansafe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvals1d\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    626\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mValueError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    627\u001b[0m                 \u001b[0;31m# e.g. astype_nansafe can fail on object-dtype of strings\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/share/virtualenvs/repo-4rE-q4RG/lib/python3.8/site-packages/pandas/core/dtypes/cast.py\u001b[0m in \u001b[0;36mastype_nansafe\u001b[0;34m(arr, dtype, copy, skipna)\u001b[0m\n\u001b[1;32m    872\u001b[0m         \u001b[0;31m# work around NumPy brokenness, #1987\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    873\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0missubdtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minteger\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 874\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype_intsafe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    875\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    876\u001b[0m         \u001b[0;31m# if we have a datetime/timedelta array of objects\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/lib.pyx\u001b[0m in \u001b[0;36mpandas._libs.lib.astype_intsafe\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: 'N/A'"
     ]
    }
   ],
   "source": [
    "payload = []\n",
    "\n",
    "for index, row in pdf_meta.iterrows():\n",
    "    payload.append(process_row(row))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Where is `'N/A'` coming from?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<pdfplumber.display.PageImage at 0x11a23e8e0>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdfplumber.open(\n",
    "    pdf_meta.iloc[1]['file_name']\n",
    ").pages[\n",
    "    pdf_meta.iloc[1]['table_page']\n",
    "].to_image(resolution=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our function needs a tweak to convert `'N/A'` to `0` so we can add up grievances."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_row(row):\n",
    "    pdf = pdfplumber.open(row['file_name'])\n",
    "    page = pdf.pages[row['table_page']]\n",
    "    page_count = row['pages']\n",
    "    \n",
    "    coordinate_grievances = list(filter(\n",
    "        lambda x: re.search(\n",
    "            pattern_grievance_table, x['text']\n",
    "        ),\n",
    "        page.extract_words()\n",
    "    ))[0]\n",
    "    \n",
    "    coordinate_left = coordinate_grievances['x1']\n",
    "    coordinate_right = page.width\n",
    "    \n",
    "    if row['pages'] == 9:\n",
    "        coordinate_top = coordinate_grievances['top'] - 5\n",
    "        coordinate_bottom = coordinate_grievances['top'] + 30\n",
    "        \n",
    "    else:\n",
    "        coordinate_left = coordinate_left + 100\n",
    "        coordinate_top = coordinate_grievances['top'] - 5\n",
    "        coordinate_bottom = coordinate_grievances['top'] + 30\n",
    "\n",
    "    crop_coordinates = (coordinate_left, coordinate_top, coordinate_right, coordinate_bottom)\n",
    "        \n",
    "        \n",
    "    page = page.within_bbox(crop_coordinates)\n",
    "    \n",
    "    if page_count == 9:\n",
    "        return pd.DataFrame(\n",
    "            page.extract_table({\n",
    "                'snap_tolerance': 8\n",
    "            }),\n",
    "            columns = [\n",
    "                'ice',\n",
    "                'non_ice',\n",
    "                'total'\n",
    "            ]\n",
    "        ).astype(int).assign(\n",
    "            total=lambda x: x['ice'] + x['non_ice'],\n",
    "            file=row['file_name']\n",
    "        )\n",
    "\n",
    "    else:\n",
    "        return pd.DataFrame(\n",
    "            page.extract_table(),\n",
    "            columns=[\n",
    "                'q1',\n",
    "                'q2',\n",
    "                'q3',\n",
    "                'q4'\n",
    "            ]\n",
    "        ).replace('N/A', 0).astype(int).assign(\n",
    "            total=lambda x: x.sum(axis=1),\n",
    "            file=row['file_name']\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "payload = []\n",
    "\n",
    "for index, row in pdf_meta.iterrows():\n",
    "    payload.append(process_row(row))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>file</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/catahoulaLA_SIS_08-22-2019.pdf</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/RVRCCLA_SIS_10-24-2019.pdf</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/LAWINCI_SIS_10-10-2019.pdf</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/RWCCMLA_SIS_10-03-2019.pdf</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/natchitochesDcLA_SIS_07-03-2019.pdf</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/jenaLaSalle_SIS_09-26-2019.pdf</td>\n",
       "      <td>492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pdf/allenParishDetFac_SIS_02-14-2019.pdf</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             file  total\n",
       "0  pdf/RiverCorrectionalCenter_SIS_12-06-2018.pdf    106\n",
       "0              pdf/catahoulaLA_SIS_08-22-2019.pdf      1\n",
       "0                  pdf/RVRCCLA_SIS_10-24-2019.pdf      0\n",
       "0                  pdf/LAWINCI_SIS_10-10-2019.pdf     22\n",
       "0                  pdf/RWCCMLA_SIS_10-03-2019.pdf      1\n",
       "0         pdf/natchitochesDcLA_SIS_07-03-2019.pdf      0\n",
       "0              pdf/jenaLaSalle_SIS_09-26-2019.pdf    492\n",
       "0        pdf/allenParishDetFac_SIS_02-14-2019.pdf      0"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat(payload)[['file', 'total']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Look at all the PDFs we parsed!\n",
    "\n",
    "But processing actually invovled quite a few things. We:\n",
    "\n",
    "- created pandas data frames about our data\n",
    "- wrote `for` loops\n",
    "- used regular expressions\n",
    "- filtered lists\n",
    "- used trial-and-error to find the perfect PDF coordinates\n",
    "- debugged errors\n",
    "\n",
    "pdfplumber helped collect data from the reports, but we also used [Overview](https://blog.overviewdocs.com/) to search text and OCR non-machine-readable documents we encountered."
   ]
  }
 ],
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