notebooks/analyze-fcc-comments.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis of comments in three FCC dockets\n",
    "\n",
    "This notebook contains Python code that runs the following steps:\n",
    "\n",
    "- Loading the four comment datasets under analysis (published comments for FCC dockets 14-28, 16-42, 17-108, plus bulk-uploaded comments for docket 17-108).\n",
    "\n",
    "\n",
    "- Classifying the comments for dockets 14-28 and 16-42, based on the language used in them.\n",
    "\n",
    "\n",
    "- Examining:\n",
    "\n",
    "    - How often email addresses the 17-108 bulk uploads appear in data breaches identified by [Have I Been Pwned](https://haveibeenpwned.com/)\n",
    "\n",
    "    - The overlap between comments in docket 16-42 and bulk-uploaded comments in docket 17-108\n",
    "\n",
    "    - The comments attributed to Annie Reeves vis-a-vis the timing and language used in American Commitment's docket 14-28 and docket 16-42 mass-comment campaigns.\n",
    "    \n",
    "__Please see this repository's landing page and associated BuzzFeed News article (linked on the landing page) for context before continuing.__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import Python libraries and set key variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standard libraries\n",
    "import os\n",
    "import sys\n",
    "import time\n",
    "import re\n",
    "\n",
    "# External libraries\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change this to True if you plan to reuse this notebook\n",
    "# and want to make HTTP requests to Have I Been Pwned's API\n",
    "\n",
    "MAKE_HTTP_REQUESTS = False\n",
    "\n",
    "if MAKE_HTTP_REQUESTS:\n",
    "    from tqdm.auto import tqdm\n",
    "    import requests\n",
    "    import requests_cache\n",
    "    \n",
    "    # This is the API key for Have I Been Pwned\n",
    "    HIBP_KEY = open(\"../hibp-key.txt\").read().strip()\n",
    "    \n",
    "    # Enables graphical progress bars when fetching HIPB data\n",
    "    tqdm.pandas()\n",
    "    \n",
    "    # For caching HTTP requests\n",
    "    requests_cache.install_cache(\n",
    "        \"../hibp-requests-cache\",\n",
    "        allowable_codes = (200, 404),\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "BASE_PATH = \"../data/\"\n",
    "\n",
    "# In the sampling procedures below, we use this \"random state\"\n",
    "# to make the samples reproducible. \n",
    "RANDOM_STATE = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_comments(path, **kwargs):\n",
    "    return (\n",
    "        pd.read_csv(\n",
    "            path,\n",
    "            dtype = str,\n",
    "            **kwargs\n",
    "        )\n",
    "        .astype({\n",
    "            \"email_address_nonstandard\": int\n",
    "        })\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Docket 17-108, bulk uploads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>comments</th>\n",
       "      <th>file</th>\n",
       "      <th>uploader</th>\n",
       "      <th>email_address_nonstandard</th>\n",
       "      <th>email_address</th>\n",
       "      <th>email_domain</th>\n",
       "      <th>name_and_location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>5/8/2017</td>\n",
       "      <td>Dear FCC, I am am writing today to SUPPORT net...</td>\n",
       "      <td>ecfs-input-template-17-108 (209).csv</td>\n",
       "      <td>kathleenkintz@gmail.com</td>\n",
       "      <td>0</td>\n",
       "      <td>9f664e24-96aa-4d96-b453-24d926658b47</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>5100f64f-b025-467f-9aa6-0100fa615ae6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>12/31/2017</td>\n",
       "      <td>Dear FCC, I am writing you today because I spe...</td>\n",
       "      <td>ecfs-input-template-17-108 (120).csv</td>\n",
       "      <td>vgboy522@gmail.com</td>\n",
       "      <td>0</td>\n",
       "      <td>818761bf-4c51-4970-95e6-11b01bac631f</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>dda3bd6b-9ad2-42d0-af15-f12c0b8a9354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>5/16/17</td>\n",
       "      <td>Obama's Federal Communications Commission (FCC...</td>\n",
       "      <td>TPA_3911_2017526.csv</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>0</td>\n",
       "      <td>f2cf802f-0c01-4d1f-b28f-0efef2a053ba</td>\n",
       "      <td>hotmail.com</td>\n",
       "      <td>d9b96c36-796e-45d1-97d8-00647ae09d89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>5/16/17</td>\n",
       "      <td>Obama's Federal Communications Commission (FCC...</td>\n",
       "      <td>TPA_3911_2017526.csv</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>0</td>\n",
       "      <td>6966ae39-6da6-4a47-a1ec-7dc854030634</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>f6d75f39-e952-41ff-b7a9-3d86da811496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5/16/17</td>\n",
       "      <td>Obama's Federal Communications Commission (FCC...</td>\n",
       "      <td>TPA_3911_2017526.csv</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>0</td>\n",
       "      <td>610afa24-f0df-44ff-b621-f545d371efab</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>1b3050d5-6f3a-495e-a67f-b3b61040fe02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date                                           comments  \\\n",
       "0    5/8/2017  Dear FCC, I am am writing today to SUPPORT net...   \n",
       "1  12/31/2017  Dear FCC, I am writing you today because I spe...   \n",
       "2     5/16/17  Obama's Federal Communications Commission (FCC...   \n",
       "3     5/16/17  Obama's Federal Communications Commission (FCC...   \n",
       "4     5/16/17  Obama's Federal Communications Commission (FCC...   \n",
       "\n",
       "                                   file                 uploader  \\\n",
       "0  ecfs-input-template-17-108 (209).csv  kathleenkintz@gmail.com   \n",
       "1  ecfs-input-template-17-108 (120).csv       vgboy522@gmail.com   \n",
       "2                  TPA_3911_2017526.csv           esmisc@mac.com   \n",
       "3                  TPA_3911_2017526.csv           esmisc@mac.com   \n",
       "4                  TPA_3911_2017526.csv           esmisc@mac.com   \n",
       "\n",
       "   email_address_nonstandard                         email_address  \\\n",
       "0                          0  9f664e24-96aa-4d96-b453-24d926658b47   \n",
       "1                          0  818761bf-4c51-4970-95e6-11b01bac631f   \n",
       "2                          0  f2cf802f-0c01-4d1f-b28f-0efef2a053ba   \n",
       "3                          0  6966ae39-6da6-4a47-a1ec-7dc854030634   \n",
       "4                          0  610afa24-f0df-44ff-b621-f545d371efab   \n",
       "\n",
       "  email_domain                     name_and_location  \n",
       "0    gmail.com  5100f64f-b025-467f-9aa6-0100fa615ae6  \n",
       "1    gmail.com  dda3bd6b-9ad2-42d0-af15-f12c0b8a9354  \n",
       "2  hotmail.com  d9b96c36-796e-45d1-97d8-00647ae09d89  \n",
       "3    gmail.com  f6d75f39-e952-41ff-b7a9-3d86da811496  \n",
       "4    gmail.com  1b3050d5-6f3a-495e-a67f-b3b61040fe02  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bulk_uploads_17_108 = load_comments(BASE_PATH + \"bulk-uploads-17-108-with-uuids.csv\")\n",
    "\n",
    "bulk_uploads_17_108.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Examine bulk-uploader metrics for 17-108"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>submissions</th>\n",
       "      <th>unique_emails</th>\n",
       "      <th>prop_with_email</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uploader</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>4347979</td>\n",
       "      <td>3966016</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>1856553</td>\n",
       "      <td>1501145</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mike@fightforthefuture.org</td>\n",
       "      <td>1464423</td>\n",
       "      <td>129682</td>\n",
       "      <td>0.2464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>karen@momsrising.org</td>\n",
       "      <td>1069368</td>\n",
       "      <td>17870</td>\n",
       "      <td>0.0362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>dutch@freepress.net</td>\n",
       "      <td>528607</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>kurt@demandprogress.org</td>\n",
       "      <td>412792</td>\n",
       "      <td>290372</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fccfreedom@hmamail.com</td>\n",
       "      <td>207007</td>\n",
       "      <td>122252</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>advocacy@mozilla.com</td>\n",
       "      <td>82926</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>action@aclu.org</td>\n",
       "      <td>48733</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>meaghan@mandatemedia.com</td>\n",
       "      <td>17317</td>\n",
       "      <td>16267</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ncatalano@ofa.us</td>\n",
       "      <td>12230</td>\n",
       "      <td>12230</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            submissions  unique_emails  prop_with_email\n",
       "uploader                                                               \n",
       "esmisc@mac.com                  4347979        3966016           1.0000\n",
       "shane@mediabridgellc.com        1856553        1501145           1.0000\n",
       "mike@fightforthefuture.org      1464423         129682           0.2464\n",
       "karen@momsrising.org            1069368          17870           0.0362\n",
       "dutch@freepress.net              528607              3           0.0000\n",
       "kurt@demandprogress.org          412792         290372           1.0000\n",
       "fccfreedom@hmamail.com           207007         122252           1.0000\n",
       "advocacy@mozilla.com              82926              0           0.0000\n",
       "action@aclu.org                   48733              0           0.0000\n",
       "meaghan@mandatemedia.com          17317          16267           1.0000\n",
       "ncatalano@ofa.us                  12230          12230           1.0000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uploader_metrics = (\n",
    "    bulk_uploads_17_108\n",
    "    .assign(\n",
    "        prop_with_email = lambda df: df[\"email_address\"].notnull()\n",
    "    )\n",
    "    .groupby(\"uploader\")\n",
    "    .pipe(lambda grp: pd.DataFrame({\n",
    "        \"submissions\": grp.size(),\n",
    "        \"unique_emails\": grp[\"email_address\"].nunique(),        \n",
    "        \"prop_with_email\": grp[\"prop_with_email\"].mean().round(4),\n",
    "    }))\n",
    ")\n",
    "    \n",
    "(\n",
    "    uploader_metrics\n",
    "    .sort_values(\"submissions\", ascending = False)\n",
    "    .loc[lambda df: df[\"submissions\"] >= 10000]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Docket 17-108, all comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id_submission</th>\n",
       "      <th>date</th>\n",
       "      <th>email_address_nonstandard</th>\n",
       "      <th>email_address</th>\n",
       "      <th>email_domain</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>04272972619149</td>\n",
       "      <td>2017-04-27</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0427547924954</td>\n",
       "      <td>2017-04-27</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>10427918117987</td>\n",
       "      <td>2017-04-27</td>\n",
       "      <td>0</td>\n",
       "      <td>1f4830aa-726c-4206-9bef-cb3f2a57bb20</td>\n",
       "      <td>gmail.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>10427080530667</td>\n",
       "      <td>2017-04-27</td>\n",
       "      <td>0</td>\n",
       "      <td>f10d9c2b-2c98-44c2-9c7a-fe57b96930d8</td>\n",
       "      <td>gmail.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1042709110034</td>\n",
       "      <td>2017-04-27</td>\n",
       "      <td>0</td>\n",
       "      <td>a6609a29-4b4c-4857-9e42-a886f61b8aaa</td>\n",
       "      <td>d6b158e4-d116-4944-ab88-73091f1fc465</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id_submission        date  email_address_nonstandard  \\\n",
       "0  04272972619149  2017-04-27                          0   \n",
       "1   0427547924954  2017-04-27                          0   \n",
       "2  10427918117987  2017-04-27                          0   \n",
       "3  10427080530667  2017-04-27                          0   \n",
       "4   1042709110034  2017-04-27                          0   \n",
       "\n",
       "                          email_address                          email_domain  \n",
       "0                                   NaN                                   NaN  \n",
       "1                                   NaN                                   NaN  \n",
       "2  1f4830aa-726c-4206-9bef-cb3f2a57bb20                             gmail.com  \n",
       "3  f10d9c2b-2c98-44c2-9c7a-fe57b96930d8                             gmail.com  \n",
       "4  a6609a29-4b4c-4857-9e42-a886f61b8aaa  d6b158e4-d116-4944-ab88-73091f1fc465  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comments_17_108 = (\n",
    "    load_comments(BASE_PATH + \"comments-17-108-with-uuids.csv\")\n",
    "    .assign(date = lambda df: df[\"date\"].str.slice(0, 10))\n",
    ")\n",
    "\n",
    "comments_17_108.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Examine email domains attributed to these comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>unique_addresses</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_domain</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>gmail.com</td>\n",
       "      <td>5000687</td>\n",
       "      <td>4160788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>yahoo.com</td>\n",
       "      <td>2536892</td>\n",
       "      <td>2126544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>hotmail.com</td>\n",
       "      <td>673018</td>\n",
       "      <td>571156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>aol.com</td>\n",
       "      <td>632971</td>\n",
       "      <td>508087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>pornhub.com</td>\n",
       "      <td>1030003</td>\n",
       "      <td>233516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>comcast.net</td>\n",
       "      <td>208512</td>\n",
       "      <td>158939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>icloud.com</td>\n",
       "      <td>106442</td>\n",
       "      <td>91091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>msn.com</td>\n",
       "      <td>110056</td>\n",
       "      <td>89398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>hurra.de</td>\n",
       "      <td>363357</td>\n",
       "      <td>88571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>outlook.com</td>\n",
       "      <td>79411</td>\n",
       "      <td>67890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>att.net</td>\n",
       "      <td>79823</td>\n",
       "      <td>60640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>live.com</td>\n",
       "      <td>70139</td>\n",
       "      <td>59210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>sbcglobal.net</td>\n",
       "      <td>70126</td>\n",
       "      <td>51206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>yahoo.fr</td>\n",
       "      <td>93389</td>\n",
       "      <td>48034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ymail.com</td>\n",
       "      <td>45036</td>\n",
       "      <td>37515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>bellsouth.net</td>\n",
       "      <td>40432</td>\n",
       "      <td>32155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>cox.net</td>\n",
       "      <td>40137</td>\n",
       "      <td>31260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>verizon.net</td>\n",
       "      <td>41933</td>\n",
       "      <td>29236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>yahoo.de</td>\n",
       "      <td>97977</td>\n",
       "      <td>28310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mail.ru</td>\n",
       "      <td>60608</td>\n",
       "      <td>24570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>me.com</td>\n",
       "      <td>26000</td>\n",
       "      <td>19559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>charter.net</td>\n",
       "      <td>24425</td>\n",
       "      <td>18487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>einrot.com</td>\n",
       "      <td>793148</td>\n",
       "      <td>17091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>gustr.com</td>\n",
       "      <td>769010</td>\n",
       "      <td>16813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>rhyta.com</td>\n",
       "      <td>773757</td>\n",
       "      <td>16756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>jourrapide.com</td>\n",
       "      <td>782650</td>\n",
       "      <td>16746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>armyspy.com</td>\n",
       "      <td>780664</td>\n",
       "      <td>16741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>dayrep.com</td>\n",
       "      <td>770023</td>\n",
       "      <td>16733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>superrito.com</td>\n",
       "      <td>767495</td>\n",
       "      <td>16684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>teleworm.us</td>\n",
       "      <td>765488</td>\n",
       "      <td>16673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>cuvox.de</td>\n",
       "      <td>775904</td>\n",
       "      <td>16623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fleckens.hu</td>\n",
       "      <td>776092</td>\n",
       "      <td>16600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mail.com</td>\n",
       "      <td>16392</td>\n",
       "      <td>14657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>rocketmail.com</td>\n",
       "      <td>17112</td>\n",
       "      <td>14266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>windstream.net</td>\n",
       "      <td>13496</td>\n",
       "      <td>11107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>earthlink.net</td>\n",
       "      <td>18068</td>\n",
       "      <td>11088</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  count  unique_addresses\n",
       "email_domain                             \n",
       "gmail.com       5000687           4160788\n",
       "yahoo.com       2536892           2126544\n",
       "hotmail.com      673018            571156\n",
       "aol.com          632971            508087\n",
       "pornhub.com     1030003            233516\n",
       "comcast.net      208512            158939\n",
       "icloud.com       106442             91091\n",
       "msn.com          110056             89398\n",
       "hurra.de         363357             88571\n",
       "outlook.com       79411             67890\n",
       "att.net           79823             60640\n",
       "live.com          70139             59210\n",
       "sbcglobal.net     70126             51206\n",
       "yahoo.fr          93389             48034\n",
       "ymail.com         45036             37515\n",
       "bellsouth.net     40432             32155\n",
       "cox.net           40137             31260\n",
       "verizon.net       41933             29236\n",
       "yahoo.de          97977             28310\n",
       "mail.ru           60608             24570\n",
       "me.com            26000             19559\n",
       "charter.net       24425             18487\n",
       "einrot.com       793148             17091\n",
       "gustr.com        769010             16813\n",
       "rhyta.com        773757             16756\n",
       "jourrapide.com   782650             16746\n",
       "armyspy.com      780664             16741\n",
       "dayrep.com       770023             16733\n",
       "superrito.com    767495             16684\n",
       "teleworm.us      765488             16673\n",
       "cuvox.de         775904             16623\n",
       "fleckens.hu      776092             16600\n",
       "mail.com          16392             14657\n",
       "rocketmail.com    17112             14266\n",
       "windstream.net    13496             11107\n",
       "earthlink.net     18068             11088"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "email_domains_17_108 = (\n",
    "    comments_17_108\n",
    "    .groupby([ \"email_domain\" ])\n",
    "    .pipe(lambda grp: pd.DataFrame({\n",
    "        \"count\": grp.size(),\n",
    "        \"unique_addresses\": grp[\"email_address\"].nunique()\n",
    "    }))\n",
    "    .sort_values([ \"count\", \"unique_addresses\" ], ascending = False)\n",
    ")\n",
    "\n",
    "(\n",
    "    email_domains_17_108\n",
    "    .loc[lambda df: df[\"unique_addresses\"] >= 10000]\n",
    "    .sort_values(\"unique_addresses\", ascending = False)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we count the comments and unique email addresses associated with FakeMailGenerator.com:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "FAKEMAIL_DOMAINS = [\n",
    "    \"einrot.com\",\n",
    "    \"jourrapide.com\",\n",
    "    \"armyspy.com\",\n",
    "    \"fleckens.hu\",\n",
    "    \"cuvox.de\",\n",
    "    \"rhyta.com\",\n",
    "    \"dayrep.com\",\n",
    "    \"gustr.com\",\n",
    "    \"superrito.com\",\n",
    "    \"teleworm.us\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>7754231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>unique_addresses</td>\n",
       "      <td>167460</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    count\n",
       "count             7754231\n",
       "unique_addresses   167460"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    email_domains_17_108\n",
    "    .loc[FAKEMAIL_DOMAINS]\n",
    "    [[\"count\", \"unique_addresses\"]]\n",
    "    .sum()\n",
    "    .to_frame(\"count\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Docket 16-42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>date</th>\n",
       "      <th>id_submission</th>\n",
       "      <th>comments</th>\n",
       "      <th>email_address_nonstandard</th>\n",
       "      <th>email_address</th>\n",
       "      <th>email_domain</th>\n",
       "      <th>name_and_location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2016-02-19</td>\n",
       "      <td>60001483702</td>\n",
       "      <td>60001515146.txtThank you!  Very pleased to see...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8ad10c4e-1354-42ba-83f1-be6b3c89f331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2016-02-22</td>\n",
       "      <td>60001484317</td>\n",
       "      <td>60001843102.txt[5/23/2016 7:55:30 PM]The excha...</td>\n",
       "      <td>0</td>\n",
       "      <td>310d8308-43a0-4b84-93dc-6662acdef829</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>d984ccab-11bb-4994-bcfe-f0d407fd03b5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2016-02-25</td>\n",
       "      <td>60001486876</td>\n",
       "      <td>60001518518.txtPlease eliminate the cable TV b...</td>\n",
       "      <td>0</td>\n",
       "      <td>7e6087df-a7a2-414f-8ebb-3be229805bec</td>\n",
       "      <td>yahoo.com</td>\n",
       "      <td>298bb4d9-8130-4ced-86e9-6a5d0c740c66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2016-02-27</td>\n",
       "      <td>60001489444</td>\n",
       "      <td>I?support?the?FCC?allowing?homeowners?to?be?fr...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12614861-1a8f-4313-aeff-2366bcf18ca8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>60001492083</td>\n",
       "      <td>60001523826.txtAs a consumer, I agree with the...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10268573-9386-42c7-ab31-4d76641e76ed</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date id_submission  \\\n",
       "0  2016-02-19   60001483702   \n",
       "1  2016-02-22   60001484317   \n",
       "2  2016-02-25   60001486876   \n",
       "3  2016-02-27   60001489444   \n",
       "4  2016-02-29   60001492083   \n",
       "\n",
       "                                            comments  \\\n",
       "0  60001515146.txtThank you!  Very pleased to see...   \n",
       "1  60001843102.txt[5/23/2016 7:55:30 PM]The excha...   \n",
       "2  60001518518.txtPlease eliminate the cable TV b...   \n",
       "3  I?support?the?FCC?allowing?homeowners?to?be?fr...   \n",
       "4  60001523826.txtAs a consumer, I agree with the...   \n",
       "\n",
       "   email_address_nonstandard                         email_address  \\\n",
       "0                          0                                   NaN   \n",
       "1                          0  310d8308-43a0-4b84-93dc-6662acdef829   \n",
       "2                          0  7e6087df-a7a2-414f-8ebb-3be229805bec   \n",
       "3                          0                                   NaN   \n",
       "4                          0                                   NaN   \n",
       "\n",
       "  email_domain                     name_and_location  \n",
       "0          NaN  8ad10c4e-1354-42ba-83f1-be6b3c89f331  \n",
       "1    gmail.com  d984ccab-11bb-4994-bcfe-f0d407fd03b5  \n",
       "2    yahoo.com  298bb4d9-8130-4ced-86e9-6a5d0c740c66  \n",
       "3          NaN  12614861-1a8f-4313-aeff-2366bcf18ca8  \n",
       "4          NaN  10268573-9386-42c7-ab31-4d76641e76ed  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comments_16_42 = (\n",
    "    load_comments(BASE_PATH + \"comments-16-42-with-uuids.csv\")\n",
    "    .assign(date = lambda df: df[\"date\"].str.slice(0, 10))\n",
    ")    \n",
    "\n",
    "comments_16_42.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Docket 14-28"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>date</th>\n",
       "      <th>id_submission</th>\n",
       "      <th>comments</th>\n",
       "      <th>email_address_nonstandard</th>\n",
       "      <th>email_address</th>\n",
       "      <th>email_domain</th>\n",
       "      <th>name_and_location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2014-02-21</td>\n",
       "      <td>6017589853</td>\n",
       "      <td>7521074305.txt Reclassify The Internet As A Co...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a0fad65b-1482-427d-b300-da8e63d14272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2014-02-21</td>\n",
       "      <td>6017589866</td>\n",
       "      <td>7521074318.txt Reclassify The Internet As A Co...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45954c7c-d52d-48f0-a252-343b4f82e509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2014-02-21</td>\n",
       "      <td>6017589903</td>\n",
       "      <td>7521074355.txt Reclassify The Internet As A Co...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0a1dea8a-3ae6-434f-be03-4b6447c3190c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2014-02-21</td>\n",
       "      <td>6017589904</td>\n",
       "      <td>7521074356.txt Reclassify The Internet As A Co...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5cb3b14f-71a4-4763-8bd1-40ad440c5eb8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2014-02-21</td>\n",
       "      <td>6017589924</td>\n",
       "      <td>7521074376.txt Reclassify The Internet As A Co...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0de47b78-a256-4e36-93ad-1f4830b07c48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date id_submission  \\\n",
       "0  2014-02-21    6017589853   \n",
       "1  2014-02-21    6017589866   \n",
       "2  2014-02-21    6017589903   \n",
       "3  2014-02-21    6017589904   \n",
       "4  2014-02-21    6017589924   \n",
       "\n",
       "                                            comments  \\\n",
       "0  7521074305.txt Reclassify The Internet As A Co...   \n",
       "1  7521074318.txt Reclassify The Internet As A Co...   \n",
       "2  7521074355.txt Reclassify The Internet As A Co...   \n",
       "3  7521074356.txt Reclassify The Internet As A Co...   \n",
       "4  7521074376.txt Reclassify The Internet As A Co...   \n",
       "\n",
       "   email_address_nonstandard email_address email_domain  \\\n",
       "0                          0           NaN          NaN   \n",
       "1                          0           NaN          NaN   \n",
       "2                          0           NaN          NaN   \n",
       "3                          0           NaN          NaN   \n",
       "4                          0           NaN          NaN   \n",
       "\n",
       "                      name_and_location  \n",
       "0  a0fad65b-1482-427d-b300-da8e63d14272  \n",
       "1  45954c7c-d52d-48f0-a252-343b4f82e509  \n",
       "2  0a1dea8a-3ae6-434f-be03-4b6447c3190c  \n",
       "3  5cb3b14f-71a4-4763-8bd1-40ad440c5eb8  \n",
       "4  0de47b78-a256-4e36-93ad-1f4830b07c48  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comments_14_28 = (\n",
    "    load_comments(BASE_PATH + \"comments-14-28-with-uuids.csv\")\n",
    "    .assign(date = lambda df: df[\"date\"].str.slice(0, 10))\n",
    ")    \n",
    "\n",
    "comments_14_28.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classify comments\n",
    "\n",
    "In this step, we create derivative dataframes that classify each comment based on the language used in them. (Note: Because the formatting of comments can be inconsistent, the classification approach ignores whitespace.)\n",
    "\n",
    "The classifier takes a series of texts and a series of patterns to look for. Each text is labeled based on the __first__ pattern it matches, based on the sequential order of the patterns; if the text matches no pattern, it is labeled `[other]`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def classify(texts, patterns):\n",
    "    # Create a copy of the texts and remove whitespace\n",
    "    s = texts.copy().str.replace(r\"\\s+\", \"\")\n",
    "    \n",
    "    # Remove whitespace from classification patterns\n",
    "    without_whitespace = [ (re.sub(r\"\\s+\", \"\", pat), val)\n",
    "        for pat, val in patterns ]\n",
    "    \n",
    "    # An empty series, indexed identically to the original texts.\n",
    "    ix = pd.Series(None, index = texts.index)\n",
    "\n",
    "    # As we progress through the matching, we will gradually\n",
    "    # fill `ix` in with the matches we've found.\n",
    "    \n",
    "    # Iterate through the classification patterns\n",
    "    for pat, val in without_whitespace:\n",
    "        # Determine which texts match\n",
    "        search_result = s.str.contains(pat, na = False)\n",
    "        matches = search_result.loc[lambda x: x == True]\n",
    "        \n",
    "        # For matches, update `ix` to indicate the pattern ID/description\n",
    "        ix.loc[matches.index] = val\n",
    "        \n",
    "        # Subset `s` so that it only contains unmatched texts\n",
    "        s = s.loc[s.index.difference(matches.index)]\n",
    "\n",
    "    return ix.fillna(\"[other]\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_classification(df, patterns):\n",
    "    return (\n",
    "        df\n",
    "        .assign(group = lambda df: (\n",
    "            df[\"comments\"]\n",
    "            .pipe(classify, patterns)\n",
    "        ))\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_example_comments(df, n = 3, max_chars = 500):\n",
    "    for grp, subdf in df.groupby(\"group\"):\n",
    "        print(f\"=== {grp} ===\\n\")\n",
    "        \n",
    "        examples = (\n",
    "            subdf[\"comments\"]\n",
    "            .sample(n, random_state = RANDOM_STATE)\n",
    "            .pipe(lambda x: pd.np.where(\n",
    "                x.apply(len) > max_chars,\n",
    "                x.str.slice(0, max_chars) + \"[...]\",\n",
    "                x\n",
    "            ))\n",
    "        )\n",
    "        \n",
    "        print(\"\\n\\n\".join(examples) + \"\\n\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Docket 14-28\n",
    "\n",
    "BuzzFeed News identified the phrases below based on extensive examination of the 14-28 docket, and by cross-referencing them with [this December 2014 Sunlight Foundation analysis](http://web.archive.org/web/20150301070951/http://sunlightfoundation.com/blog/2014/12/16/one-group-dominates-the-second-round-of-net-neutrality-comments/).\n",
    "\n",
    "The `AC-` comments use language from American Commitment's comment campaign. It is possible that entities other than American Commitment submitted comments that used the same language. \n",
    "\n",
    "Note: The final phrase in the list below also appears alongside some of the other permutations; but because it is the final phrase in the list, only comments that don't match the other phrasings receive this classification.\n",
    "\n",
    "Please see this repository's landing page, and the associated BuzzFeed News article, for additional context. (E.g., not all comments are indivudally retreivable from the FCC's public portal.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "ac_patterns_main = [\n",
    "    # Earlier set of comments\n",
    "    \"The federal government can use their power over the internet to direct content\", \n",
    "    \"because of high barriers to entry and a disastrous lack of competition\", \n",
    "    \"federal bureaucrats will slow down the process and protect prevailing interests first\", \n",
    "    \"blossoming in America today, largely due to the internet\", \n",
    "    \"Government will make it impossible for internet providers to upgrade service\", \n",
    "    \"government will naturally favor entrenched special interests, rather than upstart companies\", \n",
    "    \"will begin to be mismanaged, like many other government-run industries\", \n",
    "    \"put directly in the hands of bureaucrats, instead of the free market\", \n",
    "    \"will result in worse service, even as costs continue to skyrocket\", \n",
    "    \"Our options for cheap, high-speed, high-performing internet providers\", \n",
    "\n",
    "    # Later set of comments\n",
    "    \"Left-wing extremists have been crying wolf\", \n",
    "    \"The federal government needs to keep its hands off the Internet\", \n",
    "    \"Before the FCC places regulatory handcuffs on Internet providers\", \n",
    "    \"The notion that the internet is broken and needs repair is simply not true\", \n",
    "    \"will send the crown jewel of the US economy into an economic tailspin\", \n",
    "    \"no longer acting in the interests of the American people\", \n",
    "    \"just another slow-moving government-controlled mess\", \n",
    "    \"defend ourselves against power-hungry bureaucrats\", \n",
    "    \"simply another attempt by the federal government to take control of another sector of the economy\", \n",
    "    \"Millions of liberal fools demanding you reduce the Internet\", \n",
    "    \"FCC is clearly ignoring the will of the American people\", \n",
    "    \"devastate private investment with the force of an atomic bomb\", \n",
    "    \"without being slowed by bureaucratic inertia\", \n",
    "    \"A small fringe of the extremist left has been demanding\", \n",
    "    \"a tiny minority of far-left political activists\", \n",
    "    \"ultimate goal is to get rid of the media capitalists\", \n",
    "    \"created economic and human wreckage in their wake\", \n",
    "    \"increase its own power at the expense of the free people\", \n",
    "    \"it will have proven itself to be an unaccountable agency\", \n",
    "    \"subjecting it to 1930s-style regulations meant for telephone monopolies\", \n",
    "    \"Government regulation of Internet services would chase investment\", \n",
    "    \"it will seriously degrade the Internet we have\", \n",
    "    \"it can and should suffer the consequences\", \n",
    "    \"taking such reckless actions to gain control over the Internet\", \n",
    "    \"simply is no evidence to back up the dire claims of disaster\", \n",
    "]\n",
    "\n",
    "ac_patterns_other = [\n",
    "    \"Like many Americans, I believe that the internet should remain free of government\",\n",
    "    \"As an American citizen, I wanted to voice my opposition to the FCC\",\n",
    "]\n",
    "\n",
    "ac_pattern_desciptions = (\n",
    "    [ (p, f\"AC-{i:02d}\") for i, p in enumerate(ac_patterns_main) ] +\n",
    "    [ (p, f\"AC-other\") for p in ac_patterns_other ]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notes:\n",
    "\n",
    "- The `AC-XX` classification names below are based simply on the order in which they appear above. The numbers have no independent meaning.\n",
    "\n",
    "- The `AC-other` classification indicates that key language (the two phrases in `ac_patterns_other` above) from American Commitment appears in the comment, but not any of the other phrases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AC-00          1261\n",
       "AC-01          1233\n",
       "AC-02          1246\n",
       "AC-03          1232\n",
       "AC-04          1269\n",
       "AC-05          1208\n",
       "AC-06          1210\n",
       "AC-07          1207\n",
       "AC-08          1202\n",
       "AC-09          1186\n",
       "AC-10         25801\n",
       "AC-11         25781\n",
       "AC-12         25951\n",
       "AC-13         26012\n",
       "AC-14         25667\n",
       "AC-15         25879\n",
       "AC-16         25727\n",
       "AC-17         26009\n",
       "AC-18         25658\n",
       "AC-19         25788\n",
       "AC-20         25924\n",
       "AC-21         25914\n",
       "AC-22         25950\n",
       "AC-23         25865\n",
       "AC-24         25864\n",
       "AC-25         25620\n",
       "AC-26         26044\n",
       "AC-27         25932\n",
       "AC-28         25745\n",
       "AC-29         26024\n",
       "AC-30         25624\n",
       "AC-31         25880\n",
       "AC-32         25691\n",
       "AC-33         25615\n",
       "AC-34         25836\n",
       "AC-other          6\n",
       "[other]     1396620\n",
       "Name: group, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comments_14_28_classified = (\n",
    "    comments_14_28\n",
    "    .pipe(\n",
    "        add_classification,\n",
    "        ac_pattern_desciptions\n",
    "    )\n",
    ")\n",
    "\n",
    "(\n",
    "    comments_14_28_classified\n",
    "    [\"group\"]\n",
    "    .value_counts()\n",
    "    .sort_index()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The total number of comments and unique email addreses for all `AC-`-classified comments above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>comments</td>\n",
       "      <td>658061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>unique_email_addresses</td>\n",
       "      <td>551855</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         count\n",
       "comments                658061\n",
       "unique_email_addresses  551855"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    comments_14_28_classified\n",
    "    .loc[lambda df: df[\"group\"] != \"[other]\"]\n",
    "    .pipe(lambda df: pd.Series({\n",
    "        \"comments\": len(df),\n",
    "        \"unique_email_addresses\": df[\"email_address\"].nunique()\n",
    "    }))\n",
    "    .to_frame(\"count\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Dates submitted\n",
    "\n",
    "The analysis below demonstrates that the following:\n",
    "\n",
    "- Comments `AC-00`-`AC-09` share a similar distribution of dates submitted\n",
    "- Comments `AC-10`-`AC-34` also share a similar distribution of dates submitted, but distinct from `AC-00`-`AC-09`\n",
    "\n",
    "Additional notes:\n",
    "\n",
    "- Dates below are `MM-DD`, for 2014\n",
    "\n",
    "- Dates include only those with at least 200 total `AC-` classified comments (overall), to reduce noise of stray dates that contain relatively few matching comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>date</th>\n",
       "      <th>07-14</th>\n",
       "      <th>07-16</th>\n",
       "      <th>07-17</th>\n",
       "      <th>09-11</th>\n",
       "      <th>09-12</th>\n",
       "      <th>09-13</th>\n",
       "      <th>09-14</th>\n",
       "      <th>09-15</th>\n",
       "      <th>09-16</th>\n",
       "      <th>09-17</th>\n",
       "      <th>09-18</th>\n",
       "      <th>09-19</th>\n",
       "      <th>09-22</th>\n",
       "      <th>09-23</th>\n",
       "      <th>09-24</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>AC-00</td>\n",
       "      <td>45</td>\n",
       "      <td>909</td>\n",
       "      <td>305</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-01</td>\n",
       "      <td>39</td>\n",
       "      <td>905</td>\n",
       "      <td>287</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-02</td>\n",
       "      <td>52</td>\n",
       "      <td>888</td>\n",
       "      <td>304</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-03</td>\n",
       "      <td>45</td>\n",
       "      <td>893</td>\n",
       "      <td>293</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-04</td>\n",
       "      <td>80</td>\n",
       "      <td>902</td>\n",
       "      <td>284</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-05</td>\n",
       "      <td>36</td>\n",
       "      <td>872</td>\n",
       "      <td>300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-06</td>\n",
       "      <td>47</td>\n",
       "      <td>906</td>\n",
       "      <td>257</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-07</td>\n",
       "      <td>48</td>\n",
       "      <td>859</td>\n",
       "      <td>299</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-08</td>\n",
       "      <td>45</td>\n",
       "      <td>854</td>\n",
       "      <td>303</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-09</td>\n",
       "      <td>44</td>\n",
       "      <td>878</td>\n",
       "      <td>263</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2478</td>\n",
       "      <td>3896</td>\n",
       "      <td>4591</td>\n",
       "      <td>3510</td>\n",
       "      <td>6458</td>\n",
       "      <td>2167</td>\n",
       "      <td>2143</td>\n",
       "      <td>225</td>\n",
       "      <td>63</td>\n",
       "      <td>112</td>\n",
       "      <td>80</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2483</td>\n",
       "      <td>3911</td>\n",
       "      <td>4613</td>\n",
       "      <td>3574</td>\n",
       "      <td>6365</td>\n",
       "      <td>2204</td>\n",
       "      <td>2097</td>\n",
       "      <td>231</td>\n",
       "      <td>74</td>\n",
       "      <td>118</td>\n",
       "      <td>75</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2481</td>\n",
       "      <td>3897</td>\n",
       "      <td>4577</td>\n",
       "      <td>3550</td>\n",
       "      <td>6527</td>\n",
       "      <td>2207</td>\n",
       "      <td>2197</td>\n",
       "      <td>224</td>\n",
       "      <td>76</td>\n",
       "      <td>112</td>\n",
       "      <td>79</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2488</td>\n",
       "      <td>3909</td>\n",
       "      <td>4604</td>\n",
       "      <td>3605</td>\n",
       "      <td>6438</td>\n",
       "      <td>2252</td>\n",
       "      <td>2180</td>\n",
       "      <td>241</td>\n",
       "      <td>72</td>\n",
       "      <td>123</td>\n",
       "      <td>82</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2470</td>\n",
       "      <td>3911</td>\n",
       "      <td>4528</td>\n",
       "      <td>3541</td>\n",
       "      <td>6278</td>\n",
       "      <td>2234</td>\n",
       "      <td>2168</td>\n",
       "      <td>256</td>\n",
       "      <td>71</td>\n",
       "      <td>119</td>\n",
       "      <td>75</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2470</td>\n",
       "      <td>3893</td>\n",
       "      <td>4572</td>\n",
       "      <td>3540</td>\n",
       "      <td>6451</td>\n",
       "      <td>2269</td>\n",
       "      <td>2144</td>\n",
       "      <td>254</td>\n",
       "      <td>75</td>\n",
       "      <td>117</td>\n",
       "      <td>77</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2477</td>\n",
       "      <td>3917</td>\n",
       "      <td>4562</td>\n",
       "      <td>3541</td>\n",
       "      <td>6385</td>\n",
       "      <td>2196</td>\n",
       "      <td>2144</td>\n",
       "      <td>231</td>\n",
       "      <td>69</td>\n",
       "      <td>108</td>\n",
       "      <td>83</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2496</td>\n",
       "      <td>3907</td>\n",
       "      <td>4509</td>\n",
       "      <td>3558</td>\n",
       "      <td>6511</td>\n",
       "      <td>2249</td>\n",
       "      <td>2290</td>\n",
       "      <td>231</td>\n",
       "      <td>64</td>\n",
       "      <td>105</td>\n",
       "      <td>74</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2498</td>\n",
       "      <td>3903</td>\n",
       "      <td>4569</td>\n",
       "      <td>3584</td>\n",
       "      <td>6352</td>\n",
       "      <td>2190</td>\n",
       "      <td>2067</td>\n",
       "      <td>229</td>\n",
       "      <td>55</td>\n",
       "      <td>117</td>\n",
       "      <td>80</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2475</td>\n",
       "      <td>3924</td>\n",
       "      <td>4525</td>\n",
       "      <td>3491</td>\n",
       "      <td>6523</td>\n",
       "      <td>2183</td>\n",
       "      <td>2165</td>\n",
       "      <td>258</td>\n",
       "      <td>58</td>\n",
       "      <td>94</td>\n",
       "      <td>77</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2481</td>\n",
       "      <td>3910</td>\n",
       "      <td>4568</td>\n",
       "      <td>3572</td>\n",
       "      <td>6562</td>\n",
       "      <td>2153</td>\n",
       "      <td>2150</td>\n",
       "      <td>236</td>\n",
       "      <td>86</td>\n",
       "      <td>113</td>\n",
       "      <td>79</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-21</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2476</td>\n",
       "      <td>3900</td>\n",
       "      <td>4573</td>\n",
       "      <td>3463</td>\n",
       "      <td>6493</td>\n",
       "      <td>2297</td>\n",
       "      <td>2188</td>\n",
       "      <td>239</td>\n",
       "      <td>75</td>\n",
       "      <td>113</td>\n",
       "      <td>83</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2486</td>\n",
       "      <td>3886</td>\n",
       "      <td>4557</td>\n",
       "      <td>3522</td>\n",
       "      <td>6507</td>\n",
       "      <td>2225</td>\n",
       "      <td>2240</td>\n",
       "      <td>241</td>\n",
       "      <td>82</td>\n",
       "      <td>110</td>\n",
       "      <td>81</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2484</td>\n",
       "      <td>3917</td>\n",
       "      <td>4612</td>\n",
       "      <td>3492</td>\n",
       "      <td>6441</td>\n",
       "      <td>2171</td>\n",
       "      <td>2246</td>\n",
       "      <td>235</td>\n",
       "      <td>68</td>\n",
       "      <td>108</td>\n",
       "      <td>77</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2469</td>\n",
       "      <td>3908</td>\n",
       "      <td>4637</td>\n",
       "      <td>3511</td>\n",
       "      <td>6507</td>\n",
       "      <td>2175</td>\n",
       "      <td>2169</td>\n",
       "      <td>222</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>78</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2472</td>\n",
       "      <td>3900</td>\n",
       "      <td>4562</td>\n",
       "      <td>3482</td>\n",
       "      <td>6426</td>\n",
       "      <td>2099</td>\n",
       "      <td>2191</td>\n",
       "      <td>240</td>\n",
       "      <td>64</td>\n",
       "      <td>95</td>\n",
       "      <td>78</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2491</td>\n",
       "      <td>3916</td>\n",
       "      <td>4581</td>\n",
       "      <td>3575</td>\n",
       "      <td>6462</td>\n",
       "      <td>2257</td>\n",
       "      <td>2210</td>\n",
       "      <td>248</td>\n",
       "      <td>82</td>\n",
       "      <td>131</td>\n",
       "      <td>78</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2483</td>\n",
       "      <td>3896</td>\n",
       "      <td>4599</td>\n",
       "      <td>3630</td>\n",
       "      <td>6440</td>\n",
       "      <td>2195</td>\n",
       "      <td>2192</td>\n",
       "      <td>241</td>\n",
       "      <td>70</td>\n",
       "      <td>95</td>\n",
       "      <td>76</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2475</td>\n",
       "      <td>3914</td>\n",
       "      <td>4566</td>\n",
       "      <td>3542</td>\n",
       "      <td>6366</td>\n",
       "      <td>2233</td>\n",
       "      <td>2140</td>\n",
       "      <td>233</td>\n",
       "      <td>62</td>\n",
       "      <td>123</td>\n",
       "      <td>75</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2477</td>\n",
       "      <td>3896</td>\n",
       "      <td>4651</td>\n",
       "      <td>3489</td>\n",
       "      <td>6560</td>\n",
       "      <td>2213</td>\n",
       "      <td>2228</td>\n",
       "      <td>244</td>\n",
       "      <td>64</td>\n",
       "      <td>112</td>\n",
       "      <td>77</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2501</td>\n",
       "      <td>3896</td>\n",
       "      <td>4585</td>\n",
       "      <td>3554</td>\n",
       "      <td>6332</td>\n",
       "      <td>2184</td>\n",
       "      <td>2100</td>\n",
       "      <td>220</td>\n",
       "      <td>56</td>\n",
       "      <td>101</td>\n",
       "      <td>78</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2490</td>\n",
       "      <td>3907</td>\n",
       "      <td>4617</td>\n",
       "      <td>3526</td>\n",
       "      <td>6434</td>\n",
       "      <td>2207</td>\n",
       "      <td>2179</td>\n",
       "      <td>245</td>\n",
       "      <td>71</td>\n",
       "      <td>107</td>\n",
       "      <td>83</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2477</td>\n",
       "      <td>3896</td>\n",
       "      <td>4655</td>\n",
       "      <td>3462</td>\n",
       "      <td>6367</td>\n",
       "      <td>2175</td>\n",
       "      <td>2161</td>\n",
       "      <td>233</td>\n",
       "      <td>56</td>\n",
       "      <td>119</td>\n",
       "      <td>78</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-33</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2483</td>\n",
       "      <td>3900</td>\n",
       "      <td>4544</td>\n",
       "      <td>3494</td>\n",
       "      <td>6351</td>\n",
       "      <td>2205</td>\n",
       "      <td>2161</td>\n",
       "      <td>218</td>\n",
       "      <td>68</td>\n",
       "      <td>98</td>\n",
       "      <td>79</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2477</td>\n",
       "      <td>3886</td>\n",
       "      <td>4588</td>\n",
       "      <td>3572</td>\n",
       "      <td>6441</td>\n",
       "      <td>2182</td>\n",
       "      <td>2173</td>\n",
       "      <td>243</td>\n",
       "      <td>74</td>\n",
       "      <td>107</td>\n",
       "      <td>81</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AC-other</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "date      07-14  07-16  07-17  09-11  09-12  09-13  09-14  09-15  09-16  \\\n",
       "group                                                                     \n",
       "AC-00        45    909    305      0      0      0      0      0      0   \n",
       "AC-01        39    905    287      0      0      0      0      0      0   \n",
       "AC-02        52    888    304      0      0      0      0      0      0   \n",
       "AC-03        45    893    293      0      0      0      0      0      0   \n",
       "AC-04        80    902    284      0      0      0      0      0      0   \n",
       "AC-05        36    872    300      0      0      0      0      0      0   \n",
       "AC-06        47    906    257      0      0      0      0      0      0   \n",
       "AC-07        48    859    299      0      0      0      0      0      0   \n",
       "AC-08        45    854    303      0      0      0      0      0      0   \n",
       "AC-09        44    878    263      0      0      0      0      0      0   \n",
       "AC-10         0      0      0   2478   3896   4591   3510   6458   2167   \n",
       "AC-11         0      0      0   2483   3911   4613   3574   6365   2204   \n",
       "AC-12         0      0      0   2481   3897   4577   3550   6527   2207   \n",
       "AC-13         0      0      0   2488   3909   4604   3605   6438   2252   \n",
       "AC-14         0      0      0   2470   3911   4528   3541   6278   2234   \n",
       "AC-15         0      0      0   2470   3893   4572   3540   6451   2269   \n",
       "AC-16         0      0      0   2477   3917   4562   3541   6385   2196   \n",
       "AC-17         0      0      0   2496   3907   4509   3558   6511   2249   \n",
       "AC-18         0      0      0   2498   3903   4569   3584   6352   2190   \n",
       "AC-19         0      0      0   2475   3924   4525   3491   6523   2183   \n",
       "AC-20         0      0      0   2481   3910   4568   3572   6562   2153   \n",
       "AC-21         0      0      0   2476   3900   4573   3463   6493   2297   \n",
       "AC-22         0      0      0   2486   3886   4557   3522   6507   2225   \n",
       "AC-23         0      0      0   2484   3917   4612   3492   6441   2171   \n",
       "AC-24         0      0      0   2469   3908   4637   3511   6507   2175   \n",
       "AC-25         0      0      0   2472   3900   4562   3482   6426   2099   \n",
       "AC-26         0      0      0   2491   3916   4581   3575   6462   2257   \n",
       "AC-27         0      0      0   2483   3896   4599   3630   6440   2195   \n",
       "AC-28         0      0      0   2475   3914   4566   3542   6366   2233   \n",
       "AC-29         0      0      0   2477   3896   4651   3489   6560   2213   \n",
       "AC-30         0      0      0   2501   3896   4585   3554   6332   2184   \n",
       "AC-31         0      0      0   2490   3907   4617   3526   6434   2207   \n",
       "AC-32         0      0      0   2477   3896   4655   3462   6367   2175   \n",
       "AC-33         0      0      0   2483   3900   4544   3494   6351   2205   \n",
       "AC-34         0      0      0   2477   3886   4588   3572   6441   2182   \n",
       "AC-other      0      0      0      0      0      0      0      0      0   \n",
       "\n",
       "date      09-17  09-18  09-19  09-22  09-23  09-24  \n",
       "group                                               \n",
       "AC-00         0      0      0      0      0      0  \n",
       "AC-01         0      0      0      0      0      0  \n",
       "AC-02         0      0      0      0      0      0  \n",
       "AC-03         0      0      0      0      0      0  \n",
       "AC-04         0      0      0      0      0      0  \n",
       "AC-05         0      0      0      0      0      0  \n",
       "AC-06         0      0      0      0      0      0  \n",
       "AC-07         0      0      0      0      0      0  \n",
       "AC-08         0      0      0      0      0      0  \n",
       "AC-09         0      0      0      0      0      0  \n",
       "AC-10      2143    225     63    112     80     11  \n",
       "AC-11      2097    231     74    118     75     12  \n",
       "AC-12      2197    224     76    112     79     12  \n",
       "AC-13      2180    241     72    123     82     12  \n",
       "AC-14      2168    256     71    119     75     11  \n",
       "AC-15      2144    254     75    117     77     11  \n",
       "AC-16      2144    231     69    108     83     12  \n",
       "AC-17      2290    231     64    105     74     11  \n",
       "AC-18      2067    229     55    117     80     12  \n",
       "AC-19      2165    258     58     94     77     14  \n",
       "AC-20      2150    236     86    113     79     12  \n",
       "AC-21      2188    239     75    113     83     12  \n",
       "AC-22      2240    241     82    110     81     13  \n",
       "AC-23      2246    235     68    108     77     12  \n",
       "AC-24      2169    222     75    100     78     12  \n",
       "AC-25      2191    240     64     95     78     11  \n",
       "AC-26      2210    248     82    131     78     13  \n",
       "AC-27      2192    241     70     95     76     13  \n",
       "AC-28      2140    233     62    123     75     11  \n",
       "AC-29      2228    244     64    112     77     12  \n",
       "AC-30      2100    220     56    101     78     13  \n",
       "AC-31      2179    245     71    107     83     13  \n",
       "AC-32      2161    233     56    119     78     11  \n",
       "AC-33      2161    218     68     98     79     12  \n",
       "AC-34      2173    243     74    107     81     12  \n",
       "AC-other      0      0      0      0      0      0  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    comments_14_28_classified\n",
    "    .loc[lambda df: df[\"group\"] != \"[other]\"]\n",
    "    .assign(\n",
    "        date = lambda df: df[\"date\"].str.slice(5, 10)\n",
    "    )\n",
    "    .groupby([\"group\", \"date\"])\n",
    "    .size()\n",
    "    .unstack()\n",
    "    .fillna(0)\n",
    "    .astype(int)\n",
    "    .loc[:, lambda df: df.sum() >= 200]\n",
    "    \n",
    "    # Order columns by date\n",
    "    .pipe(lambda df: df[[c for c in sorted(df.columns)]])\n",
    "    \n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Example comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== AC-10 ===\n",
      "\n",
      "The Internet is not broken, and does not need to be fixed.  Left-wing extremists have been crying wolf for the past decade about the harm to the Internet if the Federal government didn?t regulate it.  Not only were they wrong, but the Internet has exploded with innovation.  Do not regulate the Internet.  The best way to keep it open and free is what has kept it open and free all along ? no government intervention.\n",
      "\n",
      "The Internet is not broken, and does not need to be fixed.  Left-wing extremists have been crying wolf for the past decade about the harm to the Internet if the Federal government didn?t regulate it.  Not only were they wrong, but the Internet has exploded with innovation.  Do not regulate the Internet.  The best way to keep it open and free is what has kept it open and free all along ? no government intervention.\n",
      "\n",
      "The Internet is not broken, and does not need to be fixed.  Left-wing extremists have been crying wolf for the past decade about the harm to the Internet if the Federal government didn?t regulate it.  Not only were they wrong, but the Internet has exploded with innovation.  Do not regulate the Internet.  The best way to keep it open and free is what has kept it open and free all along ? no government intervention.\n",
      "\n",
      "\n",
      "=== AC-27 ===\n",
      "\n",
      "The American people are watching a Federal Communications Commission (FCC) that is not seeking to make the Internet better, but instead seeking to regulate it.  The FCC could improve broadband delivery by auctioning off much-needed spectrum.  Or it could get rid of some of its own burdensome rules that prevent companies from attracting investors and innovating.  But instead of doing these things that would improve the Internet, the FCC is wasting its time in an obsessive drive to regulate. This [...]\n",
      "\n",
      "The American people are watching a Federal Communications Commission (FCC) that is not seeking to make the Internet better, but instead seeking to regulate it.  The FCC could improve broadband delivery by auctioning off much-needed spectrum.  Or it could get rid of some of its own burdensome rules that prevent companies from attracting investors and innovating.  But instead of doing these things that would improve the Internet, the FCC is wasting its time in an obsessive drive to regulate.  This[...]\n",
      "\n",
      "7522706506.txtThe American people are watching a Federal Communications Commission (FCC) that is not seeking to make the Internet better, but instead seeking to regulate it.  The FCC could improve broadband delivery by auctioning off much-needed spectrum.  Or it could get rid of some of its own burdensome rules that prevent companies from attracting investors and innovating.  But instead of doing these things that would improve the Internet, the FCC is wasting its time in an obsessive drive to r[...]\n",
      "\n",
      "\n",
      "=== [other] ===\n",
      "\n",
      "Dear Chairman Wheeler:We are writing to urge you to implement strong and unambiguous net neutrality rules that protect the Internet from discrimination and other practices that will impede its ability to serve our democracy, empower consumers, and fuel economic growth. Erecting toll booths or designating fast lanes on the information superhighway wouldstifle free speech, limit consumer choice, and thwart innovation.  The FCC must act in a clear and decisive way to ensure the Internet does not be[...]\n",
      "\n",
      "Dear Chairman Wheeler:We are writing to urge you to implement strong and unambiguous net neutrality rules that protect the Internet from discrimination and other practices that will impede its ability to serve our democracy, empower consumers, and fuel economic growth. Erecting toll booths or designating fast lanes on the information superhighway wouldstifle free speech, limit consumer choice, and thwart innovation.  The FCC must act in a clear and decisive way to ensure the Internet does not be[...]\n",
      "\n",
      "7522187451.txtDear Chairman Wheeler:We are writing to urge you to implement strong and unambiguous net neutrality rules that protect the Internet from discrimination and other practices that will impede its ability to serve our democracy, empower consumers, and fuel economic growth. Erecting toll booths or designating fast lanes on the information superhighway wouldstifle free speech, limit consumer choice, and thwart innovation.  The FCC must act in a clear and decisive way to ensure the Intern[...]\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print_example_comments(\n",
    "    comments_14_28_classified\n",
    "    .loc[lambda df: df[\"group\"].isin([\"AC-10\", \"AC-27\", \"[other]\"])],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the above timing and language for group `AC-27` to the [comment attributed to Annie Reeves](https://www.fcc.gov/ecfs/filing/6019076835), received by the FCC on September 15, 2014:\n",
    "\n",
    "> The American people are watching a Federal Communications Commission (FCC) that is not seeking to make the Internet better, but instead seeking to regulate it. The FCC could improve broadband delivery by auctioning off much-needed spectrum. Or it could get rid of some of its own burdensome rules that prevent companies from attracting investors and innovating. But instead of doing these things that would improve the Internet, the FCC is wasting its time in an obsessive drive to regulate. This tells the American people that once again, a Washington agency is working in aself-interested way to increase its own power at the expense of the free people it is meant to serve."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Docket 16-42\n",
    "\n",
    "Here, we identify two very large sets of comments in this docket, by searching for the short phrases below. Please see the associated BuzzFeed News article for context.\n",
    "\n",
    "The \"American Commitment\" set of comments is labeled as such because it uses language from [that organization's comment campaign](http://web.archive.org/web/20160403182941/https://www.americancommitment.org/cablebox-petition). (The text of comments appear to be generated algorithmically, selecting randomly from sets of pre-selected words and phrases, but the phrase used here for classification is static — it does not change across the comments.) To be sure, it is possible the comments were submitted by entities other than American Commitment, using the same language; the FCC's public portal does not specify who submitted these comments. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'over $200'            104816\n",
       "American Commitment    101783\n",
       "[other]                 75175\n",
       "Name: group, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comments_16_42_classified = (\n",
    "    comments_16_42\n",
    "    .pipe(\n",
    "        add_classification,\n",
    "        [\n",
    "            (\"cloud-based video on demand, and apps providing news\", \"American Commitment\"),\n",
    "            (\"A cable subscriber pays over \\$200\", \"'over $200'\"),\n",
    "        ]\n",
    "    )\n",
    ")\n",
    "\n",
    "(\n",
    "    comments_16_42_classified\n",
    "    [\"group\"]\n",
    "    .value_counts()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Dates submitted, by two main groups of comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2016-04-19    10499\n",
       "2016-04-20    59247\n",
       "2016-04-21    35070\n",
       "Name: date, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    comments_16_42_classified\n",
    "    .loc[lambda df: df[\"group\"] == \"'over $200'\"]\n",
    "    [\"date\"]\n",
    "    .value_counts()\n",
    "    .sort_index()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2016-02-22        1\n",
       "2016-05-16    12293\n",
       "2016-05-17    55852\n",
       "2016-05-18    33637\n",
       "Name: date, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    comments_16_42_classified\n",
    "    .loc[lambda df: df[\"group\"] == \"American Commitment\"]\n",
    "    [\"date\"]\n",
    "    .value_counts()\n",
    "    .sort_index()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note: The 2016-02-22 comment above appears to stem from a data-entry mistake on the FCC's website. There, [the comment](https://www.fcc.gov/ecfs/filing/60001484317)'s text seems to suggests that the language actually came from a [comment with ID 60001843102](https://www.fcc.gov/ecfs/filing/60001843102); that comment, in turn, says it was received on May 18, 2016.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Example comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== 'over $200' ===\n",
      "\n",
      "60001650840.txtA cable subscriber pays over $200 per year to rent a box from the cable companies that are already protected by government. This kills competition, limits consumer choice, and lifts up cable profits that are already excessive.Allow the free market to work and unlock the box to open competition and end the monopoly that cable companies have over our televisions.Page 1\n",
      "\n",
      "60001633497.txtA cable subscriber pays over $200 per year to rent a box from the cable companies that are already protected by government. This kills competition, limits consumer choice, and lifts up cable profits that are already excessive.Allow the free market to work and unlock the box to open competition and end the monopoly that cable companies have over our televisions.Page 1\n",
      "\n",
      "60001621406.txtA cable subscriber pays over $200 per year to rent a box from the cable companies that are already protected by government. This kills competition, limits consumer choice, and lifts up cable profits that are already excessive.Allow the free market to work and unlock the box to open competition and end the monopoly that cable companies have over our televisions.Page 1\n",
      "\n",
      "\n",
      "=== American Commitment ===\n",
      "\n",
      "60001870988.txtThe marketplace for video content is thriving and extremely competitive, offering a vast array of video streaming services, cloud-based video on demand, and apps providing news, cinema and programming. This market is rapidly innovating beyond thetraditional set-top box to new applications and devices with more choices than ever. Past government attempts to control set-top boxes have been a complete failure.  Yet another failed attempt at top-down government regulation will only pu[...]\n",
      "\n",
      "60001888486.txtThe exchange for video content is booming and incredibly competitive, offering a wide array of video streaming services, cloud-based video on demand, and apps providing news, cinema and programming. This market is swiftly innovating beyond thetraditional set-top box to new applications and devices with more options than ever. Past Commission attempts to control set-top boxes have been a complete failure.  Yet another failed attempt at one-size-fits-all government regulation will o[...]\n",
      "\n",
      "60001883996.txtThe exchange for video content is roaring and incredibly competitive, offering a vast array of video streaming services, cloud-based video on demand, and apps providing news, cinema and programming. This market is quickly innovating beyond thetraditional set-top box to new applications and devices with more options than ever. Past FCC attempts to regulate set-top boxes have been a complete failure.  Yet another failed attempt at heavy-handed government regulation will only put the[...]\n",
      "\n",
      "\n",
      "=== [other] ===\n",
      "\n",
      "60001976192.txtI oppose unnecessary set-top box regulations that will mean higher bills, fewer choices, and less privacy on TV. The television and video market today is full of great choices, why put such a healthy market at risk with complex and unnecessary new mandates?Page 1\n",
      "\n",
      "60001962194.txtI oppose unnecessary set-top box regulations that will mean higher bills, fewer choices, and less privacy on TV. The television and video market today is full of great choices, why put such a healthy market at risk with complex and unnecessary new mandates?Page 1\n",
      "\n",
      "60001991447.txtI oppose unnecessary set-top box regulations that will mean higher bills, fewer choices, and less privacy on TV. The television and video market today is full of great choices, why put such a healthy market at risk with complex and unnecessary new mandates?Page 1\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print_example_comments(comments_16_42_classified)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the above timing and language to the [comment attributed to Annie Reeves](https://www.fcc.gov/ecfs/filing/60001803771), received by the FCC on May 17, 2016:\n",
    "\n",
    "> The market for video content is booming and extremely competitive, offering a vast array of video streaming services, cloud-based video on demand, and apps providing news, cinema and programming. This market is swiftly innovating beyond the traditional set-top box to new applications and devices with more options than ever. Past Commission attempts to regulate set-top boxes have been a complete failure. Yet another failed attempt at heavy-handed government regulation will only stifle innovation and benefit companies with political influence rather than companies thatprovide what consumers want. We don't need the federal government to fix what isn'tbroken -- I urge you to reject the proposed rule."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examine email address crossover between 16-42 and bulk-uploaded 17-108 comments\n",
    "\n",
    "Here, we calculate the proportion of commenters from docket 16-42 that later appeared in comments bulk-uploaded to docket 17-108, and observe a very high rate of overlap between the email addresses associated with comments that used American Commitment's language in docket 16-42 and the email addresses listed in comments bulk-uploaded by Media Bridge. We find the same for commenters' full names plus physical addresses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>num_emails</th>\n",
       "      <th>email_isin_17_108_nonmb</th>\n",
       "      <th>email_isin_17_108_mb</th>\n",
       "      <th>name_and_location_isin_17_108_mb</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>American Commitment</td>\n",
       "      <td>100252</td>\n",
       "      <td>0.0231</td>\n",
       "      <td>0.9987</td>\n",
       "      <td>0.9987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>'over $200'</td>\n",
       "      <td>100482</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>0.0601</td>\n",
       "      <td>0.0566</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     num_emails  email_isin_17_108_nonmb  \\\n",
       "group                                                      \n",
       "American Commitment      100252                   0.0231   \n",
       "'over $200'              100482                   0.0243   \n",
       "\n",
       "                     email_isin_17_108_mb  name_and_location_isin_17_108_mb  \n",
       "group                                                                        \n",
       "American Commitment                0.9987                            0.9987  \n",
       "'over $200'                        0.0601                            0.0566  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    comments_16_42_classified\n",
    "    [[\n",
    "        \"email_address\",\n",
    "        \"name_and_location\",\n",
    "        \"group\",\n",
    "    ]]\n",
    "    .drop_duplicates()\n",
    "    .dropna()\n",
    "    .assign(\n",
    "        email_isin_17_108_nonmb = lambda df: (\n",
    "            df[\"email_address\"].notnull() & df[\"email_address\"].isin(\n",
    "                bulk_uploads_17_108\n",
    "                .loc[lambda df: df[\"uploader\"] != \"shane@mediabridgellc.com\"]\n",
    "                [\"email_address\"]\n",
    "            )\n",
    "        ),\n",
    "        email_isin_17_108_mb = lambda df: (\n",
    "            df[\"email_address\"].notnull() & df[\"email_address\"].isin(\n",
    "                bulk_uploads_17_108\n",
    "                .loc[lambda df: df[\"uploader\"] == \"shane@mediabridgellc.com\"]\n",
    "                [\"email_address\"]\n",
    "            )\n",
    "        ),\n",
    "        name_and_location_isin_17_108_mb = lambda df: (\n",
    "            df[\"name_and_location\"].isin(\n",
    "                bulk_uploads_17_108\n",
    "                .loc[lambda df: df[\"uploader\"] == \"shane@mediabridgellc.com\"]\n",
    "                [\"name_and_location\"]\n",
    "            )\n",
    "        ),\n",
    "    )\n",
    "    .groupby(\"group\")\n",
    "    .pipe(lambda grp: pd.DataFrame({\n",
    "        \"num_emails\": grp.size(),\n",
    "        \"email_isin_17_108_nonmb\": grp[\"email_isin_17_108_nonmb\"].mean().round(4),\n",
    "        \"email_isin_17_108_mb\": grp[\"email_isin_17_108_mb\"].mean().round(4),\n",
    "        \"name_and_location_isin_17_108_mb\": grp[\"name_and_location_isin_17_108_mb\"].mean().round(4),\n",
    "    }))\n",
    "    .loc[lambda df: df[\"num_emails\"] >= 1000]\n",
    "    .sort_values(\"email_isin_17_108_mb\", ascending = False)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyze 17-108 bulk-uploads vis-a-vis Have I Been Pwned\n",
    "\n",
    "In this section, we take random samples of email addresses the comments bulk-uploaded to Docket 17-108,  and calculate the rates at which they have appeared in the data breaches tracked by Have I Been Pwned. We focus on the accounts that uploaded comments containing 10,000+ distinct email addresses.\n",
    "\n",
    "*Note: The HIBP data has already been been fetched and saved, but the code used to fetch the data is included here for reference, and for reuse by other researchers.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    uuid_lookup = pd.read_csv(\n",
    "        BASE_PATH + \"bulk-uploads-17-108-uuid-lookup.csv\",\n",
    "        dtype = str,\n",
    "    )\n",
    "    \n",
    "    assert uuid_lookup[\"email_address_uuid\"].value_counts().max() == 1\n",
    "    print(f\"{len(uuid_lookup):,d}\")\n",
    "except:\n",
    "    uuid_lookup = pd.DataFrame(None, columns = [ \"email_address\", \"email_address_uuid\" ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "BASE_HIBP_URL = \"https://haveibeenpwned.com/api/v3/breachedaccount/\"\n",
    "from json import JSONDecodeError\n",
    "\n",
    "def fetch_hipb_results(email_address):\n",
    "    while True:\n",
    "        try:\n",
    "            res = requests.get(\n",
    "                f\"{BASE_HIBP_URL}{email_address.strip()}\",\n",
    "                headers = {\n",
    "                    'hibp-api-key': HIBP_KEY,\n",
    "                },\n",
    "            )\n",
    "            if res.from_cache == False:\n",
    "                time.sleep(1.5)\n",
    "\n",
    "            # Check that JSON is parseable\n",
    "            if res.content != b\"\":\n",
    "                res.json()\n",
    "                if \"message\" in res.json():\n",
    "                    raise Exception(\"HIPB error: {res.json()['message']}\")\n",
    "\n",
    "        except requests.RequestException:\n",
    "            sys.stderr.write(f\"\\nException; sleeping for 10 seconds\\n\")\n",
    "            time.sleep(10)            \n",
    "            continue\n",
    "            \n",
    "        except JSONDecodeError as e:\n",
    "            sys.stderr.write(f\"\\nERROR: <{email_address}>\\n\")\n",
    "            sys.stderr.write(f\"{e}\\n\")\n",
    "            sys.stderr.write(f\"{res.content}\\n\")\n",
    "            return [ { \"email_address\": email_address, \"breach\": \"[error]\" } ]\n",
    "\n",
    "        if res.status_code == 429:\n",
    "            sleep_int = int(res.headers[\"Retry-After\"])\n",
    "            sys.stderr.write(f\"\\nSleeping for {sleep_int + 1} seconds\")\n",
    "            time.sleep(sleep_int)\n",
    "            continue\n",
    "            \n",
    "        if res.content == b\"\" or res.status_code == 404:\n",
    "            return [ { \"email_address\": email_address, \"breach\": \"[none]\" } ]\n",
    "\n",
    "        else:\n",
    "            return [ { \"email_address\": email_address, \"breach\": x[\"Name\"] } for x in res.json() ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function creates a sample — or a grouped set of samples — from a given set of comments. Before sampling, the code removes blank email addresses and those with non-standard characters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_sample(df, grouping = [], n = 1000, random_state = RANDOM_STATE):\n",
    "    clean = (\n",
    "        df\n",
    "        .loc[lambda df: df[\"email_address\"].notnull()]\n",
    "        .loc[lambda df: df[\"email_address_nonstandard\"] == 0]\n",
    "        .drop_duplicates(subset = [ \"email_address\" ] + grouping)\n",
    "    )\n",
    "    \n",
    "    sampler = lambda df: df.sample(n, random_state = random_state)\n",
    "    \n",
    "    if len(grouping):\n",
    "        return (\n",
    "            clean\n",
    "            .groupby(grouping)\n",
    "            .apply(sampler)\n",
    "            .reset_index(drop = True)\n",
    "        )\n",
    "    else:\n",
    "        return clean.pipe(sampler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_breaches(df, save_path, save = True, use_saved = True):\n",
    "    if use_saved and os.path.exists(save_path):\n",
    "        return pd.read_csv(save_path, dtype = str)\n",
    "    else:\n",
    "        breaches_raw = pd.concat(map(pd.DataFrame, (\n",
    "            df\n",
    "            .rename(columns = {\n",
    "                \"email_address\": \"email_address_uuid\"\n",
    "            })\n",
    "            .merge(\n",
    "                uuid_lookup,\n",
    "                how = \"left\",\n",
    "                on = [ \"email_address_uuid\" ]\n",
    "            )\n",
    "            [\"email_address\"]\n",
    "            .progress_apply(fetch_hipb_results)\n",
    "        ))).drop_duplicates()\n",
    "        \n",
    "        breaches = (\n",
    "            breaches_raw\n",
    "            .merge(\n",
    "                uuid_lookup,\n",
    "                how = \"left\",\n",
    "                on = [ \"email_address\" ]\n",
    "            )\n",
    "            .drop(columns = [ \"email_address\" ])\n",
    "            .rename(columns = {\n",
    "                \"email_address_uuid\": \"email_address\",\n",
    "            })\n",
    "        )\n",
    "        \n",
    "        if save:\n",
    "            breaches.to_csv(save_path, index = False)\n",
    "\n",
    "        return breaches"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The function below calculates the breach rates for groups of sampled comments, for each breach found."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_breach_rates(sample, breaches):\n",
    "    return (\n",
    "        sample\n",
    "        [[\n",
    "            \"email_address\",\n",
    "            \"uploader\",\n",
    "        ]]\n",
    "        \n",
    "        .merge(\n",
    "            breaches,\n",
    "            how = \"left\",\n",
    "            on = [ \"email_address\" ],\n",
    "        )\n",
    "        .assign(breached = 1)\n",
    "        .set_index([\n",
    "            \"uploader\",\n",
    "            \"email_address\",\n",
    "            \"breach\",\n",
    "        ])\n",
    "        [\"breached\"]\n",
    "        .unstack()\n",
    "        .fillna(0)\n",
    "        .astype(int)\n",
    "        # At this point, we have a matrix of uploader+email x breach\n",
    "        # where the values are 1 if breached and 0 if not\n",
    "        \n",
    "        # Now, we group by uploader and calculate the proportion of\n",
    "        # emails breached\n",
    "        .groupby([ \"uploader\" ])\n",
    "        .mean()\n",
    "        \n",
    "        # Then we return the data frame to a \"tidy\" format:\n",
    "        # uploader|breach|rate\n",
    "        .stack()\n",
    "        .sort_values(ascending = False)\n",
    "        .to_frame(\"rate\")\n",
    "        .reset_index()\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 17-108 by bulk uploader\n",
    "\n",
    "Limited here to the accounts that uploaded comments containing 10,000+ distinct email addresses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>date</th>\n",
       "      <th>comments</th>\n",
       "      <th>file</th>\n",
       "      <th>uploader</th>\n",
       "      <th>email_address_nonstandard</th>\n",
       "      <th>email_address</th>\n",
       "      <th>email_domain</th>\n",
       "      <th>name_and_location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>5/15/17</td>\n",
       "      <td>In 2015, wealthy leftist billionaires and powe...</td>\n",
       "      <td>FOI-14090-2017527.csv</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>0</td>\n",
       "      <td>939bfae2-62d1-47de-b009-c2abc6b681f5</td>\n",
       "      <td>yahoo.com</td>\n",
       "      <td>8930069a-021b-4263-9c3b-a3923af9a9dc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>8/5/17</td>\n",
       "      <td>Before leaving office, the Obama Administratio...</td>\n",
       "      <td>CFIF_1_25000_08052017_4 (1).csv</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>0</td>\n",
       "      <td>f9a12339-56cb-4540-9adc-fc6238428f49</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>6c65ec31-5135-4500-99c5-bba309b415fb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>8/6/17</td>\n",
       "      <td>Before leaving office, the Obama Administratio...</td>\n",
       "      <td>CFIF_1_25000_08062017_2.csv</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>0</td>\n",
       "      <td>fcf0991a-0ed7-408b-8e52-4735baccd906</td>\n",
       "      <td>yahoo.com</td>\n",
       "      <td>6dfa9546-ad61-404a-bec7-48464be021b4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>7/29/17</td>\n",
       "      <td>Before leaving office, the Obama Administratio...</td>\n",
       "      <td>CFIF_1_40000_07292017.csv</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>0</td>\n",
       "      <td>ee33e2a5-854f-471b-adb1-1ff62d69bf46</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>6d99eb3f-9242-440d-be2a-c7f7ae3b4e91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5/9/17</td>\n",
       "      <td>Obama's Federal Communications Commission (FCC...</td>\n",
       "      <td>T2017510-2.csv</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>0</td>\n",
       "      <td>4d294840-8365-4d34-a5c4-c09f6b8bc01d</td>\n",
       "      <td>icloud.com</td>\n",
       "      <td>d132203a-a146-4043-b097-d6606498309f</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      date                                           comments  \\\n",
       "0  5/15/17  In 2015, wealthy leftist billionaires and powe...   \n",
       "1   8/5/17  Before leaving office, the Obama Administratio...   \n",
       "2   8/6/17  Before leaving office, the Obama Administratio...   \n",
       "3  7/29/17  Before leaving office, the Obama Administratio...   \n",
       "4   5/9/17  Obama's Federal Communications Commission (FCC...   \n",
       "\n",
       "                              file        uploader  email_address_nonstandard  \\\n",
       "0            FOI-14090-2017527.csv  esmisc@mac.com                          0   \n",
       "1  CFIF_1_25000_08052017_4 (1).csv  esmisc@mac.com                          0   \n",
       "2      CFIF_1_25000_08062017_2.csv  esmisc@mac.com                          0   \n",
       "3        CFIF_1_40000_07292017.csv  esmisc@mac.com                          0   \n",
       "4                   T2017510-2.csv  esmisc@mac.com                          0   \n",
       "\n",
       "                          email_address email_domain  \\\n",
       "0  939bfae2-62d1-47de-b009-c2abc6b681f5    yahoo.com   \n",
       "1  f9a12339-56cb-4540-9adc-fc6238428f49    gmail.com   \n",
       "2  fcf0991a-0ed7-408b-8e52-4735baccd906    yahoo.com   \n",
       "3  ee33e2a5-854f-471b-adb1-1ff62d69bf46    gmail.com   \n",
       "4  4d294840-8365-4d34-a5c4-c09f6b8bc01d   icloud.com   \n",
       "\n",
       "                      name_and_location  \n",
       "0  8930069a-021b-4263-9c3b-a3923af9a9dc  \n",
       "1  6c65ec31-5135-4500-99c5-bba309b415fb  \n",
       "2  6dfa9546-ad61-404a-bec7-48464be021b4  \n",
       "3  6d99eb3f-9242-440d-be2a-c7f7ae3b4e91  \n",
       "4  d132203a-a146-4043-b097-d6606498309f  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_17_108_bulk_uploads = (\n",
    "    bulk_uploads_17_108\n",
    "    .loc[lambda df: df[\"uploader\"].isin(\n",
    "        uploader_metrics\n",
    "        .loc[lambda df: df[\"unique_emails\"] >= 10000]\n",
    "        .index\n",
    "    )]\n",
    "    .pipe(\n",
    "        create_sample,\n",
    "        grouping = [ \"uploader\" ],\n",
    "        n = 1000\n",
    "    )\n",
    ")\n",
    "\n",
    "sample_17_108_bulk_uploads.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "esmisc@mac.com                1000\n",
       "fccfreedom@hmamail.com        1000\n",
       "karen@momsrising.org          1000\n",
       "kurt@demandprogress.org       1000\n",
       "meaghan@mandatemedia.com      1000\n",
       "mike@fightforthefuture.org    1000\n",
       "ncatalano@ofa.us              1000\n",
       "shane@mediabridgellc.com      1000\n",
       "Name: uploader, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_17_108_bulk_uploads[\"uploader\"].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": false
   },
   "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>breach</th>\n",
       "      <th>email_address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>8tracks</td>\n",
       "      <td>939bfae2-62d1-47de-b009-c2abc6b681f5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Animoto</td>\n",
       "      <td>939bfae2-62d1-47de-b009-c2abc6b681f5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>MindJolt</td>\n",
       "      <td>939bfae2-62d1-47de-b009-c2abc6b681f5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>939bfae2-62d1-47de-b009-c2abc6b681f5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>939bfae2-62d1-47de-b009-c2abc6b681f5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    breach                         email_address\n",
       "0                  8tracks  939bfae2-62d1-47de-b009-c2abc6b681f5\n",
       "1                  Animoto  939bfae2-62d1-47de-b009-c2abc6b681f5\n",
       "2                 MindJolt  939bfae2-62d1-47de-b009-c2abc6b681f5\n",
       "3  ModernBusinessSolutions  939bfae2-62d1-47de-b009-c2abc6b681f5\n",
       "4           RiverCityMedia  939bfae2-62d1-47de-b009-c2abc6b681f5"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "breaches_17_108_bulk_uploads = (\n",
    "    sample_17_108_bulk_uploads\n",
    "    .pipe(get_breaches, \"../data/breaches-17-108-bulk-uploads-sample.csv\")\n",
    ")\n",
    "\n",
    "breaches_17_108_bulk_uploads.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most common breach-uploader combinations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>uploader</th>\n",
       "      <th>breach</th>\n",
       "      <th>rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>fccfreedom@hmamail.com</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>fccfreedom@hmamail.com</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>fccfreedom@hmamail.com</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>ncatalano@ofa.us</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>karen@momsrising.org</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>mike@fightforthefuture.org</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>meaghan@mandatemedia.com</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>kurt@demandprogress.org</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>karen@momsrising.org</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>meaghan@mandatemedia.com</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>ncatalano@ofa.us</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>mike@fightforthefuture.org</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>ncatalano@ofa.us</td>\n",
       "      <td>LinkedIn</td>\n",
       "      <td>0.339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>kurt@demandprogress.org</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.323</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      uploader                   breach   rate\n",
       "0     shane@mediabridgellc.com  ModernBusinessSolutions  0.942\n",
       "1     shane@mediabridgellc.com           RiverCityMedia  0.807\n",
       "2       fccfreedom@hmamail.com          VerificationsIO  0.782\n",
       "3     shane@mediabridgellc.com          VerificationsIO  0.743\n",
       "4       fccfreedom@hmamail.com           RiverCityMedia  0.645\n",
       "5               esmisc@mac.com          VerificationsIO  0.625\n",
       "6               esmisc@mac.com           RiverCityMedia  0.565\n",
       "7       fccfreedom@hmamail.com  ModernBusinessSolutions  0.466\n",
       "8             ncatalano@ofa.us          VerificationsIO  0.463\n",
       "9         karen@momsrising.org          VerificationsIO  0.459\n",
       "10  mike@fightforthefuture.org          VerificationsIO  0.435\n",
       "11    meaghan@mandatemedia.com          VerificationsIO  0.435\n",
       "12     kurt@demandprogress.org          VerificationsIO  0.412\n",
       "13        karen@momsrising.org           RiverCityMedia  0.377\n",
       "14    meaghan@mandatemedia.com           RiverCityMedia  0.364\n",
       "15            ncatalano@ofa.us           RiverCityMedia  0.345\n",
       "16              esmisc@mac.com  ModernBusinessSolutions  0.345\n",
       "17  mike@fightforthefuture.org           RiverCityMedia  0.344\n",
       "18            ncatalano@ofa.us                 LinkedIn  0.339\n",
       "19     kurt@demandprogress.org           RiverCityMedia  0.323"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    calculate_breach_rates(\n",
    "        sample_17_108_bulk_uploads,\n",
    "        breaches_17_108_bulk_uploads,\n",
    "    )\n",
    "    .head(20)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Modern Business Solutions breaches only:"
   ]
  },
  {
   "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>uploader</th>\n",
       "      <th>breach</th>\n",
       "      <th>rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>fccfreedom@hmamail.com</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>esmisc@mac.com</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>116</td>\n",
       "      <td>meaghan@mandatemedia.com</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>121</td>\n",
       "      <td>ncatalano@ofa.us</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>130</td>\n",
       "      <td>karen@momsrising.org</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>145</td>\n",
       "      <td>kurt@demandprogress.org</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>150</td>\n",
       "      <td>mike@fightforthefuture.org</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.086</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       uploader                   breach   rate\n",
       "0      shane@mediabridgellc.com  ModernBusinessSolutions  0.942\n",
       "7        fccfreedom@hmamail.com  ModernBusinessSolutions  0.466\n",
       "16               esmisc@mac.com  ModernBusinessSolutions  0.345\n",
       "116    meaghan@mandatemedia.com  ModernBusinessSolutions  0.114\n",
       "121            ncatalano@ofa.us  ModernBusinessSolutions  0.106\n",
       "130        karen@momsrising.org  ModernBusinessSolutions  0.099\n",
       "145     kurt@demandprogress.org  ModernBusinessSolutions  0.087\n",
       "150  mike@fightforthefuture.org  ModernBusinessSolutions  0.086"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    calculate_breach_rates(\n",
    "        sample_17_108_bulk_uploads,\n",
    "        breaches_17_108_bulk_uploads,\n",
    "    )\n",
    "    .loc[lambda df: df[\"breach\"] == \"ModernBusinessSolutions\"]    \n",
    "    .head(20)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Larger 17-108 Media Bridge sample (10,000 addresses), for more precise rates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>date</th>\n",
       "      <th>comments</th>\n",
       "      <th>file</th>\n",
       "      <th>uploader</th>\n",
       "      <th>email_address_nonstandard</th>\n",
       "      <th>email_address</th>\n",
       "      <th>email_domain</th>\n",
       "      <th>name_and_location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>3236533</td>\n",
       "      <td>5/14/17</td>\n",
       "      <td>Dear Chairman Pai,  I am concerned about Inter...</td>\n",
       "      <td>Batch-A4.csv</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>0</td>\n",
       "      <td>44a8867c-3332-403f-9b34-560c054bd728</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>058cbe31-9c92-4509-a8d9-50f84a1cf1ae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2723370</td>\n",
       "      <td>5/15/17</td>\n",
       "      <td>Dear Mr. Pai,  Regarding the Obama takeover of...</td>\n",
       "      <td>Batch-A2.csv</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>0</td>\n",
       "      <td>f9ad6e74-115c-4ccd-8a4e-f1e408423942</td>\n",
       "      <td>icloud.com</td>\n",
       "      <td>99c87532-c65e-42fa-97bd-0438d3ff504c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>56337</td>\n",
       "      <td>5/14/17</td>\n",
       "      <td>Chairman Pai:  Hi, I'd like to comment on Titl...</td>\n",
       "      <td>file-i.csv</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>0</td>\n",
       "      <td>ad374006-bbed-4c8b-932d-e7dfacce1a29</td>\n",
       "      <td>aol.com</td>\n",
       "      <td>6752ca9d-c848-4f3d-a66c-49073afe2458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>592618</td>\n",
       "      <td>05/16/2017</td>\n",
       "      <td>The Title II order created a gaping gap in pri...</td>\n",
       "      <td>batch-d-4.csv</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>0</td>\n",
       "      <td>c16e61f3-bd1f-4e50-95dd-830f5a219543</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>ebccbc49-fa14-404f-bf83-b0ef00d48e78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1014169</td>\n",
       "      <td>05/15/2017</td>\n",
       "      <td>Dear Chairman Pai,  I'm very worried about Net...</td>\n",
       "      <td>batch-b-5.csv</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>0</td>\n",
       "      <td>b252ca16-b5a2-4c61-9034-6e365bec0beb</td>\n",
       "      <td>gmail.com</td>\n",
       "      <td>bc102bc2-d454-44a4-974d-d0b1a377f392</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               date                                           comments  \\\n",
       "3236533     5/14/17  Dear Chairman Pai,  I am concerned about Inter...   \n",
       "2723370     5/15/17  Dear Mr. Pai,  Regarding the Obama takeover of...   \n",
       "56337       5/14/17  Chairman Pai:  Hi, I'd like to comment on Titl...   \n",
       "592618   05/16/2017  The Title II order created a gaping gap in pri...   \n",
       "1014169  05/15/2017  Dear Chairman Pai,  I'm very worried about Net...   \n",
       "\n",
       "                  file                  uploader  email_address_nonstandard  \\\n",
       "3236533   Batch-A4.csv  shane@mediabridgellc.com                          0   \n",
       "2723370   Batch-A2.csv  shane@mediabridgellc.com                          0   \n",
       "56337       file-i.csv  shane@mediabridgellc.com                          0   \n",
       "592618   batch-d-4.csv  shane@mediabridgellc.com                          0   \n",
       "1014169  batch-b-5.csv  shane@mediabridgellc.com                          0   \n",
       "\n",
       "                                email_address email_domain  \\\n",
       "3236533  44a8867c-3332-403f-9b34-560c054bd728    gmail.com   \n",
       "2723370  f9ad6e74-115c-4ccd-8a4e-f1e408423942   icloud.com   \n",
       "56337    ad374006-bbed-4c8b-932d-e7dfacce1a29      aol.com   \n",
       "592618   c16e61f3-bd1f-4e50-95dd-830f5a219543    gmail.com   \n",
       "1014169  b252ca16-b5a2-4c61-9034-6e365bec0beb    gmail.com   \n",
       "\n",
       "                            name_and_location  \n",
       "3236533  058cbe31-9c92-4509-a8d9-50f84a1cf1ae  \n",
       "2723370  99c87532-c65e-42fa-97bd-0438d3ff504c  \n",
       "56337    6752ca9d-c848-4f3d-a66c-49073afe2458  \n",
       "592618   ebccbc49-fa14-404f-bf83-b0ef00d48e78  \n",
       "1014169  bc102bc2-d454-44a4-974d-d0b1a377f392  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_17_108_mb = (\n",
    "    bulk_uploads_17_108\n",
    "    .loc[lambda df: df[\"uploader\"] == \"shane@mediabridgellc.com\"]\n",
    "    .pipe(\n",
    "        create_sample,\n",
    "        n = 10000,\n",
    "        random_state = RANDOM_STATE + 1,  # +1 so that we have an independent sample    \n",
    "    )\n",
    ")\n",
    "\n",
    "sample_17_108_mb.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>breach</th>\n",
       "      <th>email_address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Edmodo</td>\n",
       "      <td>44a8867c-3332-403f-9b34-560c054bd728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>44a8867c-3332-403f-9b34-560c054bd728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>44a8867c-3332-403f-9b34-560c054bd728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>SpecialKSpamList</td>\n",
       "      <td>44a8867c-3332-403f-9b34-560c054bd728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>44a8867c-3332-403f-9b34-560c054bd728</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    breach                         email_address\n",
       "0                   Edmodo  44a8867c-3332-403f-9b34-560c054bd728\n",
       "1  ModernBusinessSolutions  44a8867c-3332-403f-9b34-560c054bd728\n",
       "2           RiverCityMedia  44a8867c-3332-403f-9b34-560c054bd728\n",
       "3         SpecialKSpamList  44a8867c-3332-403f-9b34-560c054bd728\n",
       "4          VerificationsIO  44a8867c-3332-403f-9b34-560c054bd728"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "breaches_17_108_mb = (\n",
    "    sample_17_108_mb\n",
    "    .pipe(get_breaches, \"../data/breaches-17-108-mb-sample.csv\")\n",
    ")\n",
    "\n",
    "breaches_17_108_mb.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>uploader</th>\n",
       "      <th>breach</th>\n",
       "      <th>rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>ModernBusinessSolutions</td>\n",
       "      <td>0.9388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>RiverCityMedia</td>\n",
       "      <td>0.8277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>VerificationsIO</td>\n",
       "      <td>0.7651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>Collection1</td>\n",
       "      <td>0.2574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>Exactis</td>\n",
       "      <td>0.2571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>MySpace</td>\n",
       "      <td>0.1968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>AntiPublic</td>\n",
       "      <td>0.1956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>SpecialKSpamList</td>\n",
       "      <td>0.1946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>OnlinerSpambot</td>\n",
       "      <td>0.1941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>shane@mediabridgellc.com</td>\n",
       "      <td>ExploitIn</td>\n",
       "      <td>0.1826</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   uploader                   breach    rate\n",
       "0  shane@mediabridgellc.com  ModernBusinessSolutions  0.9388\n",
       "1  shane@mediabridgellc.com           RiverCityMedia  0.8277\n",
       "2  shane@mediabridgellc.com          VerificationsIO  0.7651\n",
       "3  shane@mediabridgellc.com              Collection1  0.2574\n",
       "4  shane@mediabridgellc.com                  Exactis  0.2571\n",
       "5  shane@mediabridgellc.com                  MySpace  0.1968\n",
       "6  shane@mediabridgellc.com               AntiPublic  0.1956\n",
       "7  shane@mediabridgellc.com         SpecialKSpamList  0.1946\n",
       "8  shane@mediabridgellc.com           OnlinerSpambot  0.1941\n",
       "9  shane@mediabridgellc.com                ExploitIn  0.1826"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    calculate_breach_rates(\n",
    "        sample_17_108_mb,\n",
    "        breaches_17_108_mb,\n",
    "    )\n",
    "    .head(10)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparing MBS breach status to Docket 16-42 overlap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>isin_mbs</th>\n",
       "      <th>isin_16</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>3236533</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2723370</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>56337</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>592618</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1014169</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         isin_mbs  isin_16\n",
       "3236533      True    False\n",
       "2723370      True    False\n",
       "56337        True    False\n",
       "592618       True    False\n",
       "1014169      True    False"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_17_108_mb_comparison = (\n",
    "    sample_17_108_mb    \n",
    "    .assign(\n",
    "        isin_mbs = lambda df: (\n",
    "            df\n",
    "            [\"email_address\"].isin(\n",
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    "                .loc[lambda df: df[\"breach\"] == \"ModernBusinessSolutions\"]\n",
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   "source": [
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   ]
  },
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       "isin_16   False  True \n",
       "isin_mbs              \n",
       "False        35    577\n",
       "True       9287    101"
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   "source": [
    "Among comments whose email addresses do *not* appear in MBS, this is the proportion that use exactly the same contact information as in the Docket 16-42 comments using American Commitment's language:"
   ]
  },
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   "source": [
    "Among comments whose email addresses use exactly the same contact information as in the Docket 16-42 comments using American Commitment's language, this is the proportion of email addresses that appear in MBS:"
   ]
  },
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   "source": [
    "This is the proportion of comments that *either* are attributed to email addresses that appear in the Modern Business Solutions breach *or* use exactly the same contact information as in the Docket 16-42 comments using American Commitment's language:"
   ]
  },
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