pro_publica_campaign_data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ProPublica Campaign API Data\n",
    "ProPublica makes their campaign data API available to the public. This notebook will play around with some requests on the data.  \n",
    "\n",
    "We'll use the utlity [jq](https://stedolan.github.io/jq/manual/) to filter the JSON returned from the API.  \n",
    "\n",
    "Later, we'll use `pandas` and other tools to visualize the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2016 Presedential Race"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "DATA=\"data/campaign_totals_2016.json\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll just look at some results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;39m[\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"clinton\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Clinton, Hillary\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Hillary Clinton\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"D\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00575795.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00575795\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m186735031.61\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m157763659.51\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m28971372.1\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-04-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P00003392\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m51431956.48\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m11434374.12\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m25107086.49\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m13644451.08\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m76523400\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m24342711.9\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m13\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m30.3\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m45.1\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m106.9341168047289\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m169552497.08\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m10116597.97\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m6987601.95000001\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"sanders\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Sanders, Bernie\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Bernie Sanders\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"D\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00577130.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00577130\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m185864101.89\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m168349117.67\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m17460961.37\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-04-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P60007168\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m221735971.88\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m19404608.34\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m20837551.49\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3105827.9\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2068200\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m17460961.37\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m9.4\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m121.2\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1.0999999999999999\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m99.45757021313398\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m182923991.19\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4334387.32\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m859341.11\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"cruz\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Cruz, Ted\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Ted Cruz\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"R\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00574624.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00574624\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m79060950.56\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m70254861.95\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m8806088.61\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-01-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P60006111\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m49809054.51\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m7008975.51\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m8823012.37\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2282803.11\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m7263000\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4652997.16\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m5.8999999999999995\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m63.3\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m9.2\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m93.926460079587\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m78679628.91\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m20654581.12\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m9231692.41\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"carson\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Carson, Ben\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Ben Carson\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"R\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00573519.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00573519\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m64101879.28\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m60735508.43\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3366370.85\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-01-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P60005915\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m47118584.66\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m5010794.25\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m7428252.61\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1228302.13\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1952100\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2532820.62\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m74.2\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3.1\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m403.7636261097707\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m63469219.92\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4700711.12\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2910.7\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"rubio\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Rubio, Marco\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Marco Rubio\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"R\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00458844.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00458844\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m56650061.41\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m53455375.79\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3736205.11\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-04-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P60006723\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m14245863.39\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2928690.61\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m8346507.91\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4053985.54\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m13535100\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m791439.59\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1.4000000000000001\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m26.8\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m25.4\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m166.18885723607215\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m53216332.09\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m39675849.74\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m7591247.66999999\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"trump\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Trump, Donald J.\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Donald J. Trump\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"R\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00580100.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00580100\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m49296493.8\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m47185423.71\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2111070.09\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-04-02\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P80001571\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m9641910.28\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m875672.44\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m753579.05\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m85870.58\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m747900\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2036721.63\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4.1000000000000005\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m76.8\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m6\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m94.7081997541097\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m12562427.5\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1516288.02\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m52104202.9899999\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"bush\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Bush, Jeb\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Jeb Bush\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"R\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00579458.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00579458\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m35224251.05\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m35193065.7\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m31185.35\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-04-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P60008059\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2490899.04\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m686152.3\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4432996.83\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1904747.44\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m23444100\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m-529579.95\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m-1.5\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m7.199999999999999\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m68.2\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m182.24781264481385\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m34362074.58\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m78108743.8\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3004092.01\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m\n",
      "\u001b[1;39m]\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!cat $DATA | jq '.results[0:7]'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conveniently, the first two results are Clinton and Sanders. Let's isolate the two using a range:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;39m[\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"clinton\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Clinton, Hillary\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Hillary Clinton\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"D\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00575795.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00575795\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m186735031.61\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m157763659.51\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m28971372.1\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-04-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P00003392\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m51431956.48\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m11434374.12\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m25107086.49\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m13644451.08\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m76523400\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m24342711.9\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m13\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m30.3\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m45.1\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m106.9341168047289\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m169552497.08\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m10116597.97\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m6987601.95000001\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"slug\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"sanders\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Sanders, Bernie\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"Bernie Sanders\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"D\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"committees/C00577130.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"C00577130\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_receipts\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m185864101.89\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m168349117.67\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"cash_on_hand\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m17460961.37\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2016-03-31\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2015-04-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_id\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"P60007168\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m221735971.88\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_200_499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m19404608.34\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_500_1499\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m20837551.49\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_1500_2699\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3105827.9\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2068200\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m17460961.37\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"net_primary_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m9.4\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_less_than_200_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m121.2\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"contributions_max_pct\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1.0999999999999999\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"burn_rate\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m99.45757021313398\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m182923991.19\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_support\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4334387.32\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"independent_expenditures_oppose\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m859341.11\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m\n",
      "\u001b[1;39m]\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!cat $DATA | jq '.results[0:2]'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2020 Campaign Data \n",
    "It seems the presedential campaign data isn't there yet (which makes sense since as of now, it is early in the primary season). There is however some data for congressional races.  \n",
    "\n",
    "First we'll query the API for PAC (Political Action Committees) money. There's a special endpoint to query for that, which is `https://api.propublica.org/campaign-finance/v1/2020/candidates/leaders/pac-total.json`. Saving that as JSON, we can look at the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA=\"data/pac_totals_2020.json\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at the first 5 results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;39m[\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"relative_uri\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/candidates/S4CO00395.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"GARDNER, CORY\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"REP\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"state\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/races/CO.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"district\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"00\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/committees/C00492454.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"status\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"I\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_individuals\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1995170.01\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_pacs\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1320380.83\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3360150.84\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_loans\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m793711.46\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"begin_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1701437.57\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"end_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4919791.17\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_refunds\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m46550\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"debts_owed\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-01-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-06-30\"\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"relative_uri\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/candidates/S2KY00012.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"MCCONNELL, MITCH\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"REP\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"state\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/races/KY.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"district\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"00\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/committees/C00193342.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"status\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"I\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_individuals\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2994920.43\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_pacs\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1254488.28\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4249408.71\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_loans\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m919654.68\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"begin_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3595456.04\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"end_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m7874816.47\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_refunds\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m57736.11\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"debts_owed\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-01-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-06-30\"\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"relative_uri\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/candidates/S4MI00355.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"PETERS, GARY\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"DEM\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"state\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/races/MI.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"district\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"00\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/committees/C00437889.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"status\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"I\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_individuals\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2896352.95\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_pacs\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1077617.44\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m3973970.39\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_loans\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1111493.99\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"begin_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1503727.91\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"end_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4714855.59\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_refunds\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m16060.48\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"debts_owed\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-01-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-06-30\"\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"relative_uri\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/candidates/S4NC00162.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"TILLIS, THOM R. SEN.\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"REP\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"state\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/races/NC.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"district\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"00\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/committees/C00545772.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"status\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"I\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_individuals\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1436143.46\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_pacs\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1051300\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2487443.46\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_loans\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m710301.32\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"begin_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m2025444.43\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"end_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m4387420.8\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_refunds\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m40880\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"debts_owed\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-01-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-06-30\"\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m,\n",
      "  \u001b[1;39m{\n",
      "    \u001b[0m\u001b[34;1m\"relative_uri\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/candidates/H2MD05155.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"name\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"HOYER, STENY\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"party\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"DEM\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"state\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/races/MD.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"district\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"05\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"committee\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"/committees/C00140715.json\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"status\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"I\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_individuals\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m255967.14\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_from_pacs\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m885490\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_contributions\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1141457.14\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"candidate_loans\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_disbursements\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m1051065.38\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"begin_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m634132.38\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"end_cash\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m865414.11\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"total_refunds\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;39m970\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"debts_owed\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[1;30mnull\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_from\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-01-01\"\u001b[0m\u001b[1;39m,\n",
      "    \u001b[0m\u001b[34;1m\"date_coverage_to\"\u001b[0m\u001b[1;39m: \u001b[0m\u001b[0;32m\"2019-06-30\"\u001b[0m\u001b[1;39m\n",
      "  \u001b[1;39m}\u001b[0m\u001b[1;39m\n",
      "\u001b[1;39m]\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!cat $DATA | jq '.results[0:5]'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perhaps we should put this data into a dataFrame now that we see the general shape of the data. I've converted the raw JSON file into a csv, which will make our lives easier for `pandas`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/pac_totals_2020.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>results__relative_uri</th>\n",
       "      <th>results__name</th>\n",
       "      <th>results__party</th>\n",
       "      <th>results__state</th>\n",
       "      <th>results__district</th>\n",
       "      <th>results__committee</th>\n",
       "      <th>results__status</th>\n",
       "      <th>results__total_from_individuals</th>\n",
       "      <th>results__total_from_pacs</th>\n",
       "      <th>results__total_contributions</th>\n",
       "      <th>results__candidate_loans</th>\n",
       "      <th>results__total_disbursements</th>\n",
       "      <th>results__begin_cash</th>\n",
       "      <th>results__end_cash</th>\n",
       "      <th>results__total_refunds</th>\n",
       "      <th>results__debts_owed</th>\n",
       "      <th>results__date_coverage_from</th>\n",
       "      <th>results__date_coverage_to</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>/candidates/S4CO00395.json</td>\n",
       "      <td>GARDNER, CORY</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/CO.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00492454.json</td>\n",
       "      <td>I</td>\n",
       "      <td>1995170.01</td>\n",
       "      <td>1320380.83</td>\n",
       "      <td>3360150.84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>793711.46</td>\n",
       "      <td>1701437.57</td>\n",
       "      <td>4919791.17</td>\n",
       "      <td>46550.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>/candidates/S2KY00012.json</td>\n",
       "      <td>MCCONNELL, MITCH</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/KY.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00193342.json</td>\n",
       "      <td>I</td>\n",
       "      <td>2994920.43</td>\n",
       "      <td>1254488.28</td>\n",
       "      <td>4249408.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>919654.68</td>\n",
       "      <td>3595456.04</td>\n",
       "      <td>7874816.47</td>\n",
       "      <td>57736.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>/candidates/S4MI00355.json</td>\n",
       "      <td>PETERS, GARY</td>\n",
       "      <td>DEM</td>\n",
       "      <td>/races/MI.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00437889.json</td>\n",
       "      <td>I</td>\n",
       "      <td>2896352.95</td>\n",
       "      <td>1077617.44</td>\n",
       "      <td>3973970.39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1111493.99</td>\n",
       "      <td>1503727.91</td>\n",
       "      <td>4714855.59</td>\n",
       "      <td>16060.48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>/candidates/S4NC00162.json</td>\n",
       "      <td>TILLIS, THOM R. SEN.</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/NC.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00545772.json</td>\n",
       "      <td>I</td>\n",
       "      <td>1436143.46</td>\n",
       "      <td>1051300.00</td>\n",
       "      <td>2487443.46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710301.32</td>\n",
       "      <td>2025444.43</td>\n",
       "      <td>4387420.80</td>\n",
       "      <td>40880.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>/candidates/H2MD05155.json</td>\n",
       "      <td>HOYER, STENY</td>\n",
       "      <td>DEM</td>\n",
       "      <td>/races/MD.json</td>\n",
       "      <td>5</td>\n",
       "      <td>/committees/C00140715.json</td>\n",
       "      <td>I</td>\n",
       "      <td>255967.14</td>\n",
       "      <td>885490.00</td>\n",
       "      <td>1141457.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1051065.38</td>\n",
       "      <td>634132.38</td>\n",
       "      <td>865414.11</td>\n",
       "      <td>970.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>/candidates/S4IA00129.json</td>\n",
       "      <td>ERNST, JONI K</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/IA.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00546788.json</td>\n",
       "      <td>I</td>\n",
       "      <td>1001901.01</td>\n",
       "      <td>864463.53</td>\n",
       "      <td>1866364.54</td>\n",
       "      <td>NaN</td>\n",
       "      <td>740748.29</td>\n",
       "      <td>1363149.69</td>\n",
       "      <td>3438302.17</td>\n",
       "      <td>20403.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>/candidates/S8AZ00221.json</td>\n",
       "      <td>MCSALLY, MARTHA</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/AZ.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00666040.json</td>\n",
       "      <td>I</td>\n",
       "      <td>4049121.69</td>\n",
       "      <td>830650.00</td>\n",
       "      <td>4924371.69</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2046560.38</td>\n",
       "      <td>923793.51</td>\n",
       "      <td>4376711.44</td>\n",
       "      <td>99679.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>/candidates/S0AL00156.json</td>\n",
       "      <td>JONES, DOUG</td>\n",
       "      <td>DEM</td>\n",
       "      <td>/races/AL.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00640623.json</td>\n",
       "      <td>C</td>\n",
       "      <td>2599782.14</td>\n",
       "      <td>817712.94</td>\n",
       "      <td>3417495.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1527526.54</td>\n",
       "      <td>2131165.71</td>\n",
       "      <td>4259540.86</td>\n",
       "      <td>39286.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>/candidates/S2MT00096.json</td>\n",
       "      <td>DAINES, STEVEN</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/MT.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00491357.json</td>\n",
       "      <td>I</td>\n",
       "      <td>1417549.82</td>\n",
       "      <td>794692.49</td>\n",
       "      <td>2212242.31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>581045.41</td>\n",
       "      <td>1450176.34</td>\n",
       "      <td>3510319.36</td>\n",
       "      <td>16672.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>/candidates/S2TX00106.json</td>\n",
       "      <td>CORNYN, JOHN SEN</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/TX.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00369033.json</td>\n",
       "      <td>I</td>\n",
       "      <td>2153832.99</td>\n",
       "      <td>761650.00</td>\n",
       "      <td>2915482.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1264464.62</td>\n",
       "      <td>5790126.35</td>\n",
       "      <td>9070560.43</td>\n",
       "      <td>7800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>/candidates/S8MN00578.json</td>\n",
       "      <td>SMITH, TINA</td>\n",
       "      <td>DEM</td>\n",
       "      <td>/races/MN.json</td>\n",
       "      <td>99</td>\n",
       "      <td>/committees/C00663781.json</td>\n",
       "      <td>C</td>\n",
       "      <td>1735752.63</td>\n",
       "      <td>748545.09</td>\n",
       "      <td>2489897.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000560.09</td>\n",
       "      <td>433782.60</td>\n",
       "      <td>2078580.97</td>\n",
       "      <td>7430.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>/candidates/H8MA02041.json</td>\n",
       "      <td>NEAL, RICHARD E MR.</td>\n",
       "      <td>DEM</td>\n",
       "      <td>/races/MA.json</td>\n",
       "      <td>1</td>\n",
       "      <td>/committees/C00226522.json</td>\n",
       "      <td>I</td>\n",
       "      <td>356226.27</td>\n",
       "      <td>747650.00</td>\n",
       "      <td>1103876.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>776745.69</td>\n",
       "      <td>3308302.26</td>\n",
       "      <td>3962356.46</td>\n",
       "      <td>6800.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>/candidates/S4GA11285.json</td>\n",
       "      <td>PERDUE, DAVID</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/GA.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00547570.json</td>\n",
       "      <td>I</td>\n",
       "      <td>1287948.70</td>\n",
       "      <td>738150.00</td>\n",
       "      <td>2026098.70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>532198.26</td>\n",
       "      <td>1703670.97</td>\n",
       "      <td>4862783.30</td>\n",
       "      <td>23953.13</td>\n",
       "      <td>820583.21</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>/candidates/H6TX08100.json</td>\n",
       "      <td>BRADY, KEVIN</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/TX.json</td>\n",
       "      <td>8</td>\n",
       "      <td>/committees/C00311043.json</td>\n",
       "      <td>I</td>\n",
       "      <td>214522.05</td>\n",
       "      <td>724150.00</td>\n",
       "      <td>938672.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>596780.60</td>\n",
       "      <td>722637.18</td>\n",
       "      <td>1210207.81</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>/candidates/S0NH00219.json</td>\n",
       "      <td>SHAHEEN, JEANNE</td>\n",
       "      <td>DEM</td>\n",
       "      <td>/races/NH.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00457325.json</td>\n",
       "      <td>I</td>\n",
       "      <td>2476528.97</td>\n",
       "      <td>722875.96</td>\n",
       "      <td>3199404.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>943337.78</td>\n",
       "      <td>467428.19</td>\n",
       "      <td>2882289.70</td>\n",
       "      <td>38310.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>/candidates/S0SC00149.json</td>\n",
       "      <td>GRAHAM, LINDSEY O.</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/SC.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00458828.json</td>\n",
       "      <td>I</td>\n",
       "      <td>3723964.40</td>\n",
       "      <td>714000.00</td>\n",
       "      <td>4437964.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1805551.48</td>\n",
       "      <td>3200959.20</td>\n",
       "      <td>6460822.56</td>\n",
       "      <td>76225.91</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>/candidates/H2SC02042.json</td>\n",
       "      <td>CLYBURN, JAMES E.</td>\n",
       "      <td>DEM</td>\n",
       "      <td>/races/SC.json</td>\n",
       "      <td>6</td>\n",
       "      <td>/committees/C00255562.json</td>\n",
       "      <td>I</td>\n",
       "      <td>287518.79</td>\n",
       "      <td>712520.00</td>\n",
       "      <td>1000038.79</td>\n",
       "      <td>NaN</td>\n",
       "      <td>742470.92</td>\n",
       "      <td>905678.59</td>\n",
       "      <td>1165275.11</td>\n",
       "      <td>8100.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>/candidates/S6VA00093.json</td>\n",
       "      <td>WARNER, MARK ROBERT</td>\n",
       "      <td>DEM</td>\n",
       "      <td>/races/VA.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00438713.json</td>\n",
       "      <td>I</td>\n",
       "      <td>2114261.45</td>\n",
       "      <td>710924.00</td>\n",
       "      <td>2825185.45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>870140.03</td>\n",
       "      <td>3066836.33</td>\n",
       "      <td>5412994.84</td>\n",
       "      <td>21814.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>/candidates/S6ME00159.json</td>\n",
       "      <td>COLLINS, SUSAN M.</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/ME.json</td>\n",
       "      <td>0</td>\n",
       "      <td>/committees/C00314575.json</td>\n",
       "      <td>I</td>\n",
       "      <td>2363315.03</td>\n",
       "      <td>710019.05</td>\n",
       "      <td>3073334.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>744842.67</td>\n",
       "      <td>2627724.77</td>\n",
       "      <td>5409262.73</td>\n",
       "      <td>14700.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>/candidates/H2IL13120.json</td>\n",
       "      <td>DAVIS, RODNEY L</td>\n",
       "      <td>REP</td>\n",
       "      <td>/races/IL.json</td>\n",
       "      <td>13</td>\n",
       "      <td>/committees/C00521948.json</td>\n",
       "      <td>I</td>\n",
       "      <td>197555.00</td>\n",
       "      <td>693697.20</td>\n",
       "      <td>892352.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>451025.65</td>\n",
       "      <td>19576.43</td>\n",
       "      <td>532913.84</td>\n",
       "      <td>1650.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2019-06-30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         results__relative_uri         results__name results__party  \\\n",
       "0   /candidates/S4CO00395.json         GARDNER, CORY            REP   \n",
       "1   /candidates/S2KY00012.json      MCCONNELL, MITCH            REP   \n",
       "2   /candidates/S4MI00355.json          PETERS, GARY            DEM   \n",
       "3   /candidates/S4NC00162.json  TILLIS, THOM R. SEN.            REP   \n",
       "4   /candidates/H2MD05155.json          HOYER, STENY            DEM   \n",
       "5   /candidates/S4IA00129.json         ERNST, JONI K            REP   \n",
       "6   /candidates/S8AZ00221.json       MCSALLY, MARTHA            REP   \n",
       "7   /candidates/S0AL00156.json           JONES, DOUG            DEM   \n",
       "8   /candidates/S2MT00096.json        DAINES, STEVEN            REP   \n",
       "9   /candidates/S2TX00106.json      CORNYN, JOHN SEN            REP   \n",
       "10  /candidates/S8MN00578.json           SMITH, TINA            DEM   \n",
       "11  /candidates/H8MA02041.json   NEAL, RICHARD E MR.            DEM   \n",
       "12  /candidates/S4GA11285.json         PERDUE, DAVID            REP   \n",
       "13  /candidates/H6TX08100.json          BRADY, KEVIN            REP   \n",
       "14  /candidates/S0NH00219.json       SHAHEEN, JEANNE            DEM   \n",
       "15  /candidates/S0SC00149.json    GRAHAM, LINDSEY O.            REP   \n",
       "16  /candidates/H2SC02042.json     CLYBURN, JAMES E.            DEM   \n",
       "17  /candidates/S6VA00093.json   WARNER, MARK ROBERT            DEM   \n",
       "18  /candidates/S6ME00159.json     COLLINS, SUSAN M.            REP   \n",
       "19  /candidates/H2IL13120.json       DAVIS, RODNEY L            REP   \n",
       "\n",
       "    results__state  results__district          results__committee  \\\n",
       "0   /races/CO.json                  0  /committees/C00492454.json   \n",
       "1   /races/KY.json                  0  /committees/C00193342.json   \n",
       "2   /races/MI.json                  0  /committees/C00437889.json   \n",
       "3   /races/NC.json                  0  /committees/C00545772.json   \n",
       "4   /races/MD.json                  5  /committees/C00140715.json   \n",
       "5   /races/IA.json                  0  /committees/C00546788.json   \n",
       "6   /races/AZ.json                  0  /committees/C00666040.json   \n",
       "7   /races/AL.json                  0  /committees/C00640623.json   \n",
       "8   /races/MT.json                  0  /committees/C00491357.json   \n",
       "9   /races/TX.json                  0  /committees/C00369033.json   \n",
       "10  /races/MN.json                 99  /committees/C00663781.json   \n",
       "11  /races/MA.json                  1  /committees/C00226522.json   \n",
       "12  /races/GA.json                  0  /committees/C00547570.json   \n",
       "13  /races/TX.json                  8  /committees/C00311043.json   \n",
       "14  /races/NH.json                  0  /committees/C00457325.json   \n",
       "15  /races/SC.json                  0  /committees/C00458828.json   \n",
       "16  /races/SC.json                  6  /committees/C00255562.json   \n",
       "17  /races/VA.json                  0  /committees/C00438713.json   \n",
       "18  /races/ME.json                  0  /committees/C00314575.json   \n",
       "19  /races/IL.json                 13  /committees/C00521948.json   \n",
       "\n",
       "   results__status  results__total_from_individuals  results__total_from_pacs  \\\n",
       "0                I                       1995170.01                1320380.83   \n",
       "1                I                       2994920.43                1254488.28   \n",
       "2                I                       2896352.95                1077617.44   \n",
       "3                I                       1436143.46                1051300.00   \n",
       "4                I                        255967.14                 885490.00   \n",
       "5                I                       1001901.01                 864463.53   \n",
       "6                I                       4049121.69                 830650.00   \n",
       "7                C                       2599782.14                 817712.94   \n",
       "8                I                       1417549.82                 794692.49   \n",
       "9                I                       2153832.99                 761650.00   \n",
       "10               C                       1735752.63                 748545.09   \n",
       "11               I                        356226.27                 747650.00   \n",
       "12               I                       1287948.70                 738150.00   \n",
       "13               I                        214522.05                 724150.00   \n",
       "14               I                       2476528.97                 722875.96   \n",
       "15               I                       3723964.40                 714000.00   \n",
       "16               I                        287518.79                 712520.00   \n",
       "17               I                       2114261.45                 710924.00   \n",
       "18               I                       2363315.03                 710019.05   \n",
       "19               I                        197555.00                 693697.20   \n",
       "\n",
       "    results__total_contributions  results__candidate_loans  \\\n",
       "0                     3360150.84                       NaN   \n",
       "1                     4249408.71                       NaN   \n",
       "2                     3973970.39                       NaN   \n",
       "3                     2487443.46                       NaN   \n",
       "4                     1141457.14                       NaN   \n",
       "5                     1866364.54                       NaN   \n",
       "6                     4924371.69                       NaN   \n",
       "7                     3417495.08                       NaN   \n",
       "8                     2212242.31                       NaN   \n",
       "9                     2915482.99                       NaN   \n",
       "10                    2489897.72                       NaN   \n",
       "11                    1103876.27                       NaN   \n",
       "12                    2026098.70                       NaN   \n",
       "13                     938672.05                       NaN   \n",
       "14                    3199404.93                       NaN   \n",
       "15                    4437964.40                       NaN   \n",
       "16                    1000038.79                       NaN   \n",
       "17                    2825185.45                       NaN   \n",
       "18                    3073334.08                       NaN   \n",
       "19                     892352.20                       NaN   \n",
       "\n",
       "    results__total_disbursements  results__begin_cash  results__end_cash  \\\n",
       "0                      793711.46           1701437.57         4919791.17   \n",
       "1                      919654.68           3595456.04         7874816.47   \n",
       "2                     1111493.99           1503727.91         4714855.59   \n",
       "3                      710301.32           2025444.43         4387420.80   \n",
       "4                     1051065.38            634132.38          865414.11   \n",
       "5                      740748.29           1363149.69         3438302.17   \n",
       "6                     2046560.38            923793.51         4376711.44   \n",
       "7                     1527526.54           2131165.71         4259540.86   \n",
       "8                      581045.41           1450176.34         3510319.36   \n",
       "9                     1264464.62           5790126.35         9070560.43   \n",
       "10                    1000560.09            433782.60         2078580.97   \n",
       "11                     776745.69           3308302.26         3962356.46   \n",
       "12                     532198.26           1703670.97         4862783.30   \n",
       "13                     596780.60            722637.18         1210207.81   \n",
       "14                     943337.78            467428.19         2882289.70   \n",
       "15                    1805551.48           3200959.20         6460822.56   \n",
       "16                     742470.92            905678.59         1165275.11   \n",
       "17                     870140.03           3066836.33         5412994.84   \n",
       "18                     744842.67           2627724.77         5409262.73   \n",
       "19                     451025.65             19576.43          532913.84   \n",
       "\n",
       "    results__total_refunds  results__debts_owed results__date_coverage_from  \\\n",
       "0                 46550.00                  NaN                  2019-01-01   \n",
       "1                 57736.11                  NaN                  2019-01-01   \n",
       "2                 16060.48                  NaN                  2019-01-01   \n",
       "3                 40880.00                  NaN                  2019-01-01   \n",
       "4                   970.00                  NaN                  2019-01-01   \n",
       "5                 20403.00                  NaN                  2019-01-01   \n",
       "6                 99679.75                  NaN                  2019-01-01   \n",
       "7                 39286.75                  NaN                  2019-01-01   \n",
       "8                 16672.75                  NaN                  2019-01-01   \n",
       "9                  7800.00                  NaN                  2019-01-01   \n",
       "10                 7430.16                  NaN                  2019-01-01   \n",
       "11                 6800.00                  NaN                  2019-01-01   \n",
       "12                23953.13            820583.21                  2019-01-01   \n",
       "13                     NaN                  NaN                  2019-01-01   \n",
       "14                38310.30                  NaN                  2019-01-01   \n",
       "15                76225.91                  NaN                  2019-01-01   \n",
       "16                 8100.00                  NaN                  2019-01-01   \n",
       "17                21814.00                  NaN                  2019-01-01   \n",
       "18                14700.00                  NaN                  2019-01-01   \n",
       "19                 1650.00                  NaN                  2019-01-01   \n",
       "\n",
       "   results__date_coverage_to  \n",
       "0                 2019-06-30  \n",
       "1                 2019-06-30  \n",
       "2                 2019-06-30  \n",
       "3                 2019-06-30  \n",
       "4                 2019-06-30  \n",
       "5                 2019-06-30  \n",
       "6                 2019-06-30  \n",
       "7                 2019-06-30  \n",
       "8                 2019-06-30  \n",
       "9                 2019-06-30  \n",
       "10                2019-06-30  \n",
       "11                2019-06-30  \n",
       "12                2019-06-30  \n",
       "13                2019-06-30  \n",
       "14                2019-06-30  \n",
       "15                2019-06-30  \n",
       "16                2019-06-30  \n",
       "17                2019-06-30  \n",
       "18                2019-06-30  \n",
       "19                2019-06-30  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We definitely can see the data we need. So let's move to data visualization!  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Visualization\n",
    "First, we can make a plot to see how many candidates fit into certain brackets of PAC money. It will be a very basic histogram. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'No. of Candidates')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYEAAAEPCAYAAACk43iMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAHLhJREFUeJzt3Xm4HFW57/HvjwTCIHOChymGAPIQvUeBMDkgg0QEDhwQJDkODGrO9aKCF5QErhzwHM8DB1BEEQiDoiKIDBdkECIhF/DIkCAgUyRAGAOEeVBIgu/9Y63N7mx2d6r37q7enfp9nqefrq6qrvXW7tr9dq1atZYiAjMzq6blOh2AmZl1jpOAmVmFOQmYmVWYk4CZWYU5CZiZVZiTgJlZhTkJmJlVmJOAmVmFOQmYmVXY8E4HsDQjR46MMWPGdDoMM7OuMXv27OcjYlSRdYd8EhgzZgyzZs3qdBhmZl1D0mNF13V1kJlZhTkJmJlVmJOAmVmFOQmYmVWYk4CZWYWVmgQkbSbprprHq5IOLzMGMzPrVWoT0YiYA3wYQNIw4Cng8jJjMDOzXp2sDtoFeDgiCrdnNTOz1upkEpgIXNjB8s3MKq8jdwxLWgHYC5haZ/lkYDLA6NGjB1zOmClXD/i9teadsEdLtmNmNtR06kzg08CdEfFsfwsjYlpEjI+I8aNGFer+wszMBqBTSWASrgoyM+u40pOApJWBXYHLyi7bzMyWVPo1gYj4K7B22eWamdm7+Y5hM7MKcxIwM6swJwEzswpzEjAzqzAnATOzCnMSMDOrMCcBM7MKcxIwM6swJwEzswpzEjAzqzAnATOzCnMSMDOrMCcBM7MKcxIwM6swJwEzswpzEjAzqzAnATOzCnMSMDOrMCcBM7MKcxIwM6swJwEzsworPQlIWkPSJZIelPSApO3LjsHMzJLhHSjzh8DvImI/SSsAK3cgBjMzo+QkIGk1YAfgIICIWAgsLDMGMzPrVXZ10FhgAfBTSX+SdI6kVfquJGmypFmSZi1YsKDkEM3MqqPsJDAc2BI4IyK2AN4ApvRdKSKmRcT4iBg/atSokkM0M6uOspPAk8CTEXFbfn0JKSmYmVkHlJoEIuIZ4AlJm+VZuwD3lxmDmZn1KnRhWNLmwOoRcWt+vRLwHWAccENE/KiJMr8OXJBbBj0CHNxcyGZm1ipFWwf9BPhv4Nb8+mRSC5+bgRMlrRgRJxXZUETcBYxvMk4zM2uDotVBHwT+CCBpeeDzwOERsRtwNHBIe8IzM7N2KpoEVgFezdPb5deX5dd3Au9rcVxmZlaCokngEdKXP8A+wJ8i4oX8eiTwWqsDMzOz9it6TeAHwBmS9ge2YMmLuTsC97Q4LjMzK0GhJBAR50p6CNgamBIRN9QsfhE4tR3BmZlZexXuOygibgJu6mf+ca0MyMzMylP4ZjFJ60g6UdINkv4i6QN5/mHuDtrMrDsVSgKStgHmAp8B5gEbAyPy4nWBI9oRnJmZtVfRM4EfADOA9wP/Cqhm2e3ANi2Oy8zMSlD0msCWwN4R8XdJ6rPsBWCd1oZlZmZlKHom8ApQr0/nscCzrQnHzMzKVDQJXAEcL2lszbyQNBI4kt67h83MrIsUTQJTSN1G3E9vM9EzgTnA34BjWx+amZm1W9GbxV6StB3wBdIYAG+QbhI7B/h5RLzVvhDNzKxdmrlZbCFwbn6YmdkyoOh9Am/newX6W7aVpLdbG5aZmZWh6DWBvs1Cay0PLG5BLGZmVrK61UGSRgNjamZtIWnFPqutCBwIPNr60MzMrN0aXRM4GPg3IPLjjDrr/Q34covjMjOzEjRKAj8BLiFVBd0DfI53jxuwEHjcrYPMzLpT3SQQEQuABQCSNgLm5xZCgyJpHmkksreBxRHhQefNzDqk6H0CjwFIGg6MJl0L6LvO/U2Uu1NEPN/E+mZm1gaFkoCk5YHTSBeBR9RZbVirgjIzs3IUbSJ6LLAn8CXSNYKvkS4c30AaX+CfmigzgOslzZY0uYn3mZlZixVNAp8FjgMuzq9vj4ifR8QE4BZg7ybK/GhEbAl8GjhU0g59V5A0WdIsSbMWLFjQxKbNzKwZRZPAhsBfIuJt4E1gzZplF5BGHCskIp7Oz88Bl9PPgDQRMS0ixkfE+FGj6vVgbWZmg1U0CcwH1sjTjwK1v943LlqYpFUkrdozDUwA7i36fjMza62iHcjNBD4O/BY4GzhZ0ibAW8ABwIUFt/Ne4PI8ONlw4FcR8btmAjYzs9YpmgSOAUYCRMSpeYjJ/YCVgB8B3y2ykYh4BPjQAOI0M7M2KHqfwDPAMzWvf0AafN7MzLpY0WsCZma2DGrUi+ijpDb9hUTE2KWvZWZmQ0mj6qBLWTIJTARWBqYDzwHrALuShpq8qF0BmplZ+zTqQO7InmlJRwMPA3tExBs1898DXEUahN7MzLpM0WsChwIn1SYAgIh4HTg5Lzczsy5TNAmsTmrj359/AN7TmnDMzKxMRe8TuBI4SdKrwG8j4i1JI4C9gBNJN5GZmVmXKZoEvgr8jNSBXEh6DViV1KPolXm5mZl1maI3i70C7CNpHLA1qQroGeCOJgeTMTOzIaTomQDwzuhh/tI3M1tGNLpZbBzwcK7/H7e0DfmMwMys+zQ6E7gX2A64PU/Xu3tYeZmHlzQz6zKNksBO9Fb97FRCLGZmVrJGdwz/v/6mzcxs2eFeRM3MKqzRheG/01wvor4mYGbWZRpdE/gGvUlgeeAI4HXgClIvou8F9gZWAU5pY4xmZtYmja4J/LhnWtL3gduA/SMiauZPAX4DbNTOIM3MrD2KXhP4InB2bQIAyK/PBj7f6sDMzKz9iiaBYcDmdZZ9oIntmJnZEFK024gLgP+UNJzUYVzPyGJ7A98Fzm2mUEnDgFnAUxGxZzPvNTOz1imaBP43sIj0hX9izfy3gLOAbzdZ7mHAA8BqTb7PzMxaqFA1TkQsjIhvAhsAOwP/kp83iIjDI2Jh0QIlbQDsAZwzgHjNzKyFmu1F9EVgsHcPn0o6c1i13gqSJgOTAUaPHj3I4gZvzJSrW7KdeSfs0ZLtmJm1SuEkIGlFYAfS2cCKfRZHRJxRYBt7As9FxGxJO9ZbLyKmAdMAxo8fX/iGNTMza06hJCDpY8BlwMg6qwSw1CQAfBTYS9LupESymqRfRoSbmJqZdUDRpp2nAQ8DWwAjImK5Po9CXUZExNSI2CAixgATgRlOAGZmnVO0OmgzYN+IuLudwZiZWbmKJoF7SOMKt0xEzARmtnKbZmbWnKLVQV8FvinpE+0MxszMylX0TGA6sDIwQ9Ii4NW+K0TEOq0MzMzM2q9oEjidJsYWMDOz7lAoCUTEcW2Ow8zMOsC9f5qZVVgzdwxvD3wJeD/vvmOYiNimhXGZmVkJCp0JSNoVuInUZcTHgAWkoSY/BKwN3NuuAM3MrH2KVgd9F/ghqfdPgO9ExM6ks4JFuL2/mVlXKpoExgHXAn8ntRJaBSAiHgOOA45pR3BmZtZeRZPAm8ByeUzh+cDGNcteJVUTmZlZlyl6YfhuUv9B04EbgKmSngIWkqqK/tye8MzMrJ2KngmcSu/NYkcDbwDXATeSxho+tPWhmZlZuxW9WeyamumnJG0FbAKsBDzYzPCSZmY2dDRMApJWBRZFxJu18/O1gYfyaGMjSNVCZmbWZepWB0naFngR2LbB+7cFXpC0Q6sDMzOz9mt0TeBI4NcRUXdg+bzsQuCwVgdmZmbt1ygJfAK4tMA2LifdRWxmZl2mURJYndQ9xNI8D6zRmnDMzKxMjZLAsyx5U1g9Y/O6ZmbWZRolgenAoZLqtiDKyw4Frm91YGZm1n6NksD3SB3EXS1pXN+FkjYHriLdSfyfRQqTtKKk2yXdLek+SccPJGgzM2uNur/yI+IRSXsAFwF/lvQ08DjpzuHRwPrA08DuEfFIwfLeAnaOiNclLQ/cIunaiLh1UHthZmYD0vBmsYj4g6RNgc8CO5C++CFV/8wELul7I9lSthekcQgAls8Pj11sZtYhS+02In/J/zw/Bk3SMGA2qduJ0yPitlZs18zMmlf6GMMR8XZEfJjU/fQ2kj7Ydx1JkyXNkjRrwYIirVTNzGwgOjbQfES8TKpS2q2fZdMiYnxEjB81alTpsZmZVUWpSUDSKElr5OmVgE8CD5YZg5mZ9So6qEyrrAucn68LLAdcHBFXlRyDmZlljW4EewTYJyLulnQscE5EPD2YwiLiHmCLwWzDzMxap1F10PrAynn63/A4wmZmy5xG1UEPA1+TtDYg4COSRtZbuXb0MTMz6w6NksBU4HxgEumGru83WDeAYS2My8zMStCo24grJK0FrEfqLmJf4E9lBWZmZu23tG4j/g48Kelg4OaIeKGcsMzMrAyFmohGxPkAktYDtgfWIo0//MfBthgyM7POKZQEJC0H/Bj4CkvW/b8taRrw9XzWYGZmXaToHcPfBQ4BjgbGACvl56Pz/ONaH5qZmbVb0TuGvwj8n4g4uWbe48BJkgL4BnBsq4MzM7P2KnomsA5wT51l9+TlZmbWZYomgb8AE+ssmwjMaU04ZmZWpqLVQf8BXCRpNHAJ8Czp1//+wE7UTxBmZjaEFW0ierGkl4HjgR+ShoVcRBohbLeImN6+EM3MrF0KdyUdEdcD1+fmoiOB590s1MysuzU9nkD+4n+uDbGYmVnJOja8pJmZdZ6TgJlZhTkJmJlVmJOAmVmFOQmYmVXYoJOApLMlnduKYMzMrFytOBPYKT+WStKGkm6U9ICk+yQd1oLyzcxsgJq+T6CviNikidUXA0dExJ2SVgVmS5oeEfcPNg4zM2teqdcEImJ+RNyZp18DHgDWLzMGMzPrVfhMQNJw4DPAx+gdXvJm4LKIWNxswZLGAFsAtzX7XjMza42iw0uuA1wP/CMwj9SL6PbAocDdkiZExIKihUp6D3ApcHhEvNrP8snAZIDRo0cX3WxljJly9aC3Me+EPVoQiZl1u6LVQd8H1ga2jYixEbF9RIwFts3zv1+0QEnLkxLABRFxWX/rRMS0iBgfEeNHjRpVdNNmZtakoklgd+CoiLijdmZ+PRUo9LNSkoBzgQcionDiMDOz9iiaBEYAr9VZ9hqwQsHtfBT4ArCzpLvyY/eC7zUzsxYremH4VuAoSTMi4o2emZJWAY7Ky5cqIm4B1HSUZmbWFkWTwBHAjcATkq6nd3jJT5G+1HdsS3RmZtZWhaqDIuIuYFNgGjAK2JWUBM4ENo2Iu9sWoZmZtU0zw0s+D0xpYyxmZlYy9yJqZlZhdc8EJM1oYjsREbu0IB4zMytRo+qgFwq8f13gI0C0JhwzMytT3SQQEfvXWyZpNKlp6J7A88APWh+amZm1W1NdSUvahHSH8OeB5/L0WRHxtzbEZmZmbVa0A7kPAMcA+wNPAIcB50XEwjbGZmZmbdawdZCkrSRdBtxD6vb5y6T7As50AjAz636NWgddC0wgJYCJEfGb0qIyM7NSNKoO+lR+3hA4XdLpjTYUEeu0LCozMytFoyRwfGlRmJlZRzRqIuokYGa2jHO3EWZmFeYkYGZWYU4CZmYV5iRgZlZhTgJmZhXmJGBmVmFOAmZmFVZqEpB0nqTnJN1bZrlmZta/ss8EfgbsVnKZZmZWR6lJICJuAl4ss0wzM6uvqUFlyiJpMjAZYPTo0R2OpnXGTLm60yG8YyjFAjDvhD06HUJb+O/cPar6WQ3JC8MRMS0ixkfE+FGjRnU6HDOzZdaQTAJmZlYOJwEzsworu4nohcAfgc0kPSnpS2WWb2ZmSyr1wnBETCqzPDMza8zVQWZmFeYkYGZWYU4CZmYV5iRgZlZhTgJmZhXmJGBmVmFOAmZmFeYkYGZWYU4CZmYV5iRgZlZhTgJmZhXmJGBmVmFOAmZmFeYkYGZWYU4CZmYV5iRgZlZhTgJmZhXmJGBmVmFOAmZmFeYkYGZWYaUnAUm7SZojaa6kKWWXb2ZmvUpNApKGAacDnwbGAZMkjSszBjMz61X2mcA2wNyIeCQiFgIXAXuXHIOZmWVlJ4H1gSdqXj+Z55mZWQcML7k89TMv3rWSNBmYnF++LmlOC8oeCTzfgu10SrfHDw32QSeWHMnAdfXnoBO7O/6s2/ehUPyD/J94X9EVy04CTwIb1rzeAHi670oRMQ2Y1sqCJc2KiPGt3GaZuj1+8D4MBd0eP3T/Pgy1+MuuDroD2FTSRpJWACYCV5Ycg5mZZaWeCUTEYklfA64DhgHnRcR9ZcZgZma9yq4OIiKuAa4pu1xaXL3UAd0eP3gfhoJujx+6fx+GVPyKeNd1WTMzqwh3G2FmVmURMaQfwGbAXTWPV4HDgbWA6cBD+XnNvL6A04C5wD3AljXbOjCv/xBwYM38rYA/5/ecRu8ZUr9lDGAfvgncB9wLXAisCGwE3Ja3/WtghbzuiPx6bl4+pmY7U/P8OcCnaubvlufNBabUzO+3jAHuw2E5/vuAwxv9fYbKZwCcBzwH3Fszr2MxNyqjifj3z5/B34HxfdZvyfExkGOwyX04CXgw/w0uB9YYqvtQJ/5/z7HfBVwPrDdUj6FC/yeD3UCZD9LF5GdIbWD/q+dgAKYAJ+bp3YFr8x9rO+C2mj/qI/l5zTzd84e9Hdg+v+da4NN5fr9lNBnz+sCjwEr59cXAQfl5Yp53JvDVPP2/gDPz9ETg13l6HHB3Prg3Ah7Of49heXossEJeZ1xNWe8qYwD78EFSAliZdB3p98CmQ/0zAHYAtmTJf+COxVyvjCbj35z0w2gmNUmglccHTR6DA9iHCcDwPH1izd9nyO1DnfhXq5n+Rk05Q+4YKvR/MtgNlPnIB88f8vQcYN08vS4wJ0+fBUyqec+cvHwScFbN/LPyvHWBB2vmv7NevTKajLnnLum1SF+gVwGfIt0s0vOPsD1wXZ6+Dtg+Tw/P64n062VqzXavy+975715/tT8UL0yBrAP+wPn1Lz+DvDtbvgMgDEs+Q/csZjrldFM/DXzZ7JkEmjZ8dHsMdjsZ9Bn2T7ABUN5H5YS/1TgjKF8DC3t0W3XBCaSqlMA3hsR8wHy8zp5fr2uKRrNf7Kf+Y3KKCwingJOBh4H5gOvALOBlyNicT9lvhNnXv4KsPYA9mvtBmU0615gB0lrS1qZ9GtkQ7rkM+ijkzG3s9uUVh4fzR6Dg3EI6ZdtV+2DpO9JegL4HHDsAOMfEsdQ1ySBfHPZXsBvlrZqP/NiAPNbQtKapE7yNgLWA1Yh9aJar8xWxd+y/YqIB0in7dOB35FOpxc3eMuQ+gwKKiPmdu5nK+Mv5XOSdAzpOLpggOV2bB8i4piI2JAU+9cGWOaQOIa6JgmQvjjvjIhn8+tnJa0LkJ+fy/PrdU3RaP4G/cxvVEYzPgk8GhELImIRcBnwEWANST33adSW+U6cefnqwIsD2K/nG5TRtIg4NyK2jIgdcjwP0T2fQa1Oxlyo25QBauXx0ewx2DRJBwJ7Ap+LXK/RbfuQ/Qr4zADjHxLHUDclgUn0VgVB6m7iwDx9IHBFzfwvKtkOeCWfTl0HTJC0Zv51PoFUfzgfeE3SdpIEfLHPtvoroxmPA9tJWjlvfxfgfuBGYL868feUuR8wI/+TXAlMlDRC0kakC7O3U6crjvyeemU0TdI6+Xk0sC/ps+iWz6BWJ2OuV0YrtPL4aPYYbIqk3YCjgL0i4q/dtg+SNq15uReppVNPmd13DA3mgkJZD1KrlBeA1WvmrQ3cQPpFegOwVp4v0sA1D5OaXtVePDuE1LRqLnBwzfzxpHrvh4Ef09tMq98yBhD/8flAuRf4BallwljSwTeXVMU1Iq+7Yn49Ny8fW7OdY3KMc8itCPL83YG/5GXH1Mzvt4wB7sPNpOR1N7BLN3wGpEQ1H1hE+gX1pU7G3KiMJuLfJ0+/BTzLkhdMW3J8DOQYbHIf5pLqtXuafZ85VPehTvyX5s/9HuC3wPpD9Rgq8vAdw2ZmFdZN1UFmZtZiTgJmZhXmJGBmVmFOAmZmFeYkYGZWYU4C1nKSjpMUNY+nJV0qaeN+1pWkJ/J6Yxpsc0tJF0t6RtIiSU9JOk/S5g3eM7wmhgP6WX5wXtbo7uchSdKXc+wrtni7M1u5PRv6nASsXV6ht/OvI4EPAzdIWqXPeh+n967Jif1tSNJngVuBNUjdiO8CfAv4B+CmArG8TrrZsK+JeVk3uoL0t32r04FYd3MSsHZZHBG35sevSHc9vo9000+tScBrpLtC3/VFLWkDUp/uv4iICRFxUUTcFBG/iojdgYMLxPJbYDdJq9dsdySwM+kOzK4TqRuSW6MFN/pIWk3S2ZKeBT4h6a+SZkvaoQWh2hDnJGBlmZ2fx/TMyH267Af8X+BnwD9KGtfnfZNJ/ckf2d9GI+KqAmXfDCwg3W3bY3/gMVLyWYKkdST9QtKL+QtxhqQt+6zzpKQTJB2Rq6ZelHSBpNX6rLd2/oJ9TtKbkm6RtHXN8sslTe8nhu9Jmi9pWH871Lc6SNIm+fVncnmv5BiPzV0SNHIi6azoGNLntA8pcY5cyvtsGeAkYGUZk5+fqZm3K+mL5iLSLf6LeffZwCeA2yPipUGUHaTBR2q3PSmX258rSVVO3yR9Oa4AzJQ0ts96/0IadOQrpH7l/xn4j56F+Qt6BrATcERe/hLwe+W+mIBzgJ2V+mTqed9ywBeAn0fE203u6ynAy6TkeiGpy5J9Gr4j/Y1/GRHnAK9HxHURcVxEXNZk2daFnASsbfKF2eGS3g/8hFTt8/uaVSaRenacHhELSF+YfZPA+qRO+AbrItKX7ShJ6wMfo58kIGlPYFtg/4g4PyKuJA1tuJj0RV7rTWDfiLgmIs4CfkrqXK/HgaRRwCZExC8i4nekHidfIiUYSF1zz6e3szBIPc9uSDo7ataMiPhWREyPiG+RhqLcdynvmQ9sJek9AyjPupyTgLXL2qROtxaROuoaCxwQucfD/Cv5n4FLI3WxDemX68a11SXZoOu9I+IOUvXPfsABwP0RcW8/q24DzI+IP9S893XgalLiqDWjzy/1+4F1a6pwPkmqbnq8JyGSxga+idRxGPn95wMH1lTbHATcGmkch2Zd3+f1/SzZXXF/jqK3S+Itc+uu/zGAsq0LOQlYu7wCbE36stuANND3tTXL9wRWBa6RtIakNUjdAi9iybOBp4DRtMavSdU7E6lfFbQuqXfOvp4lDRFa6+U+rxeS/qeWz69HkhLHoj6PL7Bkn/DnkZLkx/PF633yvIHoL6aGzUgjYhapS+WDSL317gPcJenrA4zBuoiTgLXL4oiYFRGzI+Kpflqx9HzRX06qHnkJmEf6Aj0g14tDGkt325wkBusiUpPUramfBOoNYfleUtVVM14kNW3dup9HTx/4RMTDpP08iJSggpSwShMRb+RrAI9FxIeAM4AT612YtmWHk4CVLreg2R34Jemiae3jW6RhOHuaJ54NvA38V51t7VG03Ij4M3Au8JOImFtntduA9SR9pKaMVXK8txQtK7sBeD8wLyfE2kffqqhzSS2W/iepiuzVJssasDqth+4AViKN5WHLsOFLX8Ws5fYhVVGcGhGzaxdI+m/gaNKZwsyIeFLSIcAFuQXNT0l11+uTWudsRxODz0fEV5ay/GpJtwG/kTSVdIbybdIZyilFy8l+CvwrqWXRKcAjpCqi7YAnIuK0mnUvJQ0q8mHefQG63WZIupg0+MoISTuTWjvdFhGvlRyLlcxnAtYJk4AH+iYAgIhYCFwC7Cdp+TzvYtIX52vAj0itiE4hXXeY0Ib49iJdn/ghqWnpYmDHiHikmY1ExN9IzS9vBP4dmJ63uRF9hjSMiDdJwxDOy+uX6ULSZ3Id6e98Celifr93cNuyxSOLmQ0BOeE9AZwREcd3MI6ZEbFjp8q38rk6yKyDJI0APgR8HlgdmNbZiKxqnATMOmtD0sXoZ4Gv9NxH0UE/63D5VjJXB5mZVZgvDJuZVZiTgJlZhTkJmJlVmJOAmVmFOQmYmVWYk4CZWYX9fwsmYVo0WIMHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['results__total_from_pacs'].hist(bins=17, grid=False, xlabelsize=10, ylabelsize=10)\n",
    "plt.xlabel(\"PAC Money in $\", fontsize=15)\n",
    "plt.ylabel(\"No. of Candidates\",fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's try that in `seaborn`. What's interesting here is Seaborn can automagically infer sizes and axes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd11b133ef0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df['results__total_from_pacs'], kde=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That did a pretty good job. But we should probably customize it a bit like we did in the first plot. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Frequency')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df['results__total_from_pacs'], kde=False)\n",
    "plt.title('PAC Money Across Candidates', fontsize=12)\n",
    "plt.xlabel('PAC Money in $', fontsize=16)\n",
    "plt.ylabel('Frequency', fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}