Chart3_HH.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Team Project MSIS 2629\n",
    "Hariz Hisham, Qing Zhang\n",
    "\n",
    "This notebook details the data collection, feature engineering, and visualization for Team Project: First Revision.\n",
    "\n",
    "Get the data [here](https://www.opensecrets.org/news/issues/guns).<br>\n",
    "Alternatively, use [this](https://docs.google.com/spreadsheets/d/1-7PdCI2NawSgP1QE-cGYVYedetYqepR-4jBweaJyqFo/edit#gid=1782600961) link.\n",
    "\n",
    "Dependencies:\n",
    "* None\n",
    "\n",
    "Downstream use:\n",
    "* Prepared charts to be integrated with other charts for submission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import pandas as pd\n",
    "import altair as alt\n",
    "import seaborn as sns\n",
    "#import re\n",
    "from IPython.display import Image\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chart 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read in the file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('congress_funding.csv', index_col = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a new column with state label for downstream purposes\n",
    "# We'll use this when exploring how much funding from lobbyists each state receives\n",
    "df['Stateid'] = df.Distid.str[:2]\n",
    "df = df.drop(columns = ['Unnamed: 10', 'Unnamed: 11'])  # Drop unwanted columns\n",
    "\n",
    "# Add total funding from gun control and gun rights to new col 'Total Funding' \n",
    "# to check how much funding each congressman receives from lobbyist \n",
    "df['Total Funding'] = df['Total from Gun Control'] + df['Total From Gun Rights']\n",
    "\n",
    "# Next, we label each congressman which 'stance' they are on based on which lobbyist pays them more.\n",
    "# If congressman receives more from gun control, label as 'Control'; similar for gun rights.\n",
    "# If they are not funded by gun control/rights lobbyist, or have equal funding, they are 'undecided'\n",
    "# This will be useful in categorization when visualizing funding purposes\n",
    "df['Stance'] = np.where(df['Total from Gun Control'] > df['Total From Gun Rights'],\n",
    "                        'Control', 'Rights')\n",
    "df['Stance'] = np.where(df['Total from Gun Control'] == df['Total From Gun Rights'],\n",
    "                        'Undecided', df['Stance'])\n",
    "\n",
    "# We log the funding to scale down large differences between categories\n",
    "df['log_grights'] = log(1 + df['Total From Gun Rights'])\n",
    "df['log_gcontrol'] = log(1 + df['Total from Gun Control'])\n",
    "df['log_totalfund'] = log(1 + df['Total Funding'])\n",
    "\n",
    "# Rename columns for Party and Office\n",
    "df.Party = df.Party.map({'R' : 'Republican', 'D' : 'Democrat',\n",
    "                        'I' : 'Independent'})\n",
    "df.Office = df.Office.map({'S' : 'Senate', 'H' : 'House'})\n",
    "\n",
    "df = df[df.Party != 'Independent']\n",
    "df = df[df.Stance != 'Undecided']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our goal was to create a single visualization delivering our core message:\n",
    "> There are higher rates of civilian firearm ownership in the United States because of relaxed laws across states as well as pro-firearm ownership lobbyists buying their way into Congress"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first chart below shows total funding received by Congressmen in both Houses, from both Political Parties (including Ind.). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 811.625x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = 'Office'\n",
    "y = 'Total Funding'\n",
    "\n",
    "first_graph = sns.catplot(X, y, col = 'Stance', hue = 'Party', data = df,\n",
    "                          kind = 'bar', palette = 'Set1', ci = None);\n",
    "first_graph = first_graph.set(xlabel = 'Office', ylabel = 'Total Funding (USD)')\n",
    "first_graph;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, we could divide the charts into Senate and House of Representatives, with the Congressman's stance on firearm control/rights identified by color."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x15dc46b1eb8>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792.125x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = 'Party'\n",
    "y = 'Total Funding'\n",
    "\n",
    "sns.catplot(X, y, col = 'Office', hue = 'Stance', data = df, kind = 'bar', palette = 'Set1', ci = None);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interesting findings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Republican senators are funded way more by firearm rights lobbyists than those in the House of Representatives. Since the Senate has less people, it's surprising that there is a __higher funding per congressman__ rate for Senators than for Reps. This is probably due to the fact that Senators can overturn a legislation passed by the House (they have more legislative power).\n",
    "\n",
    "* Some Democrat Senators and Reps are being funded by firearm rights lobbyists! This could mean that the issue with gun control is not necessarily a bilateral issue, but could be a __more deeply rooted issue in American society__.\n",
    "\n",
    "* Independents are joining in on the conversation. Yay!\n",
    "\n",
    "* Funding plays a key role in civilian firearm ownership rates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Future improvements "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Add chart title\n",
    "2. Remove Independents entirely from visualization\n",
    "3. Refine meaning of 'Undecided' category (i.e. what if they're funded `$`6500 from Rights and `$`5900 from Control?)\n",
    "4. Use full labels for categories (e.g. Republicans instead of 'R', Senate instead of 'S')\n",
    "5. Instead of 'Office = S' labels, use 'Senate'. Similar for House of Reps."
   ]
  },
  {
   "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
}