{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import csv \n",
    "from datetime import datetime\n",
    "from dateutil.relativedelta import relativedelta\n",
    "\n",
    "# Open the CSV file for a president\n",
    "with open('obama_commutations.csv') as csvfile:\n",
    "    reader = csv.DictReader(csvfile)\n",
    "    rows = [row for row in reader]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "rows\n",
    "\n",
    "# Figure out the indicies where each individual entry begins\n",
    "individualSplits = []\n",
    "\n",
    "for i, row in enumerate(rows):\n",
    "    # Names don't have a key column, and the next row always has key \"Offense:\"\n",
    "    try:\n",
    "        if rows[i]['key'] == '' and (i == 0 or rows[i+1]['key'] == 'Offense:'):\n",
    "            individualSplits.append(i)\n",
    "    except:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "individuals = []\n",
    "\n",
    "# Parse each individual into a dict with values representing the name and the offense\n",
    "for i, split in enumerate(individualSplits):\n",
    "    try:\n",
    "        nextSplit = individualSplits[i + 1]\n",
    "    except: \n",
    "        nextSplit = len(rows)\n",
    "    \n",
    "    individual = {\n",
    "        'name': '',\n",
    "        'offense': '',\n",
    "    }\n",
    "    \n",
    "    individual['name'] += rows[split]['info']\n",
    "    \n",
    "    for x in range(split + 1, nextSplit):\n",
    "        \n",
    "        if rows[x]['key'] == 'Offense:' or (rows[x]['key'] == '' and rows[x - 1]['key'] == 'Offense:'):\n",
    "            individual['offense'] += rows[x]['info']\n",
    "        \n",
    "    individuals.append(individual)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "drug_words = [\n",
    "    \"cocaine\",\n",
    "    \"marijuana\",\n",
    "    \"controlled substance\",\n",
    "    \"drug\",\n",
    "    \"distribute\",\n",
    "    \"distribution\",\n",
    "    \"heroin\",\n",
    "    \"LSD\",\n",
    "    \"manufacture\",\n",
    "]\n",
    "\n",
    "offenses = {\n",
    "    'drug': 0,\n",
    "    'conspiracy': 0\n",
    "}\n",
    "\n",
    "for person in individuals:\n",
    "    \n",
    "    crime = person['offense'].lower()\n",
    "    \n",
    "    if any(word in crime for word in drug_words):\n",
    "        offenses['drug'] += 1\n",
    "    \n",
    "    if \"conspiracy\" in crime:\n",
    "        offenses['conspiracy'] += 1\n",
    "\n",
    "offenses['drug'] = offenses['drug'] / len(individuals)\n",
    "offenses['conspiracy'] = offenses['conspiracy'] / len(individuals)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'conspiracy': 0.6227371469949312, 'drug': 0.9840695148443157}\n"
     ]
    }
   ],
   "source": [
    "print(offenses)"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}