combined_winner_loser_count.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests, re, nltk\n",
    "from bs4 import BeautifulSoup\n",
    "from nltk import clean_html\n",
    "from collections import Counter\n",
    "import operator\n",
    "\n",
    "#code modified from Dr. Mokus's Mini Project1 Writeup\n",
    "stop_words = nltk.corpus.stopwords.words('english') + [\n",
    " 'ut', '\\'re','.', ',', '--', '\\'s', '?', ')', ':', '(', '\\'',\n",
    " '\\\"', '-', '}', '{', '&', '|', u'\\u2014', '', '–', 'still', 'good', 'well',\n",
    "'said', 'â\\x80\\x9ci', 'thats','its','I' 'mr', 'project', 'one', 'uh', 'don’t',\n",
    " 'would', 'made', 'it’s','…','that’s']\n",
    "\n",
    "def cleanHtml (html):\n",
    "    from bs4 import BeautifulSoup\n",
    "    soup = BeautifulSoup(html, 'html.parser')\n",
    "    return soup .get_text()\n",
    "\n",
    "def cleanWord (w):\n",
    "    wn = re.sub('[,\"\\.\\'&\\|@>*;/=]', \"\", w)\n",
    "    return re.sub('^[0-9\\.]*$', \"\", wn)\n",
    "       \n",
    "def debate_word_dictionary_generator (URL, name1, name2, modList, name1Arr, name2Arr):\n",
    "    r = requests .get(URL)\n",
    "    t = cleanHtml (r .text) .lower()\n",
    "    wds = re .split('\\s+',t)\n",
    "\n",
    "    for i in range(len(wds)):\n",
    "        wds[i] = cleanWord (wds [i])\n",
    "        \n",
    "    #name1Arr = []\n",
    "    #name2Arr = []\n",
    "    switcher = 3\n",
    "            \n",
    "    for i in range(len(wds)):\n",
    "        if wds[i] == name1:\n",
    "            switcher = 1\n",
    "            \n",
    "        elif wds[i] == name2:\n",
    "            switcher = 2\n",
    "            \n",
    "        elif wds[i] in modList:\n",
    "            switcher = 3\n",
    "            \n",
    "        else:\n",
    "            if switcher == 1:\n",
    "                name1Arr.append(wds[i])\n",
    "                \n",
    "            elif switcher == 2:\n",
    "                name2Arr.append(wds[i])\n",
    "    wf1 = Counter (name1Arr)\n",
    "    wf2 = Counter (name2Arr)\n",
    "    \n",
    "\n",
    "    for k in stop_words:\n",
    "        wf1. pop(k, None)\n",
    "        wf2. pop(k, None)\n",
    "\n",
    "    tw1 = 0\n",
    "    for w in wf1:\n",
    "       tw1 += wf1[w]\n",
    "        \n",
    "    tw2 = 0\n",
    "    for w in wf2:\n",
    "       tw2 += wf2[w] \n",
    "    wfs1 = sorted (wf1 .items(), key = operator.itemgetter(1), reverse=True)\n",
    "    ml1 = min(len(wfs1),30)\n",
    "    \n",
    "    wfs2 = sorted (wf2 .items(), key = operator.itemgetter(1), reverse=True)\n",
    "    ml2 = min(len(wfs2),30)\n",
    "\n",
    "    return [(wfs1 [ 0:ml1 ] [::-1], tw1), (wfs2 [ 0:ml2 ] [::-1], tw2)]\n",
    "a = []\n",
    "a2 = []\n",
    "\n",
    "#1960\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/september-26-1960-debate-transcript/', \"kennedy:\", \"nixon:\", ['smith:', 'vanocur:', 'novins:', 'warren:', 'fleming:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-7-1960-debate-transcript/', \"kennedy:\", \"nixon:\", ['mcgee:', 'nivem:', 'morgan:', 'spivak:', 'levy:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-13-1960-debate-transcript/', \"kennedy:\", \"nixon:\", ['shadel:', 'mcgee:', 'fremd:', 'cater:', 'drummond:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-21-1960-debate-transcript/', \"kennedy:\", \"nixon:\", ['howe:', 'singiser:', 'cronkite:', 'chancellor:'],a,a2)\n",
    "\n",
    "#1976\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/september-23-1976-debate-transcript/', \"carter:\", \"ford:\", ['reynolds:', 'newman:', 'gannon:', 'drew:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-6-1976-debate-transcript/', \"carter:\", \"ford:\", ['valeriani:', 'frederick:', 'frankel:', 'trewhitt:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-22-1976-debate-transcript/', \"carter:\", \"ford:\", ['walters:', 'kraft:', 'maynard:', 'nelson:'],a,a2)\n",
    "#1980\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-28-1980-debate-transcript/', \"reagan:\", \"carter:\", ['hinerfeld:', 'stone:', 'smith:', 'ellis:', 'hilliard:', 'walters:'],a,a2)\n",
    "#1984\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-7-1984-debate-transcript/', \"president:\", \"mondale:\", ['wieghart:', 'walters:', 'sawyer:', 'barnes:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-21-1984-debate-transcript/', \"president:\", \"mondale:\", ['ridings:', 'newman:', 'geyer:', 'kalb:', 'kondracke:', 'audience member:', 'trewhitt:'],a,a2)\n",
    "#1988\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/september-25-1988-debate-transcript/', \"bush:\", \"dukakis:\", ['lehrer:', 'mashek:', 'groer:', 'jennings:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-13-1988-debate-transcript/', \"bush:\", \"dukakis:\", ['shaw:', 'compton:', 'warner:', 'mitchell:'],a,a2)\n",
    "#1992\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-11-1992-first-half-debate-transcript/',  \"clinton:\", \"bush:\", ['perot:', 'lehrer:', 'compton:', 'sander vanocur:', 'vanocur:', 'mashek:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-11-1992-second-half-debate-transcript/',  \"clinton:\", \"bush:\", ['perot:', 'lehrer:', 'compton:', 'sander vanocur:', 'vanocur:', 'mashek:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-15-1992-first-half-debate-transcript/',  \"clinton:\", \"bush:\", ['perot:', 'carole simpson:', 'audience question:', 'simpson:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-15-1992-second-half-debate-transcript/',  \"clinton:\", \"bush:\", ['perot:', 'carole simpson:', 'audience question:', 'simpson:'],a,a2)\n",
    "#1996\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-6-1996-debate-transcript/', 'clinton:', 'dole:', ['lehrer:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-6-1996-debate-transcript/', 'clinton:', 'dole:', ['lehrer:', 'ms. mcafee:', 'dr. berkley:', 'mr. milligan:', 'ms. kelly:', 'mr. delgado:', 'mr. fleck:', \n",
    "'ms. gonzalez:', 'ms. johnson:', 'ms. naudin:', 'ms. sanders:', 'mr. david:', 'mr. burns:', 'ms. giannotti:', 'mr. goldfarb:', 'ms. strategos:', 'MS. O’CONNOR:', 'MS. SIEFERT:', 'MR. SMITH:', 'MR. KITE:', 'ms. dube:'],a,a2)\n",
    "#2000\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-3-2000-transcript/', 'bush:', 'gore:', ['moderator:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-11-2000-debate-transcript/', 'bush:', 'gore:', ['moderator:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-17-2000-debate-transcript/', 'bush:', 'gore:', ['moderator:', 'member of audience:'],a,a2)\n",
    "#2004\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/september-30-2004-debate-transcript/', 'bush:', 'kerry:', ['lehrer:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-8-2004-debate-transcript/', 'bush:', 'kerry:', ['gibson:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-13-2004-debate-transcript/', 'bush:', 'kerry:', ['schieffer:'],a,a2)\n",
    "#2008\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/2008-debate-transcript/', 'obama:', 'mccain:', ['lehrer:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-7-2008-debate-transcrip/', 'obama:', 'mccain:', ['brokaw:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-15-2008-debate-transcript/', 'obama:', 'mccain:', ['schieffer:'],a,a2)\n",
    "#2012\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-3-2012-debate-transcript/', 'obama:', 'romney:', ['lehrer:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-16-2012-the-second-obama-romney-presidential-debate/', 'obama:', 'romney:', ['crowley:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-22-2012-the-third-obama-romney-presidential-debate/', 'obama:', 'romney:', ['schieffer:'],a,a2)\n",
    "#2016\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/september-26-2016-debate-transcript/', 'trump:', 'clinton:', ['holt:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-9-2016-debate-transcript/', 'trump:', 'clinton:', ['cooper:','raddatz:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://debates.org/voter-education/debate-transcripts/october-19-2016-debate-transcript/', 'trump:', 'clinton:', ['wallace:'],a,a2)\n",
    "#2020\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/september-29-2020-debate-transcript/', 'biden:', 'trump:', ['wallace:'],a,a2)\n",
    "debates = debate_word_dictionary_generator ('https://www.debates.org/voter-education/debate-transcripts/october-22-2020-debate-transcript/', 'biden:', 'trump:', ['welker:'],a,a2)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 792x576 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pylab\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline\n",
    "def plotTwoLists (wf_ee, wf_bu, title):\n",
    "    f = plt.figure (figsize=(11, 8))\n",
    "    f .suptitle (title, fontsize=20)\n",
    "    ax = f.add_subplot(111)\n",
    "    ax .spines ['top'] .set_color ('none')\n",
    "    ax .spines ['bottom'] .set_color ('none')\n",
    "    ax .spines ['left'] .set_color ('none')\n",
    "    ax .spines ['right'] .set_color ('none')\n",
    "    ax .tick_params (labelcolor='w', top='off', bottom='off', left='off', right='off', labelsize=20)\n",
    "\n",
    "\n",
    "    ax1 = f .add_subplot (121)\n",
    "    plt .subplots_adjust (wspace=.5)\n",
    "\n",
    "    pos = np .arange (len(wf_ee)) \n",
    "    ax1 .tick_params (axis='both', which='major', labelsize=14)\n",
    "    pylab .yticks (pos, [ x [0] for x in wf_ee ])\n",
    "    ax1 .barh (range(len(wf_ee)), [ x [1] for x in wf_ee ], align='center',color='g')\n",
    "    #added titles to subplots\n",
    "    ax1.title.set_text('Winning Candidates')\n",
    "\n",
    "    ax2 = f .add_subplot (122)\n",
    "    ax2 .tick_params (axis='both', which='major', labelsize=14)\n",
    "    pos = np .arange (len(wf_bu)) \n",
    "    pylab .yticks (pos, [ x [0] for x in wf_bu ])\n",
    "    ax2 .barh (range (len(wf_bu)), [ x [1] for x in wf_bu ], align='center',color = 'black')\n",
    "    ax2.title.set_text('Losing Candidates')\n",
    "\n",
    "plotTwoLists (debates[0][0], debates[1][0],'Winning vs. Losing Candidates - All Combined Debates (1960-2020)')"
   ]
  },
  {
   "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}