eda-topic-modeling-where-candidates-focus.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the data - it is encoded in cp1252."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>debate_name</th>\n",
       "      <th>debate_section</th>\n",
       "      <th>speaker</th>\n",
       "      <th>speech</th>\n",
       "      <th>speaking_time_seconds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
       "      <td>Part 1: South Carolina Democratic Debate Trans...</td>\n",
       "      <td>Norah O’Donnell</td>\n",
       "      <td>Good evening and welcome, the Democratic presi...</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
       "      <td>Part 1: South Carolina Democratic Debate Trans...</td>\n",
       "      <td>Gayle King</td>\n",
       "      <td>And Super Tuesday is just a week away and this...</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
       "      <td>Part 1: South Carolina Democratic Debate Trans...</td>\n",
       "      <td>Norah O’Donnell</td>\n",
       "      <td>And CBS News is proud to bring you this debate...</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
       "      <td>Part 1: South Carolina Democratic Debate Trans...</td>\n",
       "      <td>Gayle King</td>\n",
       "      <td>And we are partnering tonight also with Twitte...</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
       "      <td>Part 1: South Carolina Democratic Debate Trans...</td>\n",
       "      <td>Norah O’Donnell</td>\n",
       "      <td>Now, here are the rules for the next two hours...</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date                                        debate_name  \\\n",
       "0 2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "1 2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "2 2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "3 2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "4 2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "\n",
       "                                      debate_section          speaker  \\\n",
       "0  Part 1: South Carolina Democratic Debate Trans...  Norah O’Donnell   \n",
       "1  Part 1: South Carolina Democratic Debate Trans...       Gayle King   \n",
       "2  Part 1: South Carolina Democratic Debate Trans...  Norah O’Donnell   \n",
       "3  Part 1: South Carolina Democratic Debate Trans...       Gayle King   \n",
       "4  Part 1: South Carolina Democratic Debate Trans...  Norah O’Donnell   \n",
       "\n",
       "                                              speech  speaking_time_seconds  \n",
       "0  Good evening and welcome, the Democratic presi...                    8.0  \n",
       "1  And Super Tuesday is just a week away and this...                   22.0  \n",
       "2  And CBS News is proud to bring you this debate...                   14.0  \n",
       "3  And we are partnering tonight also with Twitte...                   10.0  \n",
       "4  Now, here are the rules for the next two hours...                   31.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('/kaggle/input/democratic-debate-transcripts-2020/debate_transcripts_v3_2020-02-26.csv', encoding='cp1252')\n",
    "df['date'] = pd.to_datetime(df.date)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Speakers who are candidates still in the race:\n",
    "- Joe Biden\n",
    "- Elizabeth Warren\n",
    "- Bernie Sanders\n",
    "- Pete Buttigieg\n",
    "- Amy Klobuchar\n",
    "- Michael Bloomberg\n",
    "- Tom Steyer\n",
    "- Tulsi Gabbard"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter to only the above mentioned candidates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Joe Biden            456\n",
       "Elizabeth Warren     440\n",
       "Bernie Sanders       430\n",
       "Pete Buttigieg       392\n",
       "Amy Klobuchar        353\n",
       "Tom Steyer           144\n",
       "Michael Bloomberg     97\n",
       "Tulsi Gabbard         77\n",
       "Name: speaker, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.loc[df.speaker.isin({'Joe Biden', 'Elizabeth Warren', 'Bernie Sanders', 'Pete Buttigieg', 'Amy Klobuchar', 'Michael Bloomberg', 'Tom Steyer', 'Tulsi Gabbard'})]\n",
    "df.speaker.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Speaking Time EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Candidate Speaking Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "df.groupby(by='speaker').speaking_time_seconds.sum().plot.bar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Candidate Speaking Time over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "speaker\n",
       "Amy Klobuchar        803.0\n",
       "Bernie Sanders       911.0\n",
       "Elizabeth Warren     768.0\n",
       "Joe Biden            765.0\n",
       "Michael Bloomberg    822.0\n",
       "Pete Buttigieg       774.0\n",
       "Tom Steyer           414.0\n",
       "Name: speaking_time_seconds, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Multi-Index on debate, candidate\n",
    "debate_candidate_time = df.groupby(by=['date', 'speaker']).speaking_time_seconds.sum()\n",
    "# Most recent debate\n",
    "debate_candidate_time['2020-02-25']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "speaker        date      \n",
       "Amy Klobuchar  2019-06-26      0.0\n",
       "               2019-07-30    635.0\n",
       "               2019-09-12    630.0\n",
       "               2019-10-15    804.0\n",
       "               2019-11-20    647.0\n",
       "                             ...  \n",
       "Tom Steyer     2020-02-25    414.0\n",
       "Tulsi Gabbard  2019-06-26      0.0\n",
       "               2019-07-31    634.0\n",
       "               2019-10-15    501.0\n",
       "               2019-11-20    555.0\n",
       "Name: speaking_time_seconds, Length: 62, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Multi-Index on candidate, debate\n",
    "candidate_debate_time = df.groupby(by=['speaker', 'date']).speaking_time_seconds.sum()\n",
    "candidate_debate_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Bernie Sanders: 15 minutes (median)\n",
      "Michael Bloomberg: 13 minutes (median)\n",
      "Pete Buttigieg: 13 minutes (median)\n",
      "Elizabeth Warren: 16 minutes (median)\n",
      "Tom Steyer: 10 minutes (median)\n",
      "Joe Biden: 15 minutes (median)\n",
      "Amy Klobuchar: 13 minutes (median)\n",
      "Tulsi Gabbard: 9 minutes (median)\n"
     ]
    }
   ],
   "source": [
    "# Print Median Speaking Times\n",
    "for candidate in df.speaker.unique():\n",
    "    med = round(candidate_debate_time[candidate].median()/60)\n",
    "    print(f'{candidate}: {med} minutes (median)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Speaking Times Line Graph\n",
    "plt.figure(figsize=(20,10))\n",
    "for candidate in df.speaker.unique():\n",
    "    candidate_debate_time[candidate].plot(label=candidate)\n",
    "plt.legend()\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('num seconds')\n",
    "plt.title('Candidate Speaking Time over time')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that Elizabeth Warren is given the most time to speak, followed by Bernie Sanders and Joe Biden, then Buttigieg, Klobuchar, and Bloomberg.\n",
    "\n",
    "We can see that Sanders has had the majority of speaking time recently, and despite his just recent entry into the race, Michael Bloomberg spoke for the second longest time in the recent debate.\n",
    "\n",
    "Surprisingly, Amy Klobuchar has quite a bit of speaking time despite her low performance in the polls."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define Methods for Parsing the texts\n",
    "- I will be using `spaCy` as I have found their parsing to be quick and accurate.\n",
    "\n",
    "Our goal will be to turn a document into a list of terms. I will not be using a DNN like *Bert*, and therefore will be doing a good deal of preprocessing, including stop word removal, lemmatization, and noun chunk/entity merging."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import spacy\n",
    "\n",
    "nlp = spacy.load('en_core_web_sm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# I add additional stops that lead to lower quality topics\n",
    "additional_stops = {'things', 'way', 'sure', 'thing', 'question', 'able', 'point', 'lot', 'time'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from spacy.util import filter_spans\n",
    "\n",
    "\n",
    "def _remove_stops(span):\n",
    "    while span and span[0].pos_ not in {'ADJ', 'NOUN', 'PROPN'}:\n",
    "        span = span.doc[span.start+1:span.end]\n",
    "    return span\n",
    "\n",
    "\n",
    "# Resource: \n",
    "# https://github.com/explosion/spacy/blob/master/examples/information_extraction/entity_relations.py\n",
    "def merge_ents_and_nc(doc):\n",
    "    spans = list(doc.ents) + list(doc.noun_chunks)\n",
    "    spans = list(map(_remove_stops, spans))\n",
    "    spans = filter_spans(spans)\n",
    "    with doc.retokenize() as retokenizer:\n",
    "        for span in spans:\n",
    "            if span:\n",
    "                # Added this in from the code - need to lemmatize better and keep ent types\n",
    "                root = span.root\n",
    "                attrs = {'LEMMA': span.text.lower(), 'POS': root.pos_, 'ENT_TYPE': root.ent_type_}\n",
    "                retokenizer.merge(span, attrs=attrs)\n",
    "\n",
    "\n",
    "def to_terms_list(doc):\n",
    "    merge_ents_and_nc(doc)\n",
    "    return [term.lemma_ for term in doc if len(term.lemma_) > 2 and\\\n",
    "             not term.is_stop and\\\n",
    "             term.pos_ in {'NOUN', 'PROPN', 'ADJ'} and\\\n",
    "             term.lemma_ not in additional_stops and\\\n",
    "             \"crosstalk\" not in term.lower_]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple is Better than Complex. My Simple Idea with Topic Modeling\n",
    "1. Create a Corpus of Documents from `df.speech.values`\n",
    "2. Most Frequent Terms by Speaker\n",
    "3. Vectorize using `sklearn.feature_extraction.text.TfidfVectorizer`, using parsed documents as output from `to_terms_list` as input\n",
    "4. Use NMF Topic Model, `sklearn.decomposition.NMF`, to break our corpus into `N` topics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from spacy.tokens.doc import Doc\n",
    "\n",
    "corpus = list(nlp.pipe(df.speech.values, n_threads=4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "terms = [to_terms_list(doc) for doc in corpus]\n",
    "df['terms'] = terms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import itertools\n",
    "from collections import Counter\n",
    "\n",
    "def most_frequent(terms, k):\n",
    "    flat_terms = list(itertools.chain(*terms))\n",
    "    return Counter(flat_terms).most_common(k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Amy Klobuchar: [('people', 133), ('president', 102), ('country', 56), ('donald trump', 47), ('bill', 39), ('america', 37), ('state', 27), ('money', 25), ('work', 20), ('stage', 20)]\n",
      "\n",
      "Bernie Sanders: [('people', 179), ('country', 105), ('healthcare', 63), ('america', 52), ('medicare', 48), ('american people', 42), ('world', 42), ('trump', 42), ('president', 40), ('joe', 39)]\n",
      "\n",
      "Elizabeth Warren: [('people', 195), ('country', 82), ('america', 80), ('president', 42), ('money', 42), ('donald trump', 35), ('healthcare', 35), ('democrats', 35), ('families', 35), ('stage', 29)]\n",
      "\n",
      "Joe Biden: [('fact', 186), ('people', 109), ('president', 81), ('number', 66), ('country', 40), ('world', 40), ('deal', 32), ('plan', 32), ('years', 28), ('position', 26)]\n",
      "\n",
      "Michael Bloomberg: [('people', 24), ('new york city', 16), ('senator', 11), ('donald trump', 10), ('country', 10), ('money', 10), ('years', 8), ('president', 7), ('job', 7), ('right', 7)]\n",
      "\n",
      "Pete Buttigieg: [('president', 110), ('country', 75), ('people', 63), ('washington', 35), ('american people', 31), ('donald trump', 27), ('plan', 26), ('fact', 25), ('world', 24), ('politics', 24)]\n",
      "\n",
      "Tom Steyer: [('people', 43), ('stage', 30), ('american people', 28), ('economy', 27), ('government', 27), ('fact', 27), ('america', 26), ('corporations', 25), ('mr. trump', 24), ('country', 24)]\n",
      "\n",
      "Tulsi Gabbard: [('country', 36), ('people', 33), ('president', 25), ('war', 22), ('american people', 11), ('commander', 11), ('chief', 11), ('donald trump', 10), ('national security', 9), ('years', 9)]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "mf = df.groupby(by='speaker').terms.apply(lambda terms: most_frequent(terms, 10))\n",
    "speakers = mf.index\n",
    "top_terms = mf.values\n",
    "for s, tt in zip(speakers, top_terms):\n",
    "    print(f\"{s}: {tt}\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how the most successful candidate, Bernie Sanders, speaks less about Donald Trump and focuses much more on healthcare, medicare, and the american people.\n",
    "\n",
    "Compare this to second tier candidates like Buttigieg and Klobuchar who have \"president\" or \"donald trump\" surface higher in their most frequent terms."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Topic Modeling\n",
    "I take a heuristic approach to topic modeling, and have executed the below cells a few times to find a suitable value for `N`. I look for a mix of granularity and qualitative meaning.\n",
    "\n",
    "After iterative attempts, I chose **8** topics, and I do a human pass through to summarize them. One particularly great approach for helping decide the number of topics is *Stability*, as seen in the paper: *[How Many Topics? Stability Analysis for Topic Models*](https://arxiv.org/pdf/1404.4606.pdf). I need to clean up my code for that, and will implement it here in the coming days, stay tuned..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.decomposition import NMF\n",
    "\n",
    "# Useful hack: this dummy allows us to use our extracted terms from the methods above, overriding sklearn's tokenizer.\n",
    "dummy = lambda x: x\n",
    "\n",
    "vectorizer = TfidfVectorizer(max_df=0.5, min_df=10, preprocessor=dummy, tokenizer=dummy, ngram_range=(1,2))\n",
    "features = vectorizer.fit_transform(terms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## About NMF:\n",
    "**NMF** stands for **Non-negative Matrix Factorization** and it is a form of dimensionality reduction. \n",
    "\n",
    "The idea is:\n",
    "\n",
    "Given some non-negative matrix $X$, find two matrices, $W$ and $H$, such that $W\\cdot H \\approx X$   \n",
    "\n",
    "Without getting too deep into the math, here is a high level leyman's overview of what happens:\n",
    "\n",
    "1. Initialize matrices $W$ and $H$ with random values.\n",
    "2. Perform $W \\cdot H$ and compare the values to the original matrix X\n",
    "3. Now, adjust these values incrementally through a number of iterations to optimize.\n",
    "\n",
    "\n",
    "The output of this is the matrices $W$ and $H$. In the case of text processing where $X$ is some matrix containing text feature weights, these represent the 'document-topic matrix' and 'topic-term matrix' respectively.\n",
    "\n",
    "The 'document-topic matrix', or `doc_topic_matrix` in our code, has the shape `len(corpus), n_topics` and represents the topic distribution for each document.\n",
    "\n",
    "The 'topic-term matrix', `topic_term_matrix` in our code, has the shape `n_topics, len(terms)`, and represents the term distribtuion for each topic, i.e. topic 0 consists dominantly of terms A, B, C, ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2389, 8)\n"
     ]
    }
   ],
   "source": [
    "N=8\n",
    "tm = NMF(n_components=N)\n",
    "doc_topic_matrix = tm.fit_transform(features)\n",
    "topic_term_matrix = tm.components_\n",
    "terms = vectorizer.get_feature_names()\n",
    "\n",
    "# Array where rows are docs, columns are topics\n",
    "print(doc_topic_matrix.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def top_topic_terms(topic_term_matrix, i, n_terms=10):\n",
    "    topic = topic_term_matrix[i]\n",
    "    return [(terms[idx], topic[idx]) for idx in np.argsort(topic)[::-1][:n_terms]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "[('people', 3.3077405613713307), ('america', 0.27338801688902203), ('government', 0.1908463385344917), ('people people', 0.1828897380127292), ('people country', 0.13978498724519678), ('lives', 0.13692669101644975), ('place', 0.12576790167660806), ('healthcare', 0.11257941628564895), ('democrats', 0.1060778361419162), ('americans', 0.10018962290351986)]\n",
      "1\n",
      "[('president', 2.049013660571809), ('united states', 0.3464436274091054), ('president united states', 0.30183062325959786), ('stage', 0.15264808400385746), ('case', 0.12867358491484127), ('law', 0.12096794517521464), ('congress', 0.11987000821032207), ('washington', 0.10076974151180756), ('russia', 0.09613347351782972), ('allies', 0.09518776619133053)]\n",
      "2\n",
      "[('fact', 2.34102310645208), ('matter', 0.40533250792370107), ('number', 0.3146705455063268), ('fact matter', 0.31216302095017195), ('clear', 0.29217414664102237), ('man', 0.22772056694921872), ('price', 0.16225775475527887), ('matter fact', 0.15525847881828467), ('deal', 0.15467450845576738), ('senator', 0.14055315376380098)]\n",
      "3\n",
      "[('country', 1.726579779439166), ('american people', 0.28810382121998174), ('america', 0.18951593226385144), ('healthcare', 0.16571196598392327), ('people country', 0.15660669728502113), ('economy', 0.14095672228374323), ('future', 0.14091142235878756), ('state', 0.12695869806704552), ('today', 0.12677271903733114), ('government', 0.12194312012402055)]\n",
      "4\n",
      "[('world', 1.8077599908513229), ('america', 0.5953351636591905), ('allies', 0.27011717965992044), ('china', 0.2495178159965135), ('iran', 0.2207862755780774), ('climate change', 0.20386247858815357), ('rest', 0.1780277018224873), ('united states', 0.17758402555003183), ('rest world', 0.16310628178541364), ('problem', 0.14887410167558893)]\n",
      "5\n",
      "[('right', 2.1426871817664788), ('woman', 0.2602617832922118), ('american people', 0.1630251641970376), ('wrong', 0.10541767890329043), ('court', 0.10209149343010693), ('politicians', 0.08542102849698043), ('government', 0.08321201695251082), ('family', 0.07149386874815822), ('constitution', 0.06659920840503461), ('democracy', 0.05678401487361697)]\n",
      "6\n",
      "[('money', 1.241883248993707), ('plan', 1.0352384721021335), ('medicare', 0.9667648749614717), ('healthcare', 0.4383695701548618), ('year', 0.33750652972566875), ('years', 0.2741182250873605), ('family', 0.18996063930744214), ('bill', 0.1553234129085405), ('premiums', 0.15530755463533863), ('public option', 0.1392125091226166)]\n",
      "7\n",
      "[('donald trump', 1.7668826105811983), ('democrats', 0.2546435137991473), ('families', 0.18828516597487654), ('trump', 0.1780661872458887), ('stage', 0.1729718247433729), ('house', 0.1460575655144622), ('candidate', 0.12705881707129082), ('wealthy', 0.12649439921391883), ('donald trump donald trump', 0.12555720378465127), ('mayor bloomberg', 0.11879414069318961)]\n"
     ]
    }
   ],
   "source": [
    "for i in range(N):\n",
    "    print(i)\n",
    "    print(top_topic_terms(topic_term_matrix, i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = {0: 'The American People',\n",
    "         1: 'The President of the United States',\n",
    "         2: 'Biden Telling us what he is saying is a matter of fact',\n",
    "         3: 'The American Country',\n",
    "         4: 'Global Diplomatic Issues',\n",
    "         5: 'Social/Constitutional Rights',\n",
    "         6: 'Healthcare and Medicare',\n",
    "         7: 'Donald Trump'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
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       "      <th>5</th>\n",
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       "      <th>6</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
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       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
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       "      <td>2020-02-25</td>\n",
       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
       "      <td>Part 1: South Carolina Democratic Debate Trans...</td>\n",
       "      <td>Bernie Sanders</td>\n",
       "      <td>Oh, Mr. Bloomberg. Let me tell Mr. Putin. Okay...</td>\n",
       "      <td>27.0</td>\n",
       "      <td>[mr. bloomberg, mr. putin, good friend, presid...</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>South Carolina Democratic Debate Transcript: F...</td>\n",
       "      <td>Part 1: South Carolina Democratic Debate Trans...</td>\n",
       "      <td>Pete Buttigieg</td>\n",
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       "         date                                        debate_name  \\\n",
       "5  2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "6  2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "8  2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "9  2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "11 2020-02-25  South Carolina Democratic Debate Transcript: F...   \n",
       "\n",
       "                                       debate_section            speaker  \\\n",
       "5   Part 1: South Carolina Democratic Debate Trans...     Bernie Sanders   \n",
       "6   Part 1: South Carolina Democratic Debate Trans...  Michael Bloomberg   \n",
       "8   Part 1: South Carolina Democratic Debate Trans...  Michael Bloomberg   \n",
       "9   Part 1: South Carolina Democratic Debate Trans...     Bernie Sanders   \n",
       "11  Part 1: South Carolina Democratic Debate Trans...     Pete Buttigieg   \n",
       "\n",
       "                                               speech  speaking_time_seconds  \\\n",
       "5   Well, you’re right, the economy is doing reall...                   59.0   \n",
       "6                                            Senator-                    5.0   \n",
       "8   I think that Donald Trump thinks it would be b...                   19.0   \n",
       "9   Oh, Mr. Bloomberg. Let me tell Mr. Putin. Okay...                   27.0   \n",
       "11  We know what the President … what Russia wants...                    3.0   \n",
       "\n",
       "                                                terms   topic_0   topic_1  \\\n",
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       "6                                          [senator-]  0.000000  0.000000   \n",
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       "11                         [president, russia, chaos]  0.000000  0.221029   \n",
       "\n",
       "     topic_2   topic_3   topic_4   topic_5   topic_6   topic_7  \n",
       "5   0.001837  0.095823  0.000000  0.066448  0.002088  0.002068  \n",
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      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in range(N):\n",
    "    col = f\"topic_{i}\"\n",
    "    df[col] = doc_topic_matrix[:,i]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def percent_comp(x):\n",
    "    return x/x.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Speaker-Topic DataFrame\n",
    "I create a `pandas.DataFrame` to display: for each speaker, their total weight in each topic.\n",
    "This can help answer two things:\n",
    "1. If we apply `percent_comp`, the percent composition on each row, we get the percentage each candidate talks about each topic - which topics they focus on.\n",
    "2. If we apply `percent_comp` on each column, we'll see who dominates a topic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>speaker</th>\n",
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       "      <th>Amy Klobuchar</th>\n",
       "      <td>7.650797</td>\n",
       "      <td>11.547626</td>\n",
       "      <td>1.811222</td>\n",
       "      <td>7.795020</td>\n",
       "      <td>4.426998</td>\n",
       "      <td>2.367170</td>\n",
       "      <td>5.892472</td>\n",
       "      <td>7.588296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bernie Sanders</th>\n",
       "      <td>8.674468</td>\n",
       "      <td>4.092695</td>\n",
       "      <td>3.286723</td>\n",
       "      <td>14.275556</td>\n",
       "      <td>8.299994</td>\n",
       "      <td>4.739910</td>\n",
       "      <td>10.433126</td>\n",
       "      <td>4.129244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elizabeth Warren</th>\n",
       "      <td>10.385560</td>\n",
       "      <td>4.669186</td>\n",
       "      <td>2.005828</td>\n",
       "      <td>10.736469</td>\n",
       "      <td>6.938798</td>\n",
       "      <td>2.387871</td>\n",
       "      <td>8.379050</td>\n",
       "      <td>8.397786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Joe Biden</th>\n",
       "      <td>5.518507</td>\n",
       "      <td>9.306664</td>\n",
       "      <td>18.447532</td>\n",
       "      <td>5.191198</td>\n",
       "      <td>6.834613</td>\n",
       "      <td>3.591125</td>\n",
       "      <td>7.502055</td>\n",
       "      <td>4.836129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michael Bloomberg</th>\n",
       "      <td>1.076053</td>\n",
       "      <td>0.954638</td>\n",
       "      <td>0.676380</td>\n",
       "      <td>1.620823</td>\n",
       "      <td>1.002424</td>\n",
       "      <td>1.251455</td>\n",
       "      <td>1.634326</td>\n",
       "      <td>1.517536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pete Buttigieg</th>\n",
       "      <td>3.442054</td>\n",
       "      <td>12.040171</td>\n",
       "      <td>3.308789</td>\n",
       "      <td>11.444541</td>\n",
       "      <td>5.451900</td>\n",
       "      <td>3.838414</td>\n",
       "      <td>5.914650</td>\n",
       "      <td>5.476982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tom Steyer</th>\n",
       "      <td>2.047134</td>\n",
       "      <td>1.923601</td>\n",
       "      <td>2.785090</td>\n",
       "      <td>3.953023</td>\n",
       "      <td>3.349870</td>\n",
       "      <td>3.131720</td>\n",
       "      <td>1.973765</td>\n",
       "      <td>2.174290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tulsi Gabbard</th>\n",
       "      <td>1.325632</td>\n",
       "      <td>2.304739</td>\n",
       "      <td>0.774535</td>\n",
       "      <td>3.726768</td>\n",
       "      <td>1.153659</td>\n",
       "      <td>0.255148</td>\n",
       "      <td>0.803951</td>\n",
       "      <td>1.206597</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     topic_0    topic_1    topic_2    topic_3   topic_4  \\\n",
       "speaker                                                                   \n",
       "Amy Klobuchar       7.650797  11.547626   1.811222   7.795020  4.426998   \n",
       "Bernie Sanders      8.674468   4.092695   3.286723  14.275556  8.299994   \n",
       "Elizabeth Warren   10.385560   4.669186   2.005828  10.736469  6.938798   \n",
       "Joe Biden           5.518507   9.306664  18.447532   5.191198  6.834613   \n",
       "Michael Bloomberg   1.076053   0.954638   0.676380   1.620823  1.002424   \n",
       "Pete Buttigieg      3.442054  12.040171   3.308789  11.444541  5.451900   \n",
       "Tom Steyer          2.047134   1.923601   2.785090   3.953023  3.349870   \n",
       "Tulsi Gabbard       1.325632   2.304739   0.774535   3.726768  1.153659   \n",
       "\n",
       "                    topic_5    topic_6   topic_7  \n",
       "speaker                                           \n",
       "Amy Klobuchar      2.367170   5.892472  7.588296  \n",
       "Bernie Sanders     4.739910  10.433126  4.129244  \n",
       "Elizabeth Warren   2.387871   8.379050  8.397786  \n",
       "Joe Biden          3.591125   7.502055  4.836129  \n",
       "Michael Bloomberg  1.251455   1.634326  1.517536  \n",
       "Pete Buttigieg     3.838414   5.914650  5.476982  \n",
       "Tom Steyer         3.131720   1.973765  2.174290  \n",
       "Tulsi Gabbard      0.255148   0.803951  1.206597  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_speaker_topics = df.groupby(by=['speaker'])[df.columns[-N:]].sum()\n",
    "df_speaker_topics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Percent of Topic, by Candidate\n",
    "Show, for each topic, which candidates talk about it the most, by the above `df_speaker_topics`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The American People\n",
      "people | america | government | people people | people country | lives | place | healthcare | democrats | americans\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The President of the United States\n",
      "president | united states | president united states | stage | case | law | congress | washington | russia | allies\n"
     ]
    },
    {
     "data": {
      "image/png": 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Q2GrAc462vY3tbebMmTPqoSMiYimNcmfxJeBcSV+tlvekdMprcgGwiaSNgRsonfj+bpSgJK0F3GH7bklrAzsCR4yyb0RELHvDRp2dDWD7CEpRzx3AncABtj/UdGDbC4E3At8Hfg6cZHu+pEMlvbh6jWdIuh54GfBpSb2K8ycB86rOf2cBh/e1ooqIiBk07M7ifEofC2xfQLlTWCq2TwVO7Vt3cO3xBZTiqf79fgo8ZWlfLyIixmNYncUo9RIREbEcGHZnMUfSgdNttP1fY4gnIiI6aFiymAWsRu4wIiKWe8OSxW9sHzpjkURERGelziIiIhoNSxbPnbEoIiKi06ZNFrZvmclAIiKiu4Z1ylt5JgOJiIjuGlYMdQ6ApC/NUCwREdFRw1pDrSRpX8qseH/bv9H218YXVkREdMmwZHEAsA+wJvCivm0GkiwiIpYT0yYL2z8Gfixpnu3PzWBMERHRMSMNUS7pzcDO1fLZwFG27x2yT0REPISMkiw+CazI4pnx/h74FPBP4woqIiK6ZZRk8QzbT60tn1nNMxEREcuJUaZVvU/S43sL1ZzY940vpIiI6JpR7izeCpwl6WrKeFEbAfuNNaqIiOiUxmRh+wxJmwBPpCSLX9i+e+yRRUREZ4xyZ0GVHC4dcywREdFRo9RZRETEci7JIiIiGjUmC0lnjLIuIiIeuqats5C0CvAwYG1Ja7F45rzVgcfOQGwREdERwyq4Xwe8hZIYLmRxsrgdOHLMcUVERIcMG0jwo8BHJb3J9sdnMKaIiOiYUfpZfFzSDsDc+vNtf3GMcUVERIc0JotqprzHAz9j8TAfBpIsIiKWE6N0ytsG2Ny2xx1MRER00yj9LC4H1hl3IBER0V2j3FmsDVwh6Xxg0ZhQtl88tqgiIqJTRkkW/zHuICIiottGaQ11tqSNgE1sny7pYcCs8YcWERFdMcpwH68FTgY+Xa1aD/jGOIOKiIhuGaWC+w3AjpSe29j+JfDocQYVERHdMkqyuNv2Pb0FSbMp/SwiImI5MUqyOFvSO4BVJe0KfAX41igHl7SbpCslLZB00IDtO0u6SNJCSXv1bdtX0i+rn31Heb2IiBiPUZLFQcBNwGWUwQVPBd7VtJOkWZQBB3cHNgdeKWnzvqf9Gng1cHzfvo8EDgGeCWwLHFKNfBsRES0YpensqsAxtj8Di5LAqsAdDfttCyywfXW134nAHsAVvSfYvrbadn/fvi8AfmD7lmr7D4DdgBNGiDciIpaxUe4szqAkh55VgdNH2G894Lra8vXVulGMtK+k/SXNkzTvpptuGvHQERGxtEZJFqvY/nNvoXr8sBH204B1o1aMj7Sv7aNtb2N7mzlz5ox46IiIWFqjFEP9RdLWti8CkPR04M4R9rse2KC2vD5w44hxXQ/s0rfvD0fcN2JizT3oO8v8mNce/sJlfsxY/oySLP4F+Iqk3ol+XeAVI+x3AbCJpI2BG4C9gb8bMa7vA4fVKrWfD7x9xH0jImIZG5osJK0ArARsBjyRUjz0C9v3Nh3Y9kJJb6Sc+GdRKsnnSzoUmGf7FEnPAL4OrAW8SNJ7bD/Z9i2S3ktJOACH9iq7IyJi5g1NFrbvl/Rh29tThipfKrZPpTS1ra87uPb4AkoR06B9jwGOWdrXjIiIZW+UCu7TJL1U0qBK54iIWA6MUmdxIPBw4D5Jd1KKomx79bFGFhERnTHKEOWPmIlAIiKiuxqTRVX8tA+wse33StoAWNf2+WOPLiLiQUhT5GVnlDqLTwLbs7jZ658pYz5FRMRyYpQ6i2fa3lrSxQC2b5W00pjjioiIDhklWdxbDR5oAElzgP6B/2I5llv9iIe+UYqhPkbpOPdoSe8DfgwcNtaoIiKiU0ZpDXWcpAuB51Kazb7E9s/HHllERHTGtMlC0irAAcATKBMffdr2wpkKLCIiumNYMdSxwDaURLE78KEZiSgiIjpnWDHU5rafAiDpc0D6VURELKeG3VksGlk2xU8REcu3YXcWT5V0e/VYwKrVcsaGiohYzkybLGzPmslAIiKiu0bpZxEREcu5JIuIiGiUZBEREY2SLCIiolGSRURENBpl1NloSUZzjYiuyJ1FREQ0SrKIiIhGSRYREdEoySIiIholWURERKMki4iIaJRkERERjZIsIiKiUZJFREQ0SrKIiIhGSRYREdEoySIiIholWURERKMki4iIaDTWZCFpN0lXSlog6aAB21eW9OVq+3mS5lbr50q6U9LPqp+jxhlnREQMN7b5LCTNAo4EdgWuBy6QdIrtK2pPew1wq+0nSNob+ADwimrbVbafNq74IiJidOO8s9gWWGD7atv3ACcCe/Q9Zw/g2OrxycBzJWmMMUVExAMwzmSxHnBdbfn6at3A59heCPwReFS1bWNJF0s6W9JfDXoBSftLmidp3k033bRso4+IiEXGmSwG3SF4xOf8BtjQ9lbAgcDxklZf4on20ba3sb3NnDlzHnTAEREx2DiTxfXABrXl9YEbp3uOpNnAGsAttu+2fTOA7QuBq4BNxxhrREQMMc5kcQGwiaSNJa0E7A2c0vecU4B9q8d7AWfatqQ5VQU5kh4HbAJcPcZYIyJiiLG1hrK9UNIbge8Ds4BjbM+XdCgwz/YpwOeAL0laANxCSSgAOwOHSloI3AccYPuWccUaERHDjS1ZANg+FTi1b93Btcd3AS8bsN9Xga+OM7aIiBhdenBHRESjJIuIiGiUZBEREY2SLCIiolGSRURENEqyiIiIRkkWERHRKMkiIiIaJVlERESjJIuIiGiUZBEREY2SLCIiolGSRURENEqyiIiIRkkWERHRKMkiIiIaJVlERESjJIuIiGiUZBEREY2SLCIiolGSRURENEqyiIiIRkkWERHRKMkiIiIaJVlERESjJIuIiGiUZBEREY2SLCIiolGSRURENEqyiIiIRkkWERHRKMkiIiIaJVlERESjJIuIiGiUZBEREY3Gmiwk7SbpSkkLJB00YPvKkr5cbT9P0tzatrdX66+U9IJxxhkREcONLVlImgUcCewObA68UtLmfU97DXCr7ScAHwE+UO27ObA38GRgN+CT1fEiIqIF47yz2BZYYPtq2/cAJwJ79D1nD+DY6vHJwHMlqVp/ou27bV8DLKiOFxERLZg9xmOvB1xXW74eeOZ0z7G9UNIfgUdV68/t23e9/heQtD+wf7X4Z0lXLpvQF1kb+MMoT9QHlvErL53EuWyNFGfLMULiXJYeUt9NWKo4NxrlSeNMFhqwziM+Z5R9sX00cPTShzYaSfNsbzOu4y8riXPZSpzL1iTEOQkxQrtxjrMY6npgg9ry+sCN0z1H0mxgDeCWEfeNiIgZMs5kcQGwiaSNJa1EqbA+pe85pwD7Vo/3As607Wr93lVrqY2BTYDzxxhrREQMMbZiqKoO4o3A94FZwDG250s6FJhn+xTgc8CXJC2g3FHsXe07X9JJwBXAQuANtu8bV6xDjK2IaxlLnMtW4ly2JiHOSYgRWoxT5UI+IiJieunBHRERjZIsIiKiUZJFRdIsSR9sO46IGC8V67Ydx6QZZz+LiWL7PklPlyR3vCJH0suA79n+k6R3AVsD/2n7opZDm0LSjsB/UDr9zKb0n7Htx7UZV90kxBjLlm1L+jbw9LZjmY6kjzCgb1mP7QNnMBwgyaLfxcA3JX0F+Etvpe2vtRfSQO+2/RVJOwEvAD4EfIole8i37XPAvwIXAm20ZhvFJMQIgKQ/seQJ5I/APOD/2b565qNa0oTEeb6krbt2gVVzefV7O2AL4KRqeS9Kt4QZl9ZQNZI+P2C1bf/jjAczhKSLbW8l6f3AZbaP761rO7Y6SefZ7loCm2ISYuyR9B5K59TjKXdAewPrAFcC/2x7l/aiW2wS4pR0GfAk4CrKhWHvjnLrVgPrI+lM4AW2762WV6KUKjxnxmNJspg81S30DcDzKLfSdwLn235qq4H1kXQ4pY/N14C7e+u7dDU3CTH2DEpsks61vZ2kS7ry+U9CnJIeP2i97atmOpZhqvHunmn7tmp5TeA820+c6VhSDFUjaRXKsOlPBlbpre/anQXwcsrQ7R+yfVtVWffWlmMapHfCqI9lY2DGr4qGmIQYe+6X9HLKCM1QiiR6unTV1/k4bV8laTtgU9tflPQo4OFtxzXAB4GfSTq9Wn4O8J9tBJI7i5qqruIXwN8BhwL7AD+3/S+tBlYjaQXgUttbtB1LzCxJjwM+CmxPOemeS6lvuQF4uu0ftxjeIpMQZ9UwZEfg8bY3lbQe8GXbO7Uc2iLVdA3rUFqtbletPtf2Da3Ek2SxWK0u4FLbW0paEfh+G+WDw0g6Dni77V+3Hcswkh4DHAY81vbu1aRW29v+XMuhLTIJMcKiycTebPsjbcfyUCDpZ8BWwEW9ur7e/327kU0l6ULbnWi1lX4WU91b/b5N0haUUXDnthfOtNYF5ks6Q9IpvZ+2gxrgC5SxwR5bLf8f8JbWohnsC3Q/Rqqx0fonD+skSZtW383Lq+Utqyv5Lrm7aiJvAEkPazme6ZwvqROV7qmzmOpoSWsB76aMfLsacHC7IQ30nrYDGNHatk+S9HZYNLhk15qnTkKMPT+R9Angy0xt2t21yvjPUOrQPg1g+1JJx9NSWfs0vibpSGANSftR6iqPaTmmQXYCXiup9VZbSRY1tj9bPTwb6GynLNtnS9oI2MT26dVVURfnKP9LVXHYu3rbjtLevksmIcaeHarfh9bWdbEy/mG2zy9F7ossbCuYQWx/QNLuwD3AU4H32f5uy2EN8pK2A+hJsqiRtDLwUkrR06L3xvah0+3TBkmvpUwn+0jg8ZQpZ48CnttmXAMcSLlDe7yknwBzmNoypgsmIUYAbD+77RhG9IeqaWovAe8F/KbdkKaSdABwQkcTxCK9prySHkmthWYbkiym+iblqvJCam3uO+gNwLbAeQC2fynp0e2GNFXVamsV4FnAEym3z1f2Ohd1he2LJHU6xp5JqYynfD+PBjaTdANwDfCqdkNawlzgIknnUebaOb3h+a2Q9ELgI5TZQm+m1K39EthsxmNJa6jFJF0+CU1Se52eaq23ZlNadXStJcc5trdvO45BJP3tsO0dHOIFSd8FPg+80/ZTq8/9YttPaTm0gSQ9HFjB9p/ajmWQ6oJmd2A/SlHUCZTEcW2bcdVVrbZ2BU6r/td3BV5q+4CZjiV3FlP9VNJTbF/WdiANzpb0DmDV6svzeuBbLcc0yGmSXgp8rYODM76o+v1oSl3AmdXys4EfUnp0d02nK+Mlvcr2/0g6sG89ALb/q5XApmH7fknXAtcCT6G0MvympFNtv73N2GoW2r5J0gqSZPsHkt7XRiBJFiwaJ8aU92M/SVdTiqF6LQ86dcUOHERpvXEZ8DrgVOCzQ/dox4GUXrELJd3F4vdz9XbDAtv7waKhUza3/ZtqeV3gyDZjG6LrlfG9HtCPaDWKEUh6PfBq4HbKYJLvtH13dbexAOhKsvhjdYf2E+CLkn4P3N9GICmGAqqWRdOy/auZiuWhoup9usEEdBycUvTY5R7yVXv7j1NGIb2cqjLe9qWtBjaBJB0GfHbQCLiStrB9+YDdZpykR1DGfhPwD5S+X1+yfdOMx5JksVh1pTa/V8ZafVCb2z6v3ciK2h3QQF27A+pS79PpVP0WNqGUV5syQuoC229qNbBpVPUUna6Ml/SxAav/CMyz/c2Zjmc6g8aG6uLFjaQ5wDMo3895bSQKSLKYQtLFwNa98vXqKnNeV4Ytrt0BvaH6/aXq9z7AHR1s4nsk8AXbrYy/P6qqsvuvqsX/tf31NuOZjspAl6+ndNQy8CPgKNt3tRpYH0lHU1rrfKVa9VJgPrABcLXt1nvIawLGhgKoOgweSun7Jcpnf7DtY2c8liSLxST9zPbT+tZ1cbyYn9jesWld2yRdAWwK/IqpvU879X5OCkknAX8C/qda9UpgLdsvay+qJanMwfB82wur5dnAaZRWPZfZ3rzN+GCixoa6EtipdzchaW3gJ84Q5a27WtKbKbPOQbmK68KsXv0eLmmn3uidknagm8Mr7952ANOR9GPbO2nJWd06Uwk/wBM9dS6IsyRd0lo001uP8n3sVb4/nNI35D5JXem/dLdtS+r62FA3ALdj8WEfAAAWrUlEQVTVlv8IXN9GIEkWUx0AfAx4F+UEcgalp3TXvAY4RtIa1fJtQNfm3FjUMKDqMNhq79N+veIG251vuVNzsaTtbJ8LIOmZlFYyXXMEZQ6GH1KS787AYVWrnq50fhs0NtSgmTJbUV20AvwaOEfSNyjnpJeQaVVjaUlanfIZdqn55CKSXgx8mNLr9PfARpT5QZ7camADVFeWmwPX2v5D2/HU1Ro2rEip3O5Vwm4IXNHRllvrUkYZEGUWxxtbDmkJ1dhQz6fE+P0uDf0h6b3Dttt+90zF0pNkUaMyB/cSb4g7NlPeBI1hdQllkLvTq96nzwZeabv1u7UqkX0MuIVyJ3kk8DvKe/rvbVQgTmdSmnZL2sz2LzTNkNpdGh1X0mG239G0riuqixnbvrO1GJIsFqt6G/esAuwJ3Gj7zdPs0gpJ32PxGFaLevDa/nBrQQ0gaZ7tbaqksVXVY/Z829t2ILZLgJdR2q2fBWxp++qqyOyMDg+hsRalVVH9IqETJ2FJR9veX9JZAzbbHZpETNJF/a0c1ZH5weuqxPs5Sp8aKBc0/2T74pmOJXUWNba/Wl+WdALdKWOtW9/2bm0HMYLbJK0G/C9wXNX7tCtDVd9v+/8AJF3T65xl+/eSuhLjFFXRxKuBq1h8B9yZIcprd4y79zfnrZr9tk7S6yh1k5tKqifZRwDz2olqqM8Db7F9FoCkXSgTds14UkuyGG4TSrlw10zKGFZ7AHdR5l/eh3IV35WishWqq/QVgPurx70JGLo6g+TLKf0C7mk7kAY/BfqLogata8NJlIYr76cMm9PzJ9u/byekof7SSxQAtn8o6c9tBJJkUVNrRqnq92+Bf281qMF2Al4t6Ro6OIaVpLdQWulc7DIdKEBn6gAqa1CK8XoJon6V2dWy2cuBNSmNBTpH0jqUZrOrStqKxe/t6kBXmqbeCVzT65si6QmUJt6/osxr0gmSev/L51WttnojDLyCUmw68zGlzmLyTFfh2aGKzg9RRnLdDLiUclX5E+Ac27e0Gdskk7QNZc6Vy6nNt2L7xa0FVSNpX0ox2TaU5p29ZHE7cKw7MOy7pLOB19r+P5UJmi6gTFP7JOCnXanglvSjIZtte+cZC6aSZNGnGvph0XAKtr/RckjT6u+/0LVxbSStRDlx7ABsX/3c1oUevJNI0nzKvNaXURt51PbZrQU1gKS32T6ib93Gtq9pK6ZaHJf1Gi9IOpQy7PvrqxaG87rasKELUgxVI+mTwBMot3wAB0ja1fYbhuw246brvwB0rf/CqpQiiDWqnxspJ7p4YP5ge9AgfV2zN6VjXt3JQBcGlaxfHT+H8n+Ey/DkrQz93UTSCyj/2/ULw8NmOo4ki6meBWxRG0jwWLp5cnsvsB19/RdajmmRaiC5J1PGMTqPUgz1X7ZvbTWwyXehpPdTytbrxVBdaTq7GeVzX0NTZyJcne704J8v6XDKMBqbUsasohoNQcN2bEN1AbsmpRf85yn9q85tI5Yki6mupLR+6pX9b0Apc++ae23frDJ71gq2z5L0gbaDqtkQWJkyV/ANlLFsbhu6R4sk7QRsYvvzKsNBr9aFIpMBtqp+b1db15mms5Te5X9DObm9qLb+T8BrW4loSf9EaZ23GbCb7b9U67cAOjWTX2Un21tWfUDeLekI4KuNe41B6iwASd+i/NOtQRk3/vxq07aUSq/ntRXbIJJOp4wR835gbUpR1DNs79BqYDWSRLnK3KH62YLSW/oc24e0GVudpEMo9SpPrIaqfizwla6N4DtJJG1v+5y243gokHSe7WdKOo/SFP1mypw7m854LEkWIOlZw7Z3sALx4ZQmgCuwuP/CcbZvbjWwASStT5k3YAfKVeejbK/ZblSLTcpQ1bCoqOQQSpEElDkODu3a2GCTMmzOJJD0H8B/U4Z3/zhlxIZj22i1lWIopiYDSY+h3F1AGQCtc23ae7fOVUey24HLu5QoqhEzd6AkiXupms0Cx9C9OqB7+oaq7uJQ7z3HUJrNvrxa/ntKOfbfTrtHO75de7xo2JyWYplotv+jevgVlfniV22r+XnuLGokvRz4IPBDSmXXXwFvtX1ym3H1VF+Wg2xfXo3qeRFliILHAZ+x/d+tBliR9F9UfSts/6bteIaR9G+Unvq7Uor1/hE43vbHWw1sAA2enGuJdV2jMuPk6V0aG6rrVKZ0ntMbhkbSnpTWhVDeyxm/iE2yqKkGl9u190FUlZ2nd2VwMUnze8N7S3oHsJntf6i+WD/pYtHJJJC0K1OHqv5ByyENJOkcysVLb9KrHYEP2d6+3ciGk/RE4Du2n9B2LD3VAH1vpzQ7n83iURC6MCQJko6ilGwcUy1fRWm5tSplCuXXz3RMKYaaaoW+jH0z3Ron6N7a4+cCnwGw/aeuthGfEJdSWm8BdHHmuZ5/Bo6tNfO8Bdi33ZCWpCVnH+zisDnHA++gr4NjhzyT8nn33G77n6HM8thGQEkWU31P0vdZ3CnvFcCpLcbT7zpJb6I0Rd0a+B6ApFUpE+PEUhpQ9PhxSZ0peqyz/TPgqSqTXmH79pZDGsiTMfvgzV0YfmSI2Z5a7PPq2uM1aEGKofpUc1rsSDlx/K/tr7cc0iLV8B6HAusCR9rudSh6NvB02x9qM75J1PWix7pJaA0laTZwX9VoYAPKFfKCKtF1hqTnUzq4nc7UDo6dGExQ0qWU7+Xv+tavC5zWxrAkSRYxNlUv3g8Aj6Yk31658OqtBlZTHyuoWl4BuKSLYwRJ+iqlNVRvBN+/B55quxOtoSS9lvJ5/5kyysBbKY0wtgKOsd2ZjqPV6AxbAlewuBjKtv+hvagWqwZlfD2lA2FvoqOtKR0HP2X7CzMeU5LFwDLWRZvo2MltkkhaALzI9s/bjmU6kj5IOWn0ih73Bi61/bb2ohqs662hqoEOd6JMJPRzYCPbf1CZEvQCd2judUmXu4Nzl9dJ+htKvcrmlPPTFcDhtr/VRjyps2B4GWs1GmU8ML/rcqIAsP3W6g6oV/R4VIdHGr5T0k59raFam5N5gHuq8b9ulbTA9h8AbN8hqWsTNp0n6Ym2r2w7kOnY/jZT+6y0KskCkPRu2+8dsH51yqBtu8x4UBOsNojcPElfBr7B1HLh1isW++4m6wPIvVbSXZSpS99p+4wZD256g1pDvbrViKbqTXq0ArCSFk+AJLozkGDPtsCl1d1vfQKxTjSd7aIUQwGSTqPcJr+ztm4d4PvA12y/p7XgBpC0KfAp4DG2t1CZVevFtv+z5dCARcM9TMddH/ZB0izKWFbHdbGooqutoSQNncHN9rNnKpYmKhMfLcH2VTMdy6RIsoDeZPInA/9n+0BJmwDfBT5o+9PtRrckldm+3gp8ujaeUefKYCXtaPsnTeu6StLruvD5Szpw2HbbXRwttfMkbUGpY4Ey0dn8NuPpuhRDAbbvqrrTnyjpRMqMbm/pUrPZPg+zfX4Z2HWRhW0FM8THKS04mtZ1UhcSRWUS+i1MFElvpLQ26tVPnSTpSNufbDGsRSS90vYJ1ThrS3ALk2AlWTDlyu184G3Aj4CNe+s7eOX2h+o2ujf43V5AZ8ZgkrQ9ZSDBOX1XxasDs9qJanJ1rRj0IWJ/YFvbfwaQdBhlPLNOJAtgrer3nFajqEmyKOpXbh8bsK5r3gAcDWwm6QbgGuBV7YY0xUrAapTvV/19vB3Yq5WIJlhVTPoK4FbgW5QiyJ0plfDv7bU6iqUipg6fcy8dmimvd4dj+91tx9KTOosJVg2nvYLtP7UdyyCSNrL9K0kP9+IZyWIpSTqJcjJ7OOWK83JK0tgJeJrtv2kxvCWolI/uAzzO9qGSNgTWsX1+w65jJ2m27YWS3kaZirg369yewAldGwVBZRrd9wN3AN8Bngb8q+3jZzyWJIvJIelVtv9nugrPrhWXVcVRn6NMU7qhpKcCr2tjxMxJ1mu8UA2lcb3tdWrbLuna0CSSPkXpFf0c209SmXflNNvPaNh17CRd1GseK+kZlGkIekP7XNBqcAP0Ol1KeglleJIDaWk4mhRDTZbexDxdLiKr+2/gBZS+Kti+RNLOw3eJAe4BqK6I+ycRuq+FeJo80/bWki4GsH2rpJXaDqqyqKipSg6dSxB9eufov6bc+dykaqKutgIJSvt621385wMWt86ZpApP29f1tdrq7PvbYetL+hjlRNd7TLW8XnthTeveqq9KrwHGHLozDHh/o4spunZ3DnxX0uWU/5s3SFqbWgfXmZRkMdUCSScDn7d9RdvBTKf653stMJfaZ9jBzm7XSdoBcHVl+WbKmEGxdN5aezyvb1v/chd8DPg68GhJ76M0auhKRe0sSuOLzlRmD1MNR/NB4JbqzvIuWppGN3UWNSozzu0N7EcZsuAY4MQO9pT9KaV574XUrtRtf3XanVpQXQV9FHge5f38PvAv7tB84TEekjajTNAl4IyujBFWr7PoMkkvHra9jaHUkyymUZWtnwCsSend/V7bC9qNqujSSKMR/SR9yfbfN61rg6SLe6MedJmkLw3Z3MpQ6imGqqnKWV9IubOYC3wYOI7SYuJUYNPWgpvq25L+2naXZvFbgqTHUe4stqOUX59DafZ3dauBxbhNGYq8+r96ekux9Htu2wGMoguJtV/uLGokXQ2cBXzO9k/7tn3M9sCu9zOtGjH14ZSKrl5nos7NuyHpXOBIps4V8Sbbz2wvqhgXSW+nzL+wKqVfQK9e4B7gaNtvbyu2SSXpHYPW2z5sxmNJslhM0mq97v9dVXV42sD2r9uOpYmk8/oTg6RzbW/XVkyTSNLHGTw5FwBduYjpkfT+JIZlQ9K/1xZXoZR8zLe934zHkmSxmKSNgTexZCujoZVNM03Shba7clu/BEmPrB6+DbgNOJFysnsFsPKguUNieipTbE7L9rHDts80lalp/w7Y2PZ7VebiXrcLPbgnXTX0yzds7zbjr51ksZikSyg9ji+j1i7c9tmtBTWApCOBL3SxxymApGsoyWFQ80TbftwMh/SQ0vXhU7rcg3vSVRNfzbO9yUy/diq4p7qrjaF/H4BnAwdIuhb4C4vrLLZsNaqK7Y3bjuGhqD58CtDl4VO63IN7ItTGsLqYxUWQs4B1gRmvr4Aki34flXQIcBpTpwG9qL2QBtq97QBGVU0wszm1aTVtf7G9iCbapAyf0uUe3JPifMq8L/VRmhcCv7WdHtwd8BTg74HnsPjL7Wq5M6qRXHcCNrH9+eqfcbW24+pXJd5dKMniVEqS+zGQZPEATcjwKYN6cL+r3ZAmjqBb07wmWUy1J2VY5XvaDmSY6iS8DfBE4PPAisD/ADu2GdcAewFPBS62vZ+kxwCfbTmmSTYRw6fYPk7ShSzuwf2SrvTgniCdG8MqyWKqSyg9tn/fdiAN9gS2Ai4CsH1jNVRJ19xp+35JCyWtTnlfU7n9wB1A6eS4HnA9pbj0Da1GVFO11DkAeAKlkcinbXdxut9J0LkxrJIspnoM8AtJFzC1zqJTTWeBe2y7N1RxNQlSF82TtCbwGco4Vn+mlMXGA1DNiLdP23EMcSylk+iPKEWOTwLe0mpEk+s3tg9tO4i6NJ2tkfSsQes72HT234BNgF0ps2j9I3C87Y+3GtgQkuYCq9u+tOVQJlZ15f4aynAa9QYDnRhtWNJltp9SPZ4NnD8Jg/Z1URfHsFqh7QC6xPbZ9R9K64OXtx1Xv2rqx5MpU0I+ETi4i4lC0hmS/hrA9rW2L5V0dNtxTbAvAetQWkSdDawPdGlK3UVzWqf46UHr3BhWubPoI+lplN6nLweuAb5q+xPtRjW9ahjwm93BD7Iaa+s64MzehE2TMkR0F/WuNiVdantLSSsC37fdidZ6ku6j9PuBUtZeHyOqc2OXxdLJnQUgaVNJB0v6OfAJyglOtp/dpUQhaTtJP5T0NUlbVTNoXQ78TtKMd/8fwW2UK6THSPpW1fs0HrjelfttVf+VNShD03SC7Vm2V69+HmF7du1xEsWESwV38QtKpdyLenNWSPrXdkMa6BOUUT3XAM4Edrd9bjXRzAnA99oMbgBVxRGvl/RqSh+LtdoNaaIdXQ2d8W5Kx7zVgIPbDSmWF0kWxUspw2efJel7lIHvOtNkrWa27dMAJB1q+1wA27/o66jVFUf1Htj+gqTL6FBTz0lju9dH5WzSBDlmWOosaqomqC8BXknptX0s8PXeCbpt9fL+/rL/LtUFSFrd9u210WensH3LTMf0UCBpZcqFzVymjorcqSaW8dCUZDGN6kT3MuAVHaxArFceUi2vYnvFtmKrk/Rt238zzeizGXX2Aaruev/IknOvf7i1oGK5kWQRMSEkXW57i7bjiOVT6iximZM0tDisg6P4ToqfSnqK7cvaDiSWP7mziGVO0llDNrsrxXqTomoYYMrF3SbA1ZThaDo1j0k8tCVZRHScpI2Gbbf9q5mKJZZf6ZQXy5ykt9Uev6xvWyuzfE0y27+qEsK6wC215Vsow39EjF2SRYzD3rXHb+/b1sWe5pPiU5SRe3v+Uq2LGLskixgHTfN40HKMTvUxwGzfTxqpxAxJsohx8DSPBy3H6K6W9GZJK1Y//0Kp7I4Yu1RwxzI3KZ0HJ42kR1Pmt34OJemeAbzFdtdndoyHgCSLiIholPLOiI6T9DbbR0j6OAOK8Wy/uYWwYjmTZBHRfT+vfs9rNYpYrqUYKiIiGuXOIqLjJJ0ybLvtF89ULLH8SrKI6L7tKVP9ngCcR/qqRAtSDBXRcZJmAbtSJuXaEvgOcILt+a0GFsuVdMqL6Djb99n+nu19ge2ABcAPJb2p5dBiOZJiqIgJUE2p+kLK3cVcSue8r7UZUyxfUgwV0XGSjgW2AL4LnGj78pZDiuVQkkVEx0m6nzJ8CkztlNeb/Gj1mY8qljdJFhER0SgV3BER0SjJIiIiGiVZREREoySLCEDSOpJOlHSVpCsknSpp0wd5zLmSLq8ebyPpY9M871pJazcc6x0PJpaIByvJIpZ7kgR8Hfih7cfb3hx4B/CYZfUatuc9yKHEkyyiVUkWEfBs4F7bR/VW2P4ZcLGkMyRdJOkySXvAojuGn0v6jKT5kk6TtGq17emSLpF0DvCG3vEk7SLp29XjR1X7XCzp09TGepL0DUkXVsfdv1p3OLCqpJ9JOq5a9ypJ51frPl0NCRIxNkkWEaXD24UD1t8F7Gl7a0pC+XB1FwKwCXCk7ScDtwEvrdZ/Hniz7e2HvN4hwI9tbwWcAmxY2/aPtp8ObAO8WdKjbB8E3Gn7abb3kfQk4BXAjrafBtwH7PMA/u6IkWW4j4jpCThM0s7A/cB6LC6auqa6+4CSaOZKWgNY0/bZ1fovAbsPOO7OwN8C2P6OpFtr294sac/q8QaUpHRz3/7PBZ4OXFDlrlWBzMMdY5VkEQHzgb0GrN8HmAM83fa9kq4FVqm23V173n2UE7YYMO3pNJZ4nqRdgOcB29u+Q9IPa6835anAsbbfPuJrRTxoKYaKgDOBlSW9trdC0jOAjYDfV4ni2dXytGzfBvxR0k7VqumKhv63t03S7sBa1fo1gFurRLEZZYTZnnslrVg9PgPYS9Kjq2M8UtLQ2CIerCSLWO65jHmzJ7Br1XR2PvAfwKnANpLmUU7uvxjhcPsBR1YV3HdO85z3ADtLugh4PvDrav33gNmSLgXeC5xb2+do4FJJx9m+AngXcFr13B8A6478B0c8ABkbKiIiGuXOIiIiGiVZREREoySLiIholGQRERGNkiwiIqJRkkVERDRKsoiIiEb/H0kMxSMyTnl8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Biden Telling us what he is saying is a matter of fact\n",
      "fact | matter | number | fact matter | clear | man | price | matter fact | deal | senator\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The American Country\n",
      "country | american people | america | healthcare | people country | economy | future | state | today | government\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Global Diplomatic Issues\n",
      "world | america | allies | china | iran | climate change | rest | united states | rest world | problem\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Social/Constitutional Rights\n",
      "right | woman | american people | wrong | court | politicians | government | family | constitution | democracy\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Healthcare and Medicare\n",
      "money | plan | medicare | healthcare | year | years | family | bill | premiums | public option\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Donald Trump\n",
      "donald trump | democrats | families | trump | stage | house | candidate | wealthy | donald trump donald trump | mayor bloomberg\n"
     ]
    },
    {
     "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": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "topic_speaker_dist = df_speaker_topics.apply(percent_comp, axis=1)\n",
    "\n",
    "for i, topic in enumerate(topic_term_matrix):\n",
    "    print(names[i])\n",
    "    print(' | '.join(terms[idx] for idx in np.argsort(topic)[::-1][:10]))\n",
    "    topic_speaker_dist[f'topic_{i}'].plot.bar()\n",
    "    plt.title(f'Topic: {names[i]}')\n",
    "    plt.xlabel('Candidate')\n",
    "    plt.ylabel('Percent of Topic')\n",
    "    plt.show()"
   ]
  }
 ],
 "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": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}