topic_modeling_ted_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:08:30.547215Z",
     "start_time": "2017-11-15T20:08:28.639903Z"
    }
   },
   "outputs": [],
   "source": [
    "import nltk, re, pickle, os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "from textblob import TextBlob\n",
    "from nltk.tokenize import sent_tokenize, word_tokenize, wordpunct_tokenize, MWETokenizer\n",
    "from nltk.stem import porter, WordNetLemmatizer\n",
    "\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.util import ngrams\n",
    "\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
    "from sklearn.decomposition import LatentDirichletAllocation,  TruncatedSVD, NMF\n",
    "from sklearn.neighbors import NearestNeighbors\n",
    "\n",
    "#import pyLDAvis, pyLDAvis.sklearn\n",
    "#from IPython.display import display\n",
    "\n",
    "from sklearn.preprocessing  import  StandardScaler\n",
    "\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "path = '/Volumes/ext200/Dropbox/metis/p4_fletcher/pick/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:08:32.451011Z",
     "start_time": "2017-11-15T20:08:31.800142Z"
    }
   },
   "outputs": [],
   "source": [
    "#open metadata and cleaned talks\n",
    "\n",
    "with open(path + 'ted_all.pkl', 'rb') as picklefile:\n",
    "    ted_all = pickle.load(picklefile)\n",
    "\n",
    "    \n",
    "with open(path + 'cleaned_talks.pkl', 'rb') as picklefile:\n",
    "    cleaned_talks = pickle.load(picklefile)    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Vectorize + Topic Modeling \n",
    "look at tfidf in addition to count vectorizer for topic modeling methods\n",
    "\n",
    "Count vect: Convert a collection of text documents to a matrix of token counts This implementation produces a sparse representation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:06:54.880541Z",
     "start_time": "2017-11-15T20:06:54.812697Z"
    }
   },
   "outputs": [],
   "source": [
    "def topic_mod_lda(data,topics=5,iters=10,ngram_min=1, ngram_max=3, max_df=0.6, max_feats=5000):\n",
    "    \n",
    "    \"\"\" vectorizer - turn words into numbers for each document(rows)\n",
    "    then use Latent Dirichlet Allocation to get topics\"\"\"\n",
    "    \n",
    "    \n",
    "    vectorizer = CountVectorizer(ngram_range=(ngram_min,ngram_max), \n",
    "                             stop_words='english', \n",
    "                             max_df = max_df, \n",
    "                             max_features=max_feats)\n",
    "    \n",
    "      \n",
    "    #  `fit (train), then transform` to convert text to a bag of words\n",
    "\n",
    "    vect_data = vectorizer.fit_transform(data)\n",
    "    \n",
    "    \n",
    "    \n",
    "    lda = LatentDirichletAllocation(n_components=topics,\n",
    "                                    max_iter=iters,\n",
    "                                    random_state=42,\n",
    "                                    learning_method='online',\n",
    "                                    n_jobs=-1)\n",
    "    \n",
    "    lda_dat = lda.fit_transform(vect_data)\n",
    "    \n",
    "    \n",
    "    # to display a list of topic words and their scores \n",
    "    \n",
    "    def display_topics(model, feature_names, no_top_words):\n",
    "        for ix, topic in enumerate(model.components_):\n",
    "            print(\"Topic \", ix)\n",
    "            print(\" \".join([feature_names[i]\n",
    "                        for i in topic.argsort()[:-no_top_words - 1:-1]]))\n",
    "    \n",
    "    display_topics(lda, vectorizer.get_feature_names(),20)\n",
    "    \n",
    "    \n",
    "    return vectorizer, vect_data, lda, lda_dat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "best yet \n",
    "cleaned_talks,topics=23,\n",
    "                                     iters=100,\n",
    "                                     ngram_min=1, \n",
    "                                     ngram_max=2, \n",
    "                                     max_df=0.4, \n",
    "                                     max_feats=2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:16:22.346442Z",
     "start_time": "2017-11-15T20:09:22.869545Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic  0\n",
      "woman men child girl family community young black mother sex boy home man country white school story female father gender\n",
      "Topic  1\n",
      "food plant water eat farmer product plastic waste grow seed feed farm produce crop egg soil diet eating percent agriculture\n",
      "Topic  2\n",
      "universe earth planet space light star science mars physic particle galaxy sun theory billion matter hole black number image away\n",
      "Topic  3\n",
      "water ocean specie animal 000 tree sea forest fish earth planet ice area year ago river million coral bird foot shark\n",
      "Topic  4\n",
      "country percent money dollar business africa company million market economy billion 000 government cost global economic job india growth china\n",
      "Topic  5\n",
      "book word sort picture guy story medium number read page image paper interesting internet wanted write little bit 000 basically somebody\n",
      "Topic  6\n",
      "music sound song voice hear em baby listening bee noise listen play hearing ear heard note silence played band speed\n",
      "Topic  7\n",
      "love story feel friend man old moment told wanted night home oh remember experience person hand felt god believe knew\n",
      "Topic  8\n",
      "car hour fly mile 000 drive road percent minute vehicle driving driver 10 flight airplane turn 100 speed little bit dollar\n",
      "Topic  9\n",
      "game play video real film camera object piece playing hand technology movie using computer sort create eye experience physical player\n",
      "Topic  10\n",
      "city building design art space project built street create artist community new york york house wall public architecture build designer form\n",
      "Topic  11\n",
      "school kid child student teacher education learning learn language teach high class parent science knowledge english high school university classroom old\n",
      "Topic  12\n",
      "brain mind example pattern understand behavior person memory experience science neuron body study self turn happens maybe experiment information course\n",
      "Topic  13\n",
      "energy ca climate oil carbon power air fuel nuclear gas climate change solar global electricity percent wind water emission temperature clean\n",
      "Topic  14\n",
      "society social political power believe culture century history choice democracy reason group country state religion value example individual american sense\n",
      "Topic  15\n",
      "robot body animal leg rule material ant structure arm foot dog tail dinosaur nature build head bone force surface create\n",
      "Topic  16\n",
      "cell cancer disease dna gene drug virus body genome blood molecule genetic tissue bacteria vaccine protein tumor stem biology lab\n",
      "Topic  17\n",
      "patient health doctor care medical disease hospital heart treatment study death medicine surgery percent drug sleep research child blood help\n",
      "Topic  18\n",
      "data technology computer information machine company phone internet network using digital device example algorithm tool build software open help future\n",
      "Topic  19\n",
      "war government country united states conflict united states military security refugee soldier attack group weapon afghanistan peace gun police iraq state\n"
     ]
    }
   ],
   "source": [
    "vect_mod, vect_data, lda_mod, lda_data = topic_mod_lda(cleaned_talks,\n",
    "                                                       topics=20,\n",
    "                                     iters=100,\n",
    "                                     ngram_min=1, \n",
    "                                     ngram_max=2, \n",
    "                                     max_df=0.5, \n",
    "                                     max_feats=2000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:25:46.602136Z",
     "start_time": "2017-11-15T20:25:46.598326Z"
    }
   },
   "source": [
    "# for each document, assign the topic (column) with the  highest score from the LDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:25:00.419658Z",
     "start_time": "2017-11-15T20:25:00.388311Z"
    }
   },
   "outputs": [],
   "source": [
    "topic_ind = np.argmax(lda_data, axis=1)\n",
    "topic_ind.shape\n",
    "y=topic_ind\n",
    "\n",
    "# create text labels for plotting\n",
    "tsne_labels = pd.DataFrame(y)\n",
    "\n",
    "# save to csv\n",
    "tsne_labels.to_csv(path + 'tsne_labels.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-13T22:16:11.778984Z",
     "start_time": "2017-11-13T22:16:11.624198Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "topic_names = tsne_labels\n",
    "topic_names[topic_names==0] = \"family\"\n",
    "topic_names[topic_names==1] = \"agriculture\"\n",
    "topic_names[topic_names==2] = \"space\"\n",
    "topic_names[topic_names==3] = \"environment\"\n",
    "topic_names[topic_names==4] = \"global economy\"\n",
    "topic_names[topic_names==5] = \"writing\"\n",
    "topic_names[topic_names==6] = \"sounds\"\n",
    "topic_names[topic_names==7] = \"belief, mortality\"\n",
    "topic_names[topic_names==8] = \"transportation\"\n",
    "\n",
    "topic_names[topic_names==9] = \"gaming\"\n",
    "topic_names[topic_names==10] = \"architecture\"\n",
    "topic_names[topic_names==11] = \"education\"\n",
    "\n",
    "topic_names[topic_names==12] = \"neuroscience\"\n",
    "topic_names[topic_names==13] = \"climate, energy\"\n",
    "\n",
    "topic_names[topic_names==14] = \"politics\"\n",
    "topic_names[topic_names==15] = \"robotics\"  \n",
    "topic_names[topic_names==16] = \"disease biology\"\n",
    "topic_names[topic_names==17] = \"medicine\"\n",
    "topic_names[topic_names==18] = \"technology, privacy\"\n",
    "topic_names[topic_names==19] = \"war\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-13T22:16:30.403758Z",
     "start_time": "2017-11-13T22:16:30.368886Z"
    }
   },
   "outputs": [
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       "      <td>neuroscience</td>\n",
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       "      <th>2438</th>\n",
       "      <td>disease biology</td>\n",
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       "      <th>2439</th>\n",
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       "      <td>belief, mortality</td>\n",
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       "      <td>belief, mortality</td>\n",
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       "      <td>politics</td>\n",
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       "      <td>technology, privacy</td>\n",
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       "      <td>politics</td>\n",
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       "      <td>belief, mortality</td>\n",
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       "      <td>global economy</td>\n",
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       "      <td>agriculture</td>\n",
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       "      <td>global economy</td>\n",
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       "      <td>global economy</td>\n",
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       "      <td>global economy</td>\n",
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       "      <td>environment</td>\n",
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       "      <td>robotics</td>\n",
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       "      <td>belief, mortality</td>\n",
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       "      <td>architecture</td>\n",
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      ],
      "text/plain": [
       "                        0\n",
       "0       belief, mortality\n",
       "1         climate, energy\n",
       "2     technology, privacy\n",
       "3            architecture\n",
       "4          global economy\n",
       "5       belief, mortality\n",
       "6       belief, mortality\n",
       "7            architecture\n",
       "8                politics\n",
       "9       belief, mortality\n",
       "10           architecture\n",
       "11      belief, mortality\n",
       "12                writing\n",
       "13                 gaming\n",
       "14                writing\n",
       "15      belief, mortality\n",
       "16                writing\n",
       "17         global economy\n",
       "18           architecture\n",
       "19                writing\n",
       "20    technology, privacy\n",
       "21                writing\n",
       "22                writing\n",
       "23           neuroscience\n",
       "24      belief, mortality\n",
       "25                  space\n",
       "26                  space\n",
       "27         global economy\n",
       "28      belief, mortality\n",
       "29           neuroscience\n",
       "...                   ...\n",
       "2437         neuroscience\n",
       "2438      disease biology\n",
       "2439    belief, mortality\n",
       "2440       global economy\n",
       "2441    belief, mortality\n",
       "2442               family\n",
       "2443            education\n",
       "2444                  war\n",
       "2445               gaming\n",
       "2446             politics\n",
       "2447    belief, mortality\n",
       "2448             politics\n",
       "2449  technology, privacy\n",
       "2450      climate, energy\n",
       "2451          environment\n",
       "2452               family\n",
       "2453             politics\n",
       "2454    belief, mortality\n",
       "2455       global economy\n",
       "2456          agriculture\n",
       "2457       global economy\n",
       "2458                space\n",
       "2459               family\n",
       "2460  technology, privacy\n",
       "2461       global economy\n",
       "2462       global economy\n",
       "2463          environment\n",
       "2464             robotics\n",
       "2465    belief, mortality\n",
       "2466         architecture\n",
       "\n",
       "[2467 rows x 1 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
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    }
   ],
   "source": [
    "topic_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-13T22:17:07.519083Z",
     "start_time": "2017-11-13T22:17:07.481396Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#save text labels to csv and pkl for plotting\n",
    "\n",
    "topic_names.to_csv(path + 'topic_names.csv')\n",
    "\n",
    "with open(path + 'topic_names.pkl', 'wb') as picklefile:\n",
    "    pickle.dump(topic_names, picklefile)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualize the first 2 components from the topic modeling (LDA). \n",
    "Not really the best way to look at clusters, but a good place to start."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:28:17.621582Z",
     "start_time": "2017-11-15T20:28:09.867331Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda/lib/python3.5/site-packages/pyLDAvis/_prepare.py:387: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  topic_term_dists = topic_term_dists.ix[topic_order]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.css\">\n",
       "\n",
       "\n",
       "<div id=\"ldavis_el288101122321200161519143404\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "\n",
       "var ldavis_el288101122321200161519143404_data = {\"R\": 30, \"plot.opts\": {\"ylab\": \"PC2\", \"xlab\": \"PC1\"}, \"lambda.step\": 0.01, \"token.table\": {\"Freq\": [0.24569692757457445, 0.017843910941170212, 0.031913148414015956, 0.11907379031896276, 0.03671727828279255, 0.2151563876944947, 0.030540539880079785, 0.02676586641175532, 0.03877619108369681, 0.02161858440949468, 0.019216519475106383, 0.13657454912664893, 0.01338293320587766, 0.03637412614930851, 0.007206194803164893, 0.0027452170678723404, 0.7099363413876009, 0.00377625713504043, 0.09440642837601075, 0.00755251427008086, 0.03398631421536387, 0.14349777113153636, 0.015578473263573289, 0.07789236631786645, 0.13085917541401562, 0.021809862569002605, 0.6542958770700782, 0.006231389305429316, 0.09347083958143973, 0.10486369180591644, 0.1997005764272034, 0.0008355672653857884, 0.03509382514620311, 0.07561883751741384, 0.10904152813284537, 0.01921804710387313, 0.08689899560012199, 0.01880026347118024, 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217.5808719689227, 313.7527376242618, 389.44394842870304, 182.47596364577865, 248.2917329938341, 564.424315748116, 289.02015415921693, 292.9092174393489, 208.03347894636556, 388.33573130491436, 227.7969027700614, 203.9324468663172, 501.7548027398403, 207.6043552080615, 207.5220959074191, 1825.5893476531417, 1271.2013515860112, 1063.3758428380415, 597.412612578415, 482.289191612483, 1356.6027937417311, 1370.1864462745627, 741.8794849711823, 1258.0970425440305, 2734.4761856904174, 2059.924135136482, 1684.535447498364, 2278.1607331759465]}, \"topic.order\": [8, 5, 15, 13, 19, 6, 11, 4, 1, 3, 10, 18, 12, 17, 9, 14, 20, 2, 16, 7]};\n",
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       "       new LDAvis(\"#\" + \"ldavis_el288101122321200161519143404\", ldavis_el288101122321200161519143404_data);\n",
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       "   // require.js is available: use it to load d3/LDAvis\n",
       "   require.config({paths: {d3: \"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min\"}});\n",
       "   require([\"d3\"], function(d3){\n",
       "      window.d3 = d3;\n",
       "      LDAvis_load_lib(\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.js\", function(){\n",
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       "    // require.js not available: dynamically load d3 & LDAvis\n",
       "    LDAvis_load_lib(\"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js\", function(){\n",
       "         LDAvis_load_lib(\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.js\", function(){\n",
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       "</script>"
      ],
      "text/plain": [
       "PreparedData(topic_coordinates=            Freq  cluster  topics         x         y\n",
       "topic                                                \n",
       "7      15.585274        1       1  0.005882 -0.078949\n",
       "4       9.309560        1       2  0.109295 -0.068564\n",
       "14      7.987524        1       3  0.069895 -0.085987\n",
       "12      6.900363        1       4  0.006737  0.102333\n",
       "18      6.794293        1       5  0.056892  0.043012\n",
       "5       6.006289        1       6  0.015308 -0.014689\n",
       "10      5.438628        1       7  0.012518  0.075937\n",
       "3       5.407138        1       8  0.016589  0.056563\n",
       "0       4.822184        1       9  0.077258 -0.228624\n",
       "2       3.985105        1      10 -0.007261  0.129881\n",
       "9       3.973987        1      11 -0.056266  0.134987\n",
       "17      3.957960        1      12  0.071148 -0.087460\n",
       "11      3.450202        1      13  0.083880 -0.078291\n",
       "16      3.272524        1      14  0.037802  0.080084\n",
       "8       3.028973        1      15  0.012690  0.044023\n",
       "13      2.811471        1      16  0.034649  0.038878\n",
       "19      2.774401        1      17 -0.002233 -0.164643\n",
       "1       2.319808        1      18  0.033793  0.051596\n",
       "15      1.430406        1      19 -0.134770  0.204718\n",
       "6       0.743910        1      20 -0.443807 -0.154806, topic_info=     Category         Freq           Term        Total  loglift  logprob\n",
       "term                                                                    \n",
       "1962  Default  3877.000000          woman  3877.000000  30.0000  30.0000\n",
       "230   Default  3221.000000          brain  3221.000000  29.0000  29.0000\n",
       "1546  Default  2873.000000         school  2873.000000  28.0000  28.0000\n",
       "1648  Default  1544.000000          sound  1544.000000  27.0000  27.0000\n",
       "289   Default  2306.000000           cell  2306.000000  26.0000  26.0000\n",
       "310   Default  3620.000000          child  3620.000000  25.0000  25.0000\n",
       "273   Default  2094.000000            car  2094.000000  24.0000  24.0000\n",
       "323   Default  2926.000000           city  2926.000000  23.0000  23.0000\n",
       "984   Default  2650.000000            kid  2650.000000  22.0000  22.0000\n",
       "742   Default  1814.000000           food  1814.000000  21.0000  21.0000\n",
       "1189  Default  1151.000000          music  1151.000000  20.0000  20.0000\n",
       "1933  Default  2648.000000          water  2648.000000  19.0000  19.0000\n",
       "1511  Default  1212.000000          robot  1212.000000  18.0000  18.0000\n",
       "418   Default  3959.000000        country  3959.000000  17.0000  17.0000\n",
       "220   Default  2287.000000           body  2287.000000  16.0000  16.0000\n",
       "1336  Default  1825.000000           play  1825.000000  15.0000  15.0000\n",
       "603   Default  1757.000000         energy  1757.000000  14.0000  14.0000\n",
       "1925  Default  1523.000000            war  1523.000000  13.0000  13.0000\n",
       "464   Default  2669.000000           data  2669.000000  12.0000  12.0000\n",
       "1291  Default  1414.000000        patient  1414.000000  11.0000  11.0000\n",
       "267   Default  1434.000000         cancer  1434.000000  10.0000  10.0000\n",
       "856   Default  1149.000000           hear  1149.000000   9.0000   9.0000\n",
       "1131  Default  1584.000000            men  1584.000000   8.0000   8.0000\n",
       "776   Default  1521.000000           game  1521.000000   7.0000   7.0000\n",
       "852   Default  1698.000000         health  1698.000000   6.0000   6.0000\n",
       "112   Default  1639.000000         animal  1639.000000   5.0000   5.0000\n",
       "495   Default  1946.000000         design  1946.000000   4.0000   4.0000\n",
       "1908  Default   935.000000          voice   935.000000   3.0000   3.0000\n",
       "1711  Default  1525.000000        student  1525.000000   2.0000   2.0000\n",
       "814   Default  1806.000000     government  1806.000000   1.0000   1.0000\n",
       "...       ...          ...            ...          ...      ...      ...\n",
       "856   Topic20   345.779943           hear  1149.133913   3.7000  -3.1741\n",
       "165   Topic20   266.211026           baby   995.577678   3.5820  -3.4356\n",
       "731   Topic20    56.390791         flower   217.580872   3.5507  -4.9876\n",
       "1337  Topic20    75.899174         played   313.752738   3.4818  -4.6905\n",
       "1226  Topic20    93.885803           note   389.443948   3.4784  -4.4778\n",
       "1423  Topic20    31.662866          quiet   182.475964   3.1495  -5.5647\n",
       "184   Topic20    30.599356           beat   248.291733   2.8074  -5.5989\n",
       "1662  Topic20    69.014870          speed   564.424316   2.7995  -4.7856\n",
       "1861  Topic20    30.990434        typical   289.020154   2.6682  -5.5862\n",
       "1530  Topic20    30.519341         sample   292.909217   2.6395  -5.6015\n",
       "1519  Topic20    21.322298        roughly   208.033479   2.6231  -5.9601\n",
       "868   Topic20    38.479809            hey   388.335731   2.5893  -5.3697\n",
       "1521  Topic20    22.250090            row   227.796903   2.5749  -5.9175\n",
       "1567  Topic20    19.392219        sending   203.932447   2.5481  -6.0550\n",
       "209   Topic20    45.443980           bird   501.754803   2.4994  -5.2034\n",
       "1208  Topic20    18.660434        nervous   207.604355   2.4918  -6.0935\n",
       "1799  Topic20    17.937873  thousand year   207.522096   2.4527  -6.1330\n",
       "1336  Topic20   148.480927           play  1825.589348   2.3918  -4.0194\n",
       "857   Topic20   101.315761          heard  1271.201352   2.3715  -4.4016\n",
       "93    Topic20    64.478683            air  1063.375843   2.0981  -4.8535\n",
       "1461  Topic20    38.927692         record   597.412613   2.1701  -5.3582\n",
       "693   Topic20    33.604056         faster   482.289192   2.2371  -5.5052\n",
       "1006  Topic20    49.613079       language  1356.602794   1.5925  -5.1156\n",
       "851   Topic20    49.611085           head  1370.186446   1.5825  -5.1157\n",
       "1594  Topic20    38.985747          short   741.879485   1.9550  -5.3567\n",
       "185   Topic20    42.379174      beautiful  1258.097043   1.5103  -5.2732\n",
       "1075  Topic20    49.104767           love  2734.476186   0.8813  -5.1259\n",
       "429   Topic20    45.530993         create  2059.924135   1.0890  -5.2015\n",
       "1517  Topic20    43.357393           room  1684.535447   1.2412  -5.2504\n",
       "162   Topic20    39.156063           away  2278.160733   0.8374  -5.3523\n",
       "\n",
       "[986 rows x 6 columns], token_table=      Topic      Freq          Term\n",
       "term                               \n",
       "0         2  0.245697           000\n",
       "0         4  0.017844           000\n",
       "0         5  0.031913           000\n",
       "0         6  0.119074           000\n",
       "0         7  0.036717           000\n",
       "0         8  0.215156           000\n",
       "0         9  0.030541           000\n",
       "0        10  0.026766           000\n",
       "0        12  0.038776           000\n",
       "0        13  0.021619           000\n",
       "0        14  0.019217           000\n",
       "0        15  0.136575           000\n",
       "0        16  0.013383           000\n",
       "0        17  0.036374           000\n",
       "0        18  0.007206           000\n",
       "0        19  0.002745           000\n",
       "1         2  0.709936    000 dollar\n",
       "1         5  0.003776    000 dollar\n",
       "1         6  0.094406    000 dollar\n",
       "1         7  0.007553    000 dollar\n",
       "1        14  0.033986    000 dollar\n",
       "1        15  0.143498    000 dollar\n",
       "3         2  0.015578      000 year\n",
       "3         3  0.077892      000 year\n",
       "3         4  0.130859      000 year\n",
       "3         7  0.021810      000 year\n",
       "3         8  0.654296      000 year\n",
       "3        10  0.006231      000 year\n",
       "3        15  0.093471      000 year\n",
       "4         1  0.104864            10\n",
       "...     ...       ...           ...\n",
       "1993     17  0.058367          york\n",
       "1993     18  0.018721          york\n",
       "1994      1  0.041482     york city\n",
       "1994      5  0.004148     york city\n",
       "1994      7  0.804746     york city\n",
       "1994      8  0.020741     york city\n",
       "1994      9  0.091260     york city\n",
       "1994     12  0.033185     york city\n",
       "1995      1  0.208916         young\n",
       "1995      2  0.037756         young\n",
       "1995      3  0.061039         young\n",
       "1995      4  0.007551         young\n",
       "1995      5  0.003776         young\n",
       "1995      6  0.001888         young\n",
       "1995      7  0.001259         young\n",
       "1995      8  0.025800         young\n",
       "1995      9  0.478871         young\n",
       "1995     10  0.015102         young\n",
       "1995     12  0.006922         young\n",
       "1995     13  0.090614         young\n",
       "1995     14  0.016990         young\n",
       "1995     15  0.009439         young\n",
       "1995     17  0.028946         young\n",
       "1995     20  0.005663         young\n",
       "1996      1  0.003219  young people\n",
       "1996      2  0.070815  young people\n",
       "1996      3  0.212445  young people\n",
       "1996      5  0.003219  young people\n",
       "1996      9  0.618021  young people\n",
       "1996     13  0.090128  young people\n",
       "\n",
       "[6359 rows x 3 columns], R=30, lambda_step=0.01, plot_opts={'ylab': 'PC2', 'xlab': 'PC1'}, topic_order=[8, 5, 15, 13, 19, 6, 11, 4, 1, 3, 10, 18, 12, 17, 9, 14, 20, 2, 16, 7])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pyLDAvis, pyLDAvis.sklearn\n",
    "from IPython.display import display \n",
    "    \n",
    "    # Setup to run in Jupyter notebook\n",
    "pyLDAvis.enable_notebook()\n",
    "\n",
    " # Create the visualization\n",
    "vis = pyLDAvis.sklearn.prepare(lda_mod, vect_data, vect_mod)\n",
    "\n",
    " # Export as a standalone HTML web page\n",
    "pyLDAvis.save_html(vis, 'lda.html')\n",
    "\n",
    "# # Let's view it!\n",
    "display(vis)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# tSNE\n",
    "\n",
    "a way to reduce dimensionality to three components so that we can visualize where/if there are clusters in document-topic space.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:30:21.699167Z",
     "start_time": "2017-11-15T20:30:21.671280Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_tsne(X,y,v1=0,v2=0):\n",
    "    \"\"\" pass in the X from pca.transform ,and the corresponding y values and a string to add to the title\n",
    "    plots the first three PCA directions/eigenvectors with target values as the color\n",
    "    ___________________________________________________________________\"\"\"\n",
    " \n",
    "    fig = plt.figure(1, figsize=(13, 10))\n",
    "    ax = Axes3D(fig, elev=-150, azim=110)\n",
    "\n",
    "    # plot transformed values (the three features that we have decomposed to) , colors correspond to target values\n",
    "    ax.scatter(X[:, 0], X[:, 1], X[:, 2], c=y,\n",
    "               cmap=plt.cm.hot, edgecolor='k', s=50)\n",
    "    ax.set_title(\"tSNE Ted Topics \", fontsize=16)\n",
    "    ax.set_xlabel(\"1st \",fontsize=16)\n",
    "    ax.w_xaxis.set_ticklabels([])\n",
    "    ax.set_ylabel(\"2nd\",fontsize=16)\n",
    "    ax.w_yaxis.set_ticklabels([])\n",
    "    ax.set_zlabel(\"3rd\",fontsize=16)\n",
    "    ax.w_zaxis.set_ticklabels([])\n",
    "    ax.view_init(v1,v2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Want to tweak the hyperparameters so that we get the lowest KL divergence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:31:37.686749Z",
     "start_time": "2017-11-15T20:30:24.825128Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[t-SNE] Computing 55 nearest neighbors...\n",
      "[t-SNE] Indexed 2467 samples in 0.006s...\n",
      "[t-SNE] Computed neighbors for 2467 samples in 0.288s...\n",
      "[t-SNE] Computed conditional probabilities for sample 1000 / 2467\n",
      "[t-SNE] Computed conditional probabilities for sample 2000 / 2467\n",
      "[t-SNE] Computed conditional probabilities for sample 2467 / 2467\n",
      "[t-SNE] Mean sigma: 0.114020\n",
      "[t-SNE] KL divergence after 250 iterations with early exaggeration: 1.455881\n",
      "[t-SNE] Error after 1000 iterations: 1.227577\n"
     ]
    }
   ],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "\n",
    "# a t-SNE model\n",
    "# angle value close to 1 means sacrificing accuracy for speed\n",
    "# pca initializtion usually leads to better results \n",
    "tsne_model = TSNE(n_components=3, verbose=1, random_state=44, angle=.50,\n",
    "                  perplexity=18,early_exaggeration=1,learning_rate=50.0)#, init='pca'\n",
    "\n",
    "# 20-D -> 3-D\n",
    "tsne_lda = tsne_model.fit_transform(lda_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:34:38.025062Z",
     "start_time": "2017-11-15T20:34:37.986536Z"
    }
   },
   "outputs": [],
   "source": [
    "tsne_data = pd.DataFrame(tsne_lda)\n",
    "tsne_data.to_csv(path + 'tsne_lda.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:34:48.004069Z",
     "start_time": "2017-11-15T20:34:45.500814Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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iIiJeS6FXREREREREvJZCr4iIiIiIiHgthV4RERERERHxWgq9IiIiIiIi4rUUekVERERE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ccfZwwgLtZGYWEhoqih1eElNycalTaBE1VNmM06dpSoGdhL4f1FtXTKieGSUWaCoVZ2bpA5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\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dTp+PYSNHUlJSwvz580FVMRhNRBQFJaZitdqw2R0oPT1s3bKFadOmoWkqknD855Ol3nrf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jUZwJz8yHOyZBQSJUhWBPESxeA5+1QYorhtGgs6gFilJheirM+RyKSlRq2gw4rToKEr5gjIwE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\nnj171viVA0CiTPJd2KYXAADgnPWb3/xGH//4x/WjH/1IV155pS6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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1fdefb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_tsne(tsne_lda,y, 0, 60)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Below are models that gave sub-par results compared to the LDA\n",
    "\n",
    "\n",
    "# NMF - must do count vectorizer with this one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:36:04.080276Z",
     "start_time": "2017-11-15T20:36:04.020812Z"
    }
   },
   "outputs": [],
   "source": [
    "def topic_mod_nmf(data, topics=5,iters=10,ngram_min=1, ngram_max=3, max_df=0.6, max_feats=5000):\n",
    "    \n",
    "    \"\"\" vectorizer - turn words into numbers for each document(rows)\n",
    "    then use Latent Dirichlet Allocation to get topics\"\"\"\n",
    "    \n",
    "    \n",
    "    vectorizer = CountVectorizer(ngram_range=(ngram_min,ngram_max), \n",
    "                             stop_words='english', \n",
    "                             max_df = max_df, \n",
    "                             max_features=max_feats)\n",
    "    \n",
    "    # call `fit` to build the vocabulary\n",
    "    vectorizer.fit(data)\n",
    "    \n",
    "    # finally, call `transform` to convert text to a bag of words\n",
    "\n",
    "    x = vectorizer.transform(data)\n",
    "    \n",
    "    mod = NMF(n_components=topics,\n",
    "                max_iter=iters,\n",
    "                random_state=42)\n",
    "    \n",
    "    topiced_dat = mod.fit_transform(x)\n",
    "    \n",
    "    \n",
    "    # to display a list of topic words and their scores \n",
    "    \n",
    "    def display_topics(model_, feature_names, no_top_words):\n",
    "        for ix, topic in enumerate(model_.components_):\n",
    "            print(\"Topic \", ix)\n",
    "            print(\" \".join([feature_names[i]\n",
    "                        for i in topic.argsort()[:-no_top_words - 1:-1]]))\n",
    "    \n",
    "    display_topics(mod, vectorizer.get_feature_names(),20)\n",
    "    \n",
    "    \n",
    "    return mod, vectorizer, x,  topiced_dat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:36:28.402524Z",
     "start_time": "2017-11-15T20:36:05.340125Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic  0\n",
      "love thought feel talk went word started came guy great wanted man person friend experience moment hand old god bit\n",
      "Topic  1\n",
      "woman men girl man sex gender boy talk young female violence male mother heart sexual women issue men woman black daughter\n",
      "Topic  2\n",
      "brain neuron memory body cell area sleep mind region light animal ability fly control change activity turn study sound behavior\n",
      "Topic  3\n",
      "money dollar percent company business problem million market 000 cost value 10 billion buy government pay job better product 20\n",
      "Topic  4\n",
      "planet earth mars star atmosphere surface solar sun ago space picture billion year ago ice place 000 million light away far\n",
      "Topic  5\n",
      "cell cancer body disease tumor drug blood stem stem cell organ dna tissue gene muscle patient molecule able vessel protein start\n",
      "Topic  6\n",
      "school kid student teacher education high class learning teach girl classroom community went high school learn old parent college started grade\n",
      "Topic  7\n",
      "city building place space street design community public neighborhood flag built new york architecture york live project map urban build home\n",
      "Topic  8\n",
      "computer technology idea design sort machine project information building using example able internet create book used working process bit material\n",
      "Topic  9\n",
      "universe space particle idea theory question science galaxy number matter dimension physic pattern energy dark force quantum charge big answer\n",
      "Topic  10\n",
      "human question problem animal technology specie social change example gene fact dna individual nature person ago body better history understand\n",
      "Topic  11\n",
      "data information number web using fact big question better decision phone algorithm government map looking bit computer important point start\n",
      "Topic  12\n",
      "patient health care doctor disease medical drug community problem medicine hospital heart health care hiv treatment cancer help percent study better\n",
      "Topic  13\n",
      "car ca em mile seat problem road drive crash driver driving able vehicle sort hour future electric cost oil maybe\n",
      "Topic  14\n",
      "game play video video game playing real player better sound hour online feel social music win experience problem try dynamic action\n",
      "Topic  15\n",
      "robot body build building leg idea second play able foot human lab video sort rule animal task motion control ant\n",
      "Topic  16\n",
      "story book film tell story told read telling live character came went movie picture mother idea narrative medium history moment africa\n",
      "Topic  17\n",
      "country china government africa global change india political united state war economic democracy growth states united states society chinese economy europe\n",
      "Topic  18\n",
      "child family parent baby mother old country home year old autism language young percent father school born month care refugee age\n",
      "Topic  19\n",
      "energy power nuclear oil solar technology fuel wind climate change electricity percent gas cost carbon coal big problem engine air\n",
      "Topic  20\n",
      "food eat plant ant farmer feed kid percent change colony bread eating waste diet bee fact le start grow meat\n",
      "Topic  21\n",
      "black hole black hole light image galaxy star telescope universe object picture center space mass sound sun white earth size big\n",
      "Topic  22\n",
      "water ocean fish animal sea specie area shark place coral forest tree plant 000 ice foot percent river surface whale\n"
     ]
    }
   ],
   "source": [
    "nmf_,vect_mod, vect_data, topic_data  = topic_mod_nmf(cleaned_talks,\n",
    "                                                             topics=23,\n",
    "                                                             iters=50,\n",
    "                                                             ngram_min=1, \n",
    "                                                             ngram_max=2, \n",
    "                                                             max_df=0.6, \n",
    "                                                             max_feats=2000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-02T21:27:03.988222Z",
     "start_time": "2017-11-02T21:27:03.984070Z"
    }
   },
   "source": [
    "# LSA count vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:39:46.660598Z",
     "start_time": "2017-11-15T20:39:46.594540Z"
    }
   },
   "outputs": [],
   "source": [
    "def topic_mod_lsa(data, topics=5,ngram_min=1, ngram_max=3, max_df=0.6, max_feats=5000):\n",
    "    \n",
    "    \"\"\" vectorizer - turn words into numbers for each document(rows)\n",
    "    then use Latent Dirichlet Allocation to get topics\"\"\"\n",
    "    \n",
    "    \n",
    "    vectorizer = CountVectorizer(ngram_range=(ngram_min,ngram_max), \n",
    "                             stop_words='english', \n",
    "                             max_df = max_df, \n",
    "                             max_features=max_feats)\n",
    "    \n",
    "    # call `fit` to build the vocabulary\n",
    "   \n",
    "    vect_data = vectorizer.fit_transform(data)\n",
    "    \n",
    "    #stdScale = Normalizer()\n",
    "\n",
    "    #vect_scale = stdScale.fit_transform(vect_data)\n",
    "    \n",
    "    mod = TruncatedSVD(n_components=topics,random_state=42)\n",
    "    \n",
    "    topiced_dat = mod.fit_transform(vect_data)\n",
    "    \n",
    "    \n",
    "    # to display a list of topic words and their scores \n",
    "    \n",
    "    def display_topics(model_, feature_names, no_top_words):\n",
    "        for ix, topic in enumerate(model_.components_):\n",
    "            print(\"Topic \", ix)\n",
    "            print(\" \".join([feature_names[i]\n",
    "                        for i in topic.argsort()[:-no_top_words - 1:-1]]))\n",
    "    \n",
    "    display_topics(mod, vectorizer.get_feature_names(),20)\n",
    "    \n",
    "    \n",
    "    return mod, vectorizer, vect_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T20:40:05.085892Z",
     "start_time": "2017-11-15T20:39:49.785849Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic  0\n",
      "human problem idea change country story percent woman question place child talk fact great start brain better technology thought big\n",
      "Topic  1\n",
      "brain cell human technology light body computer animal neuron planet cancer robot space earth data universe able information machine example\n",
      "Topic  2\n",
      "brain woman cell men cancer child body girl love patient story neuron disease human mother man feel baby thought word\n",
      "Topic  3\n",
      "country cell cancer percent brain disease health patient drug africa government data change problem woman dollar china global growth food\n",
      "Topic  4\n",
      "woman water planet cancer cell earth men ocean space universe light energy black mars star galaxy body specie place surface\n",
      "Topic  5\n",
      "cancer cell kid school patient disease city drug child design building tumor health started doctor blood went teacher student care\n",
      "Topic  6\n",
      "brain child city water school food kid family place area animal planet ocean neuron building earth percent fish country energy\n",
      "Topic  7\n",
      "city brain building woman car design street men space cell public place architecture project power flag built new york york community\n",
      "Topic  8\n",
      "story cell country cancer human war love feel god political china believe animal body book live global thought history word\n",
      "Topic  9\n",
      "universe black space country galaxy data hole black hole light star child image telescope cancer story city particle dark building theory\n",
      "Topic  10\n",
      "car data story brain ca love dollar money percent energy guy went oil hour thought mile em company patient started\n",
      "Topic  11\n",
      "data water city human information child ocean story animal health computer fish specie map place community sea family baby shark\n",
      "Topic  12\n",
      "game cancer play city health problem patient care doctor black experience better study feel social food space drug water disease\n",
      "Topic  13\n",
      "car human child city ca em question technology family problem love god space universe choice baby future seat gene energy\n",
      "Topic  14\n",
      "game child car story play video human city technology cell video game country data planet robot family playing real war player\n",
      "Topic  15\n",
      "robot patient child country health car care building body doctor story water family ca able idea went foot brain leg\n",
      "Topic  16\n",
      "story robot cancer food data kid school energy universe city book power brain student particle question human tumor teacher tell story\n",
      "Topic  17\n",
      "story technology idea design child building energy health care patient cost business company language dollar water project community product create\n",
      "Topic  18\n",
      "black money human dollar story health community robot black hole hole company care business africa patient animal 000 galaxy million market\n",
      "Topic  19\n",
      "power cell data water ca energy problem community nuclear change patient school government health climate solar global technology care war\n",
      "Topic  20\n",
      "cancer computer school planet mars earth human student brain machine ca teacher education learning 000 technology global ago went ocean\n",
      "Topic  21\n",
      "food black technology cancer hole black hole computer image power ca machine human chinese government internet em eat plant war picture\n",
      "Topic  22\n",
      "car water black student problem story ca hole sound black hole education teacher ocean learning country language fish school example em\n"
     ]
    }
   ],
   "source": [
    "lsa_,vect_mod,lsa_topic_data  = topic_mod_lsa(cleaned_talks,\n",
    "                                                             topics=23,\n",
    "                                                             ngram_min=1, \n",
    "                                                             ngram_max=2, \n",
    "                                                             max_df=0.6, \n",
    "                                                             max_feats=2000)"
   ]
  },
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     "end_time": "2017-11-02T21:27:16.137575Z",
     "start_time": "2017-11-02T21:27:16.134844Z"
    }
   },
   "source": [
    "# LSA Tfidf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
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    "ExecuteTime": {
     "end_time": "2017-11-15T21:09:19.299723Z",
     "start_time": "2017-11-15T21:09:19.229141Z"
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   "outputs": [],
   "source": [
    "def topic_mod_lsa_t(data, topics=5,ngram_min=1, ngram_max=3, max_df=0.6, max_feats=5000):\n",
    "    \n",
    "    \"\"\" vectorizer - turn words into numbers for each document(rows)\n",
    "    then use Latent Dirichlet Allocation to get topics\"\"\"\n",
    "    \n",
    "    \n",
    "    vectorizer = TfidfVectorizer(ngram_range=(ngram_min,ngram_max), \n",
    "                             stop_words='english', \n",
    "                             max_df = max_df, \n",
    "                             max_features=max_feats)\n",
    "    \n",
    "    vect_data = vectorizer.fit_transform(data)\n",
    "    \n",
    "    stdScale = Normalizer()\n",
    "\n",
    "    vect_scale = stdScale.fit_transform(vect_data)\n",
    "    mod = TruncatedSVD(n_components=topics,random_state=42)\n",
    "    \n",
    "    topiced_dat = mod.fit_transform(vect_scale)\n",
    "        \n",
    "    # to display a list of topic words and their scores \n",
    "    \n",
    "    def display_topics(model_, feature_names, no_top_words):\n",
    "        for ix, topic in enumerate(model_.components_):\n",
    "            print(\"Topic \", ix)\n",
    "            print(\" \".join([feature_names[i]\n",
    "                        for i in topic.argsort()[:-no_top_words - 1:-1]]))\n",
    "    \n",
    "    display_topics(mod, vectorizer.get_feature_names(),20)\n",
    "    \n",
    "    \n",
    "    return mod, vectorizer, vect_scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-11-15T21:09:37.112611Z",
     "start_time": "2017-11-15T21:09:20.424812Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic  0\n",
      "human problem idea change country story percent woman question place child talk fact great start brain better technology thought big\n",
      "Topic  1\n",
      "brain cell human technology light body computer animal neuron planet cancer robot space earth data universe able information machine example\n",
      "Topic  2\n",
      "brain woman cell men cancer child body girl love patient story neuron disease human mother man feel baby thought word\n",
      "Topic  3\n",
      "country cell cancer percent brain disease health patient drug africa government data change problem woman dollar china global growth food\n",
      "Topic  4\n",
      "woman water planet cancer cell earth men ocean space universe light energy black mars star galaxy body specie place surface\n",
      "Topic  5\n",
      "cancer cell kid school patient disease city drug child design building tumor health started doctor blood went teacher student care\n",
      "Topic  6\n",
      "brain child city water school food kid family place area animal planet ocean neuron building earth percent fish country energy\n",
      "Topic  7\n",
      "city brain building woman car design street men space cell public place architecture project power flag built new york york community\n",
      "Topic  8\n",
      "story cell country cancer human war love feel god political china believe animal body book live global thought history word\n",
      "Topic  9\n",
      "universe black space country galaxy data hole black hole light star child image telescope cancer story city particle dark building theory\n",
      "Topic  10\n",
      "car data story brain ca love dollar money percent energy guy went oil hour thought mile em company patient started\n",
      "Topic  11\n",
      "data water city human information child ocean story animal health computer fish specie map place community sea family baby shark\n",
      "Topic  12\n",
      "game cancer play city health problem patient care doctor black experience better study feel social food space drug water disease\n",
      "Topic  13\n",
      "car human child city ca em question technology family problem love god space universe choice baby future seat gene energy\n",
      "Topic  14\n",
      "game child car story play video human city technology cell video game country data planet robot family playing real war player\n",
      "Topic  15\n",
      "robot patient child country health car care building body doctor story water family ca able idea went foot brain leg\n",
      "Topic  16\n",
      "story robot cancer food data kid school energy universe city book power brain student particle question human tumor teacher tell story\n",
      "Topic  17\n",
      "story technology idea design child building energy health care patient cost business company language dollar water project community product create\n",
      "Topic  18\n",
      "black money human dollar story health community robot black hole hole company care business africa patient animal 000 galaxy million market\n",
      "Topic  19\n",
      "power cell data water ca energy problem community nuclear change patient school government health climate solar global technology care war\n",
      "Topic  20\n",
      "cancer computer school planet mars earth human student brain machine ca teacher education learning 000 technology global ago went ocean\n",
      "Topic  21\n",
      "food black technology cancer hole black hole computer image power ca machine human chinese government internet em eat plant war picture\n",
      "Topic  22\n",
      "car water black student problem story ca hole sound black hole education teacher ocean learning country language fish school example em\n"
     ]
    }
   ],
   "source": [
    "lsa_,vect_mod,lsa_topic_data  = topic_mod_lsa(cleaned_talks,\n",
    "                                                             topics=23,\n",
    "                                                             ngram_min=1, \n",
    "                                                             ngram_max=2, \n",
    "                                                             max_df=0.6, \n",
    "                                                             max_feats=2000)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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