NLP_W2VEC_Improved.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Best Practices for Preprocessing Natural Language Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, we improve the quality of our Project Gutenberg word vectors by adopting best-practices for preprocessing natural language data.\n",
    "\n",
    "**N.B.:** Some, all or none of these preprocessing steps may be helpful to a given downstream application. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk\n",
    "from nltk import word_tokenize, sent_tokenize\n",
    "import gensim\n",
    "from gensim.models.word2vec import Word2Vec\n",
    "from sklearn.manifold import TSNE\n",
    "import pandas as pd\n",
    "from bokeh.io import output_notebook, output_file\n",
    "from bokeh.plotting import show, figure\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\009\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "# new!\n",
    "import string\n",
    "# addressing the Stopwords\n",
    "from nltk.corpus import stopwords\n",
    "# Stemming tools\n",
    "from nltk.stem.porter import *\n",
    "# Bigrams tools\n",
    "from gensim.models.phrases import Phraser, Phrases\n",
    "# One hot encoding\n",
    "from keras.preprocessing.text import one_hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\009\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Loading the stopwords dictionnary\n",
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package gutenberg to\n",
      "[nltk_data]     C:\\Users\\009\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package gutenberg is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('gutenberg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import gutenberg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# the sentences tokinizer instance\n",
    "gberg_sents = gutenberg.sents()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Iteratively preprocess a sentence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### a tokenized sentence: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['She',\n",
       " 'was',\n",
       " 'the',\n",
       " 'youngest',\n",
       " 'of',\n",
       " 'the',\n",
       " 'two',\n",
       " 'daughters',\n",
       " 'of',\n",
       " 'a',\n",
       " 'most',\n",
       " 'affectionate',\n",
       " ',',\n",
       " 'indulgent',\n",
       " 'father',\n",
       " ';',\n",
       " 'and',\n",
       " 'had',\n",
       " ',',\n",
       " 'in',\n",
       " 'consequence',\n",
       " 'of',\n",
       " 'her',\n",
       " 'sister',\n",
       " \"'\",\n",
       " 's',\n",
       " 'marriage',\n",
       " ',',\n",
       " 'been',\n",
       " 'mistress',\n",
       " 'of',\n",
       " 'his',\n",
       " 'house',\n",
       " 'from',\n",
       " 'a',\n",
       " 'very',\n",
       " 'early',\n",
       " 'period',\n",
       " '.']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sentnece= List of words\n",
    "gberg_sents[4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### to lowercase: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['she',\n",
       " 'was',\n",
       " 'the',\n",
       " 'youngest',\n",
       " 'of',\n",
       " 'the',\n",
       " 'two',\n",
       " 'daughters',\n",
       " 'of',\n",
       " 'a',\n",
       " 'most',\n",
       " 'affectionate',\n",
       " ',',\n",
       " 'indulgent',\n",
       " 'father',\n",
       " ';',\n",
       " 'and',\n",
       " 'had',\n",
       " ',',\n",
       " 'in',\n",
       " 'consequence',\n",
       " 'of',\n",
       " 'her',\n",
       " 'sister',\n",
       " \"'\",\n",
       " 's',\n",
       " 'marriage',\n",
       " ',',\n",
       " 'been',\n",
       " 'mistress',\n",
       " 'of',\n",
       " 'his',\n",
       " 'house',\n",
       " 'from',\n",
       " 'a',\n",
       " 'very',\n",
       " 'early',\n",
       " 'period',\n",
       " '.']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Words with Lower or Upper case are typically indentical in meaning\n",
    "# iterating\n",
    "[w.lower() for w in gberg_sents[4]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### remove stopwords and punctuation: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# the removal deppends on the needs, the size of corpus, the goals, ......\n",
    "stpwrds_and_punctuation = stopwords.words('english') + list(string.punctuation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['i',\n",
       " 'me',\n",
       " 'my',\n",
       " 'myself',\n",
       " 'we',\n",
       " 'our',\n",
       " 'ours',\n",
       " 'ourselves',\n",
       " 'you',\n",
       " \"you're\",\n",
       " \"you've\",\n",
       " \"you'll\",\n",
       " \"you'd\",\n",
       " 'your',\n",
       " 'yours',\n",
       " 'yourself',\n",
       " 'yourselves',\n",
       " 'he',\n",
       " 'him',\n",
       " 'his',\n",
       " 'himself',\n",
       " 'she',\n",
       " \"she's\",\n",
       " 'her',\n",
       " 'hers',\n",
       " 'herself',\n",
       " 'it',\n",
       " \"it's\",\n",
       " 'its',\n",
       " 'itself',\n",
       " 'they',\n",
       " 'them',\n",
       " 'their',\n",
       " 'theirs',\n",
       " 'themselves',\n",
       " 'what',\n",
       " 'which',\n",
       " 'who',\n",
       " 'whom',\n",
       " 'this',\n",
       " 'that',\n",
       " \"that'll\",\n",
       " 'these',\n",
       " 'those',\n",
       " 'am',\n",
       " 'is',\n",
       " 'are',\n",
       " 'was',\n",
       " 'were',\n",
       " 'be',\n",
       " 'been',\n",
       " 'being',\n",
       " 'have',\n",
       " 'has',\n",
       " 'had',\n",
       " 'having',\n",
       " 'do',\n",
       " 'does',\n",
       " 'did',\n",
       " 'doing',\n",
       " 'a',\n",
       " 'an',\n",
       " 'the',\n",
       " 'and',\n",
       " 'but',\n",
       " 'if',\n",
       " 'or',\n",
       " 'because',\n",
       " 'as',\n",
       " 'until',\n",
       " 'while',\n",
       " 'of',\n",
       " 'at',\n",
       " 'by',\n",
       " 'for',\n",
       " 'with',\n",
       " 'about',\n",
       " 'against',\n",
       " 'between',\n",
       " 'into',\n",
       " 'through',\n",
       " 'during',\n",
       " 'before',\n",
       " 'after',\n",
       " 'above',\n",
       " 'below',\n",
       " 'to',\n",
       " 'from',\n",
       " 'up',\n",
       " 'down',\n",
       " 'in',\n",
       " 'out',\n",
       " 'on',\n",
       " 'off',\n",
       " 'over',\n",
       " 'under',\n",
       " 'again',\n",
       " 'further',\n",
       " 'then',\n",
       " 'once',\n",
       " 'here',\n",
       " 'there',\n",
       " 'when',\n",
       " 'where',\n",
       " 'why',\n",
       " 'how',\n",
       " 'all',\n",
       " 'any',\n",
       " 'both',\n",
       " 'each',\n",
       " 'few',\n",
       " 'more',\n",
       " 'most',\n",
       " 'other',\n",
       " 'some',\n",
       " 'such',\n",
       " 'no',\n",
       " 'nor',\n",
       " 'not',\n",
       " 'only',\n",
       " 'own',\n",
       " 'same',\n",
       " 'so',\n",
       " 'than',\n",
       " 'too',\n",
       " 'very',\n",
       " 's',\n",
       " 't',\n",
       " 'can',\n",
       " 'will',\n",
       " 'just',\n",
       " 'don',\n",
       " \"don't\",\n",
       " 'should',\n",
       " \"should've\",\n",
       " 'now',\n",
       " 'd',\n",
       " 'll',\n",
       " 'm',\n",
       " 'o',\n",
       " 're',\n",
       " 've',\n",
       " 'y',\n",
       " 'ain',\n",
       " 'aren',\n",
       " \"aren't\",\n",
       " 'couldn',\n",
       " \"couldn't\",\n",
       " 'didn',\n",
       " \"didn't\",\n",
       " 'doesn',\n",
       " \"doesn't\",\n",
       " 'hadn',\n",
       " \"hadn't\",\n",
       " 'hasn',\n",
       " \"hasn't\",\n",
       " 'haven',\n",
       " \"haven't\",\n",
       " 'isn',\n",
       " \"isn't\",\n",
       " 'ma',\n",
       " 'mightn',\n",
       " \"mightn't\",\n",
       " 'mustn',\n",
       " \"mustn't\",\n",
       " 'needn',\n",
       " \"needn't\",\n",
       " 'shan',\n",
       " \"shan't\",\n",
       " 'shouldn',\n",
       " \"shouldn't\",\n",
       " 'wasn',\n",
       " \"wasn't\",\n",
       " 'weren',\n",
       " \"weren't\",\n",
       " 'won',\n",
       " \"won't\",\n",
       " 'wouldn',\n",
       " \"wouldn't\",\n",
       " '!',\n",
       " '\"',\n",
       " '#',\n",
       " '$',\n",
       " '%',\n",
       " '&',\n",
       " \"'\",\n",
       " '(',\n",
       " ')',\n",
       " '*',\n",
       " '+',\n",
       " ',',\n",
       " '-',\n",
       " '.',\n",
       " '/',\n",
       " ':',\n",
       " ';',\n",
       " '<',\n",
       " '=',\n",
       " '>',\n",
       " '?',\n",
       " '@',\n",
       " '[',\n",
       " '\\\\',\n",
       " ']',\n",
       " '^',\n",
       " '_',\n",
       " '`',\n",
       " '{',\n",
       " '|',\n",
       " '}',\n",
       " '~']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stpwrds_and_punctuation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['she',\n",
       " 'youngest',\n",
       " 'two',\n",
       " 'daughters',\n",
       " 'affectionate',\n",
       " 'indulgent',\n",
       " 'father',\n",
       " 'consequence',\n",
       " 'sister',\n",
       " 'marriage',\n",
       " 'mistress',\n",
       " 'house',\n",
       " 'early',\n",
       " 'period']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[w.lower() for w in gberg_sents[4] if w not in stpwrds_and_punctuation]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### stem words: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# truncat to the meaninufull part\n",
    "# PorterStemmer is popular stemmer\n",
    "#In case of larger corpus you may want to avoid stemming in order to keep the variations\n",
    "stemmer = PorterStemmer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['she',\n",
       " 'youngest',\n",
       " 'two',\n",
       " 'daughter',\n",
       " 'affection',\n",
       " 'indulg',\n",
       " 'father',\n",
       " 'consequ',\n",
       " 'sister',\n",
       " 'marriag',\n",
       " 'mistress',\n",
       " 'hous',\n",
       " 'earli',\n",
       " 'period']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[stemmer.stem(w.lower()) for w in gberg_sents[4] if w not in stpwrds_and_punctuation]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### handle bigram collocations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#biagrams= words occuring to much to guether=> one concept, ex: New York, Thank YOu\n",
    "phrases = Phrases(gberg_sents) # train detector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "bigram = Phraser(phrases) # create a more efficient Phraser object for transforming sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(b'la', b'!'): (7, 14.377704155768672),\n",
       " (b'fourth', b'year'): (13, 70.99107475964988),\n",
       " (b'short', b'pause'): (11, 86.61965123608095),\n",
       " (b'themselves', b'together'): (44, 32.443044734519944),\n",
       " (b'Dough', b'-'): (16, 48.041179378531076),\n",
       " (b'-', b'mast'): (30, 12.845235127949485),\n",
       " (b'am', b'persuaded'): (12, 14.509626277861573),\n",
       " (b'Wee', b\"'\"): (19, 18.940835962214123),\n",
       " (b\"'\", b'gainst'): (8, 11.668907869578344),\n",
       " (b'laid', b'wait'): (9, 23.354708359296815),\n",
       " (b'lodged', b'there'): (10, 14.090248348143085),\n",
       " (b'pivot', b'-'): (7, 19.965165456012915),\n",
       " (b'Guernsey', b'-'): (11, 34.9390395480226),\n",
       " (b'didn', b\"'\"): (160, 30.144678663077386),\n",
       " (b'most', b'amiable'): (8, 17.207358697063572),\n",
       " (b'over', b'against'): (103, 10.771922203608993),\n",
       " (b'spread', b'abroad'): (14, 194.30906996229578),\n",
       " (b'Project', b'Gutenberg'): (20, 17839.067307692305),\n",
       " (b'Colonel', b'Wallis'): (23, 967.3744677153037),\n",
       " (b'molten', b'images'): (10, 966.2828125000001),\n",
       " (b'sojourneth', b'among'): (8, 92.57799401197605),\n",
       " (b'any', b'thing'): (383, 35.72804044966351),\n",
       " (b'broken', b'glass'): (10, 52.75909432159432),\n",
       " (b'So', b'Joab'): (9, 11.749235299705518),\n",
       " (b'laugh', b'at'): (34, 11.791126449054302),\n",
       " (b'at', b'length'): (74, 17.88998495718584),\n",
       " (b'Lady', b'Elliot'): (12, 34.95596737726098),\n",
       " (b'-', b'hole'): (32, 14.739907309322033),\n",
       " (b'five', b'rams'): (12, 99.68101225016119),\n",
       " (b'ran', b'away'): (24, 15.685508857974716),\n",
       " (b'general', b'character'): (6, 10.833526031812768),\n",
       " (b'very', b'bad'): (36, 15.601593602802112),\n",
       " (b'eight', b'o'): (9, 65.15181205225453),\n",
       " (b'young', b'bullock'): (30, 123.83279935923107),\n",
       " (b'anything', b'else'): (30, 74.81068120893052),\n",
       " (b'turn', b'away'): (49, 25.69282323847976),\n",
       " (b'considerable', b'time'): (10, 11.974228401037836),\n",
       " (b'gather', b'themselves'): (11, 24.904196198453608),\n",
       " (b'Harley', b'Street'): (16, 5001.93455882353),\n",
       " (b'make', b'mention'): (12, 20.60402566372524),\n",
       " (b'plant', b'vineyards'): (8, 458.99628896585847),\n",
       " (b'Shall', b'we'): (25, 13.344431737263449),\n",
       " (b'mine', b'affliction'): (8, 19.205621118012424),\n",
       " (b'most', b'charming'): (7, 10.48020200479592),\n",
       " (b'fade', b'away'): (8, 54.923561976375865),\n",
       " (b'into', b'captivity'): (41, 41.84080196657721),\n",
       " (b'twenty', b'cubits'): (31, 164.46189409514457),\n",
       " (b'thou', b'wentest'): (9, 27.819208277103016),\n",
       " (b'watery', b'world'): (6, 12.651820785597382),\n",
       " (b'been', b'able'): (40, 15.91768079235648),\n",
       " (b'arose', b'early'): (9, 42.123901641577554),\n",
       " (b'can', b'tell'): (51, 12.430822730105128),\n",
       " (b'shan', b\"'\"): (18, 22.473452193261995),\n",
       " (b'sayest', b'thou'): (14, 20.86440620782726),\n",
       " (b'O', b'soul'): (38, 11.384483260683051),\n",
       " (b'Ile', b'haue'): (8, 43.10955943860954),\n",
       " (b'be', b'satisfied'): (66, 12.272908603731745),\n",
       " (b'diamond', b'cross'): (9, 529.1302673796791),\n",
       " (b'proclamation', b'throughout'): (6, 271.23728070175434),\n",
       " (b'stiffnecked', b'people'): (6, 24.77946067235645),\n",
       " (b'fine', b'gold'): (17, 27.12303413289865),\n",
       " (b'poor', b'Isabella'): (10, 41.30241100647832),\n",
       " (b'while', b'ago'): (10, 15.477085481465169),\n",
       " (b'depends', b'upon'): (8, 18.878472434214544),\n",
       " (b'turned', b'away'): (50, 19.3446247292484),\n",
       " (b'length', b'thereof'): (25, 48.762911797637635),\n",
       " (b'-', b'sweeper'): (22, 51.64901498403341),\n",
       " (b'third', b'part'): (39, 80.67867146551659),\n",
       " (b'time', b'appointed'): (13, 11.589870452362547),\n",
       " (b'Solomon', b'built'): (7, 16.4661980456373),\n",
       " (b'My', b'dearest'): (7, 26.665272507761294),\n",
       " (b'\"', b'Perhaps'): (40, 10.879118421244423),\n",
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       " (b'OCTAVO', b'),'): (6, 409.0085978835979),\n",
       " (b'almonds', b'gratis'): (6, 4068.5592105263154),\n",
       " (b'Miss', b'Marianne'): (31, 22.57441903563847),\n",
       " (b'almost', b'fancy'): (9, 16.725382014874913),\n",
       " (b'good', b'fortune'): (18, 19.83585738958796),\n",
       " (b'shalt', b'surely'): (28, 31.292133892133894),\n",
       " (b'every', b'respect'): (14, 12.224980231945178),\n",
       " (b'her', b'mistress'): (30, 10.11840289117327),\n",
       " (b'very', b'pretty'): (39, 20.068178868120455),\n",
       " (b'whole', b'congregation'): (17, 21.199129302070478),\n",
       " (b'Ludgate', b'Hill'): (11, 5096.876373626374),\n",
       " (b'pre', b'-'): (17, 49.325702891326024),\n",
       " (b'The', b'Second'): (9, 16.39939008220631),\n",
       " (b'your', b'Lordship'): (6, 18.24573670856199),\n",
       " (b'person', b'who'): (30, 10.409305441471528),\n",
       " (b'King', b'Solomon'): (8, 11.444822800037015),\n",
       " (b'two', b'years'): (53, 12.9458705561574),\n",
       " (b'deep', b'sigh'): (7, 47.7618937287612),\n",
       " (b'twenty', b'thousand'): (48, 77.04104378157882),\n",
       " (b'Nobody', b'could'): (9, 15.935399917542776),\n",
       " (b',\"', b'added'): (51, 22.00020571516956),\n",
       " (b'said', b'Ben'): (23, 13.917081952866162),\n",
       " (b'ain', b\"'\"): (26, 24.20217928505138),\n",
       " (b'by', b'accident'): (20, 18.377820174500155),\n",
       " (b'their', b'backs'): (23, 40.028400673158515),\n",
       " (b'tenth', b'deal'): (9, 82.53867200533868),\n",
       " (b'turn', b'back'): (15, 10.596023199431151),\n",
       " (b'west', b'side'): (28, 97.06480912800775),\n",
       " (b'good', b'news'): (18, 24.794821736984947),\n",
       " (b'Won', b\"'\"): (9, 11.315304600803241),\n",
       " (b'very', b'early'): (24, 11.01214147275924),\n",
       " (b'So', b'spake'): (28, 14.978478487965562),\n",
       " (b'prevail', b'against'): (15, 55.9682338567356),\n",
       " (b'own', b'feelings'): (16, 10.723815634320593),\n",
       " (b'll', b'pay'): (9, 17.618831908831908),\n",
       " (b'118', b':'): (29, 10.099513740604497),\n",
       " (b'everlasting', b'life'): (11, 22.981085098476402),\n",
       " (b'months', b'ago'): (7, 33.90373070913626),\n",
       " (b'an', b'unnatural'): (10, 19.2271172739709),\n",
       " (b'Holy', b'One'): (51, 391.83699724517913),\n",
       " (b'thine', b'ears'): (12, 16.90783573928259),\n",
       " (b'two', b'ends'): (14, 24.05932928727046),\n",
       " (b'.--', b'She'): (78, 30.440671188909267),\n",
       " (b'said', b'Piedro'): (32, 11.021291608636247),\n",
       " (b'Hezekiah', b'king'): (15, 18.335537239089184),\n",
       " (b'mount', b'Sinai'): (19, 706.9977135391148),\n",
       " (b'sperm', b'whale'): (55, 321.49147431898524),\n",
       " (b'!--', b'Such'): (10, 19.885431136492258),\n",
       " (b'Jesus', b'Christ'): (199, 205.6780877340959),\n",
       " (b'white', b'hair'): (20, 39.70345403184386),\n",
       " (b'drink', b'offering'): (30, 44.6133258307002),\n",
       " (b'wilt', b'thou'): (110, 43.640690275335906),\n",
       " (b'twenty', b'minutes'): (7, 11.181099087860133),\n",
       " (b'hath', b'done'): (81, 14.495192838510585),\n",
       " (b'Christ', b'Child'): (9, 219.18164097111466),\n",
       " (b'Ten', b'thousand'): (6, 37.380379593810446),\n",
       " (b'never', b'forget'): (18, 21.690200998246326),\n",
       " (b'king', b'Hezekiah'): (11, 11.00132234345351),\n",
       " (b'their', b'armies'): (20, 13.867517087142932),\n",
       " (b'my', b'fury'): (34, 16.714704182821354),\n",
       " (b'new', b'ones'): (7, 11.310855052583447),\n",
       " ...}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigram.phrasegrams # output count and score of each bigram (ocuurence of togetherness and  score= \"togetherness/a part\" in the whole corpus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Jon', 'lives', 'in', 'New', 'York', 'City']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Example of applcation of bigrams\n",
    "\"Jon lives in New York City\".split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Jon', 'lives', 'in', 'New_York', 'City']"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigram[\"Jon lives in New York City\".split()]\n",
    "# New, York = New_York \n",
    "# Trigram are to explore (New York City)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Preprocess the corpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creat list of all lower case sentneces, including the Stopwords: for training purposes some Stopwords might be paired with meaninful ones\n",
    "lower_sents = []\n",
    "for s in gberg_sents:\n",
    "    lower_sents.append([w.lower() for w in s if w not in list(string.punctuation)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['emma', 'by', 'jane', 'austen', '1816'],\n",
       " ['volume', 'i'],\n",
       " ['chapter', 'i'],\n",
       " ['emma',\n",
       "  'woodhouse',\n",
       "  'handsome',\n",
       "  'clever',\n",
       "  'and',\n",
       "  'rich',\n",
       "  'with',\n",
       "  'a',\n",
       "  'comfortable',\n",
       "  'home',\n",
       "  'and',\n",
       "  'happy',\n",
       "  'disposition',\n",
       "  'seemed',\n",
       "  'to',\n",
       "  'unite',\n",
       "  'some',\n",
       "  'of',\n",
       "  'the',\n",
       "  'best',\n",
       "  'blessings',\n",
       "  'of',\n",
       "  'existence',\n",
       "  'and',\n",
       "  'had',\n",
       "  'lived',\n",
       "  'nearly',\n",
       "  'twenty',\n",
       "  'one',\n",
       "  'years',\n",
       "  'in',\n",
       "  'the',\n",
       "  'world',\n",
       "  'with',\n",
       "  'very',\n",
       "  'little',\n",
       "  'to',\n",
       "  'distress',\n",
       "  'or',\n",
       "  'vex',\n",
       "  'her'],\n",
       " ['she',\n",
       "  'was',\n",
       "  'the',\n",
       "  'youngest',\n",
       "  'of',\n",
       "  'the',\n",
       "  'two',\n",
       "  'daughters',\n",
       "  'of',\n",
       "  'a',\n",
       "  'most',\n",
       "  'affectionate',\n",
       "  'indulgent',\n",
       "  'father',\n",
       "  'and',\n",
       "  'had',\n",
       "  'in',\n",
       "  'consequence',\n",
       "  'of',\n",
       "  'her',\n",
       "  'sister',\n",
       "  's',\n",
       "  'marriage',\n",
       "  'been',\n",
       "  'mistress',\n",
       "  'of',\n",
       "  'his',\n",
       "  'house',\n",
       "  'from',\n",
       "  'a',\n",
       "  'very',\n",
       "  'early',\n",
       "  'period']]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lower_sents[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "lower_bigram = Phraser(Phrases(lower_sents))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(b'fourth', b'year'): (13, 61.9554816),\n",
       " (b'short', b'pause'): (11, 83.26155963302752),\n",
       " (b'themselves', b'together'): (44, 31.46210359577169),\n",
       " (b'am', b'persuaded'): (12, 13.9008842237933),\n",
       " (b'zedekiah', b'king'): (15, 30.98956145832266),\n",
       " (b'king', b'post'): (10, 10.21996175753194),\n",
       " (b'laid', b'wait'): (9, 21.714408764232456),\n",
       " (b'appear', b'd'): (16, 11.653197226502312),\n",
       " (b'most', b'amiable'): (9, 20.908663648615956),\n",
       " (b'over', b'against'): (106, 10.306348762219812),\n",
       " (b'miss', b'fairfax'): (125, 253.16112835175565),\n",
       " (b'saffron', b'park'): (9, 2168.5806451612902),\n",
       " (b'sojourneth', b'among'): (8, 86.1258362989324),\n",
       " (b'any', b'thing'): (384, 34.60353767883287),\n",
       " (b'broken', b'glass'): (10, 42.57025456285268),\n",
       " (b'laugh', b'at'): (34, 10.684790511927686),\n",
       " (b'at', b'length'): (101, 22.85664635341284),\n",
       " (b'tell', b'vs'): (9, 11.407556846034918),\n",
       " (b'good', b'breeding'): (8, 36.8301848507599),\n",
       " (b'walking', b'stick'): (10, 115.37643020594965),\n",
       " (b'five', b'rams'): (12, 94.66969175402912),\n",
       " (b'ran', b'away'): (24, 14.924370991613223),\n",
       " (b'their', b'idols'): (23, 13.038870171758603),\n",
       " (b'yes', b'ma'): (9, 15.105834768931166),\n",
       " (b'young', b'bullock'): (30, 114.57935642214345),\n",
       " (b'anything', b'else'): (31, 72.72513938587002),\n",
       " (b'turn', b'away'): (53, 24.3249510219842),\n",
       " (b'sennacherib', b'king'): (9, 59.118548012800154),\n",
       " (b'nay', b'nay'): (7, 32.48591908507611),\n",
       " (b'now', b'therefore'): (145, 11.124642048311067),\n",
       " (b'considerable', b'time'): (10, 11.403428752365373),\n",
       " (b'gather', b'themselves'): (11, 21.403999905662605),\n",
       " (b'plant', b'vineyards'): (8, 438.85444874274657),\n",
       " (b'thus', b'far'): (32, 12.641590235839274),\n",
       " (b'cumberland', b'vane'): (12, 7843.033333333333),\n",
       " (b'fifteen', b'years'): (10, 60.35011071877431),\n",
       " (b'offering', b'7'): (36, 10.326767812466965),\n",
       " (b'fade', b'away'): (8, 52.6742505586349),\n",
       " (b'into', b'captivity'): (41, 39.96305551580268),\n",
       " (b'twenty', b'cubits'): (31, 156.47015994270708),\n",
       " (b'thou', b'wentest'): (11, 35.806125166444744),\n",
       " (b'on', b'tuesday'): (9, 11.26168450442066),\n",
       " (b'watery', b'world'): (6, 11.483989750403342),\n",
       " (b'been', b'able'): (40, 15.563975922210217),\n",
       " (b'arose', b'early'): (9, 39.7760830977582),\n",
       " (b'can', b'tell'): (52, 10.59868410018371),\n",
       " (b'sayest', b'thou'): (15, 19.45985063393736),\n",
       " (b'months', b'ago'): (7, 32.82608577706644),\n",
       " (b'be', b'satisfied'): (68, 11.946063802781145),\n",
       " (b'whate', b'er'): (6, 800.3095238095237),\n",
       " (b'mrs', b'theresa'): (67, 301.49822776264074),\n",
       " (b'proclamation', b'throughout'): (6, 261.24093264248705),\n",
       " (b'stiffnecked', b'people'): (6, 23.992148465381867),\n",
       " (b'fine', b'gold'): (17, 25.706201006946657),\n",
       " (b'while', b'ago'): (10, 12.961199989717313),\n",
       " (b'depends', b'upon'): (8, 17.98662227242999),\n",
       " (b'lodged', b'there'): (10, 11.027083181453671),\n",
       " (b'turned', b'away'): (50, 18.47583754119931),\n",
       " (b'c', b'.,'): (6, 484.8028846153846),\n",
       " (b'third', b'part'): (39, 74.5758658942438),\n",
       " (b'time', b'appointed'): (13, 10.902790416895671),\n",
       " (b'gather', b'yourselves'): (7, 24.23917311005168),\n",
       " (b'putteth', b'forth'): (6, 16.87682008368201),\n",
       " (b'hath', b'taken'): (36, 11.471066464841062),\n",
       " (b'fairy', b'tale'): (6, 242.59582999198076),\n",
       " (b'll', b'find'): (15, 12.291742850873986),\n",
       " (b'thou', b'mightest'): (18, 55.41424132902162),\n",
       " (b'some', b'weeks'): (10, 11.200682740440154),\n",
       " (b'greywood', b'usher'): (6, 2725.3783783783783),\n",
       " (b'sin', b'offering'): (118, 170.76244211662095),\n",
       " (b'stronger', b'than'): (29, 55.48225584594223),\n",
       " (b'meat', b'offering'): (122, 273.86742443293264),\n",
       " (b'compared', b'with'): (28, 15.206045360968936),\n",
       " (b'an', b'ass'): (27, 25.403208907227196),\n",
       " (b'wilson', b'seymour'): (10, 8024.323607427056),\n",
       " (b'five', b'minutes'): (37, 138.27274480256534),\n",
       " (b'good', b'opinion'): (19, 13.341832563897801),\n",
       " (b'draw', b'water'): (10, 20.48240981475463),\n",
       " (b'swear', b'by'): (30, 13.564908813063195),\n",
       " (b'golden', b'spoon'): (10, 833.6098098649766),\n",
       " (b'side', b'chambers'): (7, 13.837255574614066),\n",
       " (b'yes', b'yes'): (31, 34.423873463814296),\n",
       " (b'take', b'heed'): (58, 176.09156356567436),\n",
       " (b'at', b'barton'): (35, 22.230656741205607),\n",
       " (b'mr', b'somerville'): (32, 182.4671387722277),\n",
       " (b'infinitely', b'superior'): (7, 270.2854590127318),\n",
       " (b'four', b'beasts'): (11, 28.56359172882636),\n",
       " (b'four', b'cubits'): (13, 36.475572536341645),\n",
       " (b'dwelling', b'place'): (21, 78.15462119744237),\n",
       " (b'thou', b'lovest'): (9, 25.57580369031767),\n",
       " (b'be', b'saved'): (61, 12.820166032252938),\n",
       " (b'joash', b'king'): (9, 15.684512738089836),\n",
       " (b'miss', b'elliot'): (48, 75.64904190049722),\n",
       " (b'time', b'past'): (23, 12.30314881906576),\n",
       " (b'ha', b'ha'): (16, 235.80548469387756),\n",
       " (b'will', b'bring'): (145, 11.542472822887643),\n",
       " (b'miss', b'carteret'): (12, 296.58529411764704),\n",
       " (b'his', b'hammock'): (18, 11.136656727068837),\n",
       " (b'an', b'homer'): (9, 35.300563026926106),\n",
       " (b'wander', b'd'): (11, 32.52055039954133),\n",
       " (b'lady', b'dalrymple'): (25, 567.8937488267317),\n",
       " (b'sabbath', b'day'): (55, 63.16333433553818),\n",
       " (b'pleasing', b'young'): (8, 22.392079940784605),\n",
       " (b'two', b'sides'): (13, 12.986418686513664),\n",
       " (b'prince', b'cherry'): (14, 1008.39),\n",
       " (b'each', b'other'): (239, 71.31277029783762),\n",
       " (b'pretty', b'well'): (22, 13.991375757171793),\n",
       " (b'mount', b'seir'): (16, 514.0078776645042),\n",
       " (b'turned', b'back'): (42, 27.419992871324965),\n",
       " (b'wait', b'till'): (20, 30.635873858181593),\n",
       " (b'went', b'forth'): (84, 17.337695534601803),\n",
       " (b'whence', b'comest'): (8, 327.5175027066041),\n",
       " (b'mrs', b'montague'): (18, 132.3613691437803),\n",
       " (b'provoke', b'me'): (18, 15.67267568251514),\n",
       " (b'two', b'rows'): (7, 10.194338668913227),\n",
       " (b'respectable', b'young'): (8, 26.124093264248707),\n",
       " (b'instances', b'where'): (7, 14.841632733159987),\n",
       " (b'pendragon', b'park'): (9, 839.4505723204994),\n",
       " (b'believeth', b'on'): (15, 15.641228478362029),\n",
       " (b'false', b'witnesses'): (6, 71.72048364153628),\n",
       " (b'draw', b'nigh'): (9, 70.37324803722012),\n",
       " (b'an', b'hundredfold'): (7, 35.300563026926106),\n",
       " (b'most', b'favourable'): (6, 11.684253215403034),\n",
       " (b'sand', b'hills'): (9, 142.62942008486561),\n",
       " (b'dealt', b'treacherously'): (9, 1489.3144615384615),\n",
       " (b'an', b'egg'): (7, 16.473596079232184),\n",
       " (b'an', b'heave'): (11, 14.25599660702785),\n",
       " (b'thou', b'makest'): (17, 37.040819137701455),\n",
       " (b'thrown', b'down'): (19, 23.474847020219936),\n",
       " (b'most', b'noble'): (12, 18.295080692538964),\n",
       " (b'from', b'thence'): (103, 27.334646896223614),\n",
       " (b'turning', b'round'): (15, 21.605116375400833),\n",
       " (b'ox', b'or'): (14, 11.180752528104307),\n",
       " (b'assembled', b'together'): (6, 10.288993945990068),\n",
       " (b'fine', b'flour'): (36, 667.095390524968),\n",
       " (b'mr', b'hopkins'): (17, 171.2037351443124),\n",
       " (b'west', b'side'): (28, 66.67392700058453),\n",
       " (b'at', b'delaford'): (11, 13.19018966644866),\n",
       " (b'besought', b'him'): (26, 19.529225330464186),\n",
       " (b'larger', b'than'): (11, 18.09203994976377),\n",
       " (b'moby', b'dick'): (84, 6252.967817896389),\n",
       " (b'few', b'inches'): (7, 55.22398685651698),\n",
       " (b't', b'talk'): (19, 10.789205796038152),\n",
       " (b'few', b'minutes'): (86, 306.2525246213068),\n",
       " (b'heavenly', b'father'): (10, 13.448606980435041),\n",
       " (b'drew', b'nigh'): (23, 250.30135601011264),\n",
       " (b'mrs', b'talb'): (15, 59.23865472169187),\n",
       " (b'sea', b'shore'): (14, 26.870495928941523),\n",
       " (b'at', b'norland'): (19, 17.421005219837852),\n",
       " (b'eat', b'unleavened'): (9, 46.73069570758269),\n",
       " (b'moses', b'saying'): (81, 30.481433753340973),\n",
       " (b'last', b'night'): (70, 23.230537949447992),\n",
       " (b'quicken', b'me'): (9, 15.974073291794276),\n",
       " (b'need', b'not'): (108, 12.811033130226706),\n",
       " (b'whoring', b'after'): (12, 81.86091191990258),\n",
       " (b'hiding', b'place'): (12, 74.08406801007557),\n",
       " (b'fourteen', b'lambs'): (8, 513.6112054329371),\n",
       " (b'sixty', b'five'): (6, 24.217828123123724),\n",
       " (b'mrs', b'musgrove'): (66, 152.88129737790481),\n",
       " (b'an', b'elderly'): (7, 12.355197059424137),\n",
       " (b'little', b'joe'): (111, 178.84191241059102),\n",
       " (b'dwell', b'among'): (15, 10.659138155808463),\n",
       " (b'pine', b'tree'): (9, 88.53616242912017),\n",
       " (b'enter', b'lucius'): (7, 89.29073199527744),\n",
       " (b'mr', b'martin'): (37, 92.3345987295168),\n",
       " (b'thousand', b'miles'): (14, 56.34629552980133),\n",
       " (b'holy', b'garments'): (11, 44.45728421671402),\n",
       " (b'young', b'pigeons'): (10, 217.70077720207254),\n",
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       " (b'leaned', b'forward'): (6, 43.37161290322581),\n",
       " (b'be', b'exalted'): (28, 10.794121936084395),\n",
       " (b'new', b'orleans'): (8, 254.96586599241465),\n",
       " (b'every', b'thing'): (258, 26.813583851480026),\n",
       " (b'blows', b'!--'): (6, 16.26435483870968),\n",
       " (b'dear', b'jane'): (15, 27.27885083590326),\n",
       " (b'all', b'probability'): (16, 12.433560319461959),\n",
       " (b'trespass', b'against'): (11, 18.008840206569136),\n",
       " (b'mr', b'wingfield'): (9, 102.72224108658745),\n",
       " (b'milk', b'white'): (7, 13.834408012072988),\n",
       " (b'mr', b'elton'): (214, 139.40875576036868),\n",
       " (b'by', b'reason'): (70, 10.359210631680098),\n",
       " (b'captains', b'over'): (17, 18.543824563823186),\n",
       " (b'goings', b'out'): (15, 37.44300319330643),\n",
       " (b's', b'boy'): (98, 10.04584819936527),\n",
       " (b'hath', b'devoured'): (12, 28.317039414301473),\n",
       " (b'their', b'arrival'): (15, 11.398358728579826),\n",
       " (b'everlasting', b'covenant'): (15, 171.23280692817116),\n",
       " (b'high', b'priest'): (84, 68.55466854077622),\n",
       " (b'talk', b'about'): (37, 21.439425951764),\n",
       " (b'en', b'masse'): (9, 9167.181818181818),\n",
       " (b'five', b'couple'): (8, 45.27680909975305),\n",
       " (b'few', b'moments'): (43, 372.31655654877574),\n",
       " (b'old', b'manxman'): (6, 24.228495915425277),\n",
       " (b'thine', b'inheritance'): (17, 28.654905396765255),\n",
       " (b'slept', b'with'): (37, 12.645107186732789),\n",
       " (b'bring', b'forth'): (95, 45.75041588949942),\n",
       " (b'nine', b'hundred'): (19, 95.32812640677051),\n",
       " (b'five', b'talents'): (7, 28.530592035460828),\n",
       " (b'chapter', b'iii'): (10, 294.85087719298247),\n",
       " (b'next', b'week'): (13, 53.87957922858575),\n",
       " (b'fourth', b'part'): (15, 56.677658079625296),\n",
       " (b'commune', b'with'): (9, 12.501412786883552),\n",
       " (b'committeth', b'adultery'): (10, 3790.93984962406),\n",
       " (b'living', b'creature'): (16, 82.51963993453354),\n",
       " (b'lord', b'spake'): (144, 14.924423961498055),\n",
       " (b'dearly', b'beloved'): (10, 859.6675191815857),\n",
       " (b'rising', b'sun'): (7, 11.4529037631559),\n",
       " (b'bending', b'over'): (7, 13.907868422867388),\n",
       " (b'thy', b'loins'): (14, 13.119132860798041),\n",
       " (b'may', b'guess'): (11, 12.384068773773176),\n",
       " (b'conspired', b'against'): (18, 147.59419038862097),\n",
       " (b'twenty', b'miles'): (8, 30.043399099576273),\n",
       " (b'creepeth', b'upon'): (11, 56.529384284779965),\n",
       " (b'utterly', b'destroy'): (13, 104.64321694951897),\n",
       " (b'rossmore', b'castle'): (8, 1680.65),\n",
       " (b'sitting', b'down'): (24, 16.50978251971512),\n",
       " (b'king', b'ahaz'): (11, 26.20026559658189),\n",
       " (b'main', b'top'): (11, 114.79994940231484),\n",
       " (b'leave', b'off'): (19, 10.456551581109641),\n",
       " (b'fine', b'linen'): (34, 343.23133802816903),\n",
       " (b'thy', b'merchandise'): (8, 14.069794662305146),\n",
       " (b'thirty', b'cubits'): (8, 32.77540628385699),\n",
       " (b'motor', b'car'): (12, 2500.1404958677685),\n",
       " (b'sir', b'john'): (113, 127.78658844235845),\n",
       " (b'molten', b'images'): (10, 900.3482142857142),\n",
       " (b'walked', b'off'): (15, 10.460621861989791),\n",
       " (b\",'\", b'says'): (13, 42.67564803385647),\n",
       " (b'entering', b'into'): (14, 14.764128843338215),\n",
       " (b'hast', b'thou'): (192, 13.609238630335705),\n",
       " (b'strong', b'drink'): (22, 35.91132478632478),\n",
       " (b'still', b'further'): (16, 27.13654767486901),\n",
       " (b'ma', b'am'): (216, 180.33443656689536),\n",
       " (b'unc', b'billy'): (6, 2585.6153846153843),\n",
       " (b'arous', b'd'): (7, 66.58969843715606),\n",
       " (b'an', b'hour'): (155, 40.46461919025373),\n",
       " (b'an', b'invitation'): (13, 13.178876863385744),\n",
       " (b'mine', b'ears'): (13, 18.830812324929973),\n",
       " (b'our', b'selues'): (19, 111.46536477523948),\n",
       " (b'whil', b'st'): (7, 633.2119309262165),\n",
       " (b'turn', b'aside'): (23, 91.53467027517692),\n",
       " (b'mine', b'integrity'): (6, 15.609752321981423),\n",
       " (b'three', b'months'): (36, 79.13813268974364),\n",
       " (b'at', b'home'): (158, 14.817173413852018),\n",
       " (b'good', b'tidings'): (14, 28.459688293769013),\n",
       " (b'joyful', b'noise'): (7, 122.78721461187214),\n",
       " (b'miss', b'campbell'): (12, 69.78477508650519),\n",
       " (b'filled', b'with'): (114, 14.087588281459942),\n",
       " (b'commanded', b'moses'): (60, 79.41215635738833),\n",
       " (b'ninth', b'year'): (8, 69.14674285714285),\n",
       " (b'sir', b',\"'): (121, 14.215621316157259),\n",
       " (b'joe', b'otter'): (47, 3560.5195460277428),\n",
       " (b'last', b'trick'): (7, 18.526080499716766),\n",
       " (b'running', b'away'): (12, 10.939329522648434),\n",
       " (b'whosoever', b'toucheth'): (12, 563.1965425531914),\n",
       " (b'their', b'slates'): (7, 19.377209838585703),\n",
       " (b'south', b'east'): (7, 17.11383597097883),\n",
       " (b'have', b'committed'): (34, 16.059987478581785),\n",
       " (b'followeth', b'after'): (6, 14.812926918839516),\n",
       " (b'freewill', b'offering'): (9, 175.2959582790091),\n",
       " (b'receiv', b'd'): (9, 103.5839753466872),\n",
       " (b'r', b'r'): (6, 3580.082840236687),\n",
       " (b'nigger', b'ned'): (6, 5084.319327731092),\n",
       " (b'brown', b's'): (105, 12.276957466080978),\n",
       " (b'running', b'along'): (8, 20.97826011580736),\n",
       " (b'came', b'near'): (42, 11.125204066571548),\n",
       " (b'burnt', b'incense'): (12, 74.00898193128997),\n",
       " (b'man', b'milliner'): (6, 11.972573463935888),\n",
       " (b'warp', b'or'): (9, 15.305207905138339),\n",
       " (b'e', b'.,'): (6, 189.19136960600375),\n",
       " (b'wise', b'stubb'): (8, 19.088253233778527),\n",
       " (b'at', b'hartfield'): (67, 25.555992478744276),\n",
       " (b'had', b'stolen'): (13, 10.199021454669582),\n",
       " (b'loud', b'voice'): (57, 128.91419861341026),\n",
       " (b'on', b'purpose'): (36, 10.243903158363866),\n",
       " (b'witness', b'between'): (8, 12.26163438739183),\n",
       " (b'ten', b'shekels'): (18, 169.99377553005252),\n",
       " (b'sanctify', b'yourselves'): (8, 113.23156581409856),\n",
       " (b'does', b'seem'): (9, 12.372250907417822),\n",
       " (b'seven', b'rams'): (7, 27.863774523348994),\n",
       " (b'english', b'gentleman'): (7, 21.58061064345841),\n",
       " (b'break', b'down'): (21, 13.057166403424885),\n",
       " (b'twenty', b'elders'): (7, 14.08628236170609),\n",
       " (b'thus', b'eve'): (10, 19.09154591810976),\n",
       " (b'seven', b'lamps'): (7, 35.75851063829787),\n",
       " (b'mr', b'suckling'): (10, 67.58042176749174),\n",
       " (b'five', b'loaves'): (8, 84.43513048332326),\n",
       " (b'buster', b'bear'): (142, 597.6613887086307),\n",
       " (b'my', b'judgments'): (30, 10.90189066000121),\n",
       " (b'second', b'mate'): (6, 12.797639444127165),\n",
       " (b'thou', b'doest'): (30, 45.67107801842441),\n",
       " (b'dear', b'madam'): (15, 86.09887295081967),\n",
       " (b'commit', b'whoredom'): (6, 319.78541226215646),\n",
       " (b'once', b'more'): (141, 21.758506838947973),\n",
       " (b'whale', b'ship'): (34, 18.806470906004016),\n",
       " (b'mustard', b'seed'): (6, 106.23950834064968),\n",
       " (b'was', b'kindled'): (33, 12.069428800427465),\n",
       " (b'higher', b'than'): (34, 44.04157170252713),\n",
       " (b'pleas', b'd'): (20, 166.47424609289018),\n",
       " (b'spake', b'unto'): (272, 27.331433569746352),\n",
       " (b'bathe', b'himself'): (11, 68.80338122133354),\n",
       " (b'long', b'enough'): (39, 14.424561747959498),\n",
       " (b'weight', b'whereof'): (9, 231.9470960322024),\n",
       " (b'seven', b'years'): (53, 50.3345604292756),\n",
       " (b'reign', b'over'): (41, 40.725432893755226),\n",
       " (b'said', b'syme'): (117, 13.84729070381194),\n",
       " (b'stand', b'before'): (50, 10.903364575207162),\n",
       " (b'an', b'idea'): (37, 13.222953374634528),\n",
       " (b'clothed', b'with'): (37, 11.957873100497311),\n",
       " (b'thou', b'sawest'): (26, 64.82143349097754),\n",
       " (b'lazy', b'lawrence'): (11, 1212.898095556298),\n",
       " (b'very', b'wroth'): (11, 18.110271888251432),\n",
       " (b'sixth', b'hour'): (6, 24.463609898107713),\n",
       " (b'wiser', b'than'): (8, 28.37160810303864),\n",
       " (b'threw', b'down'): (16, 21.462717275629657),\n",
       " (b'wise', b'men'): (48, 25.79411671392596),\n",
       " (b'cut', b'down'): (57, 20.366082086363903),\n",
       " (b'tis', b'true'): (8, 17.697262197262198),\n",
       " (b'tenth', b'deals'): (19, 4705.82),\n",
       " (b'laughing', b'brook'): (30, 944.1853932584271),\n",
       " (b'captain', b'wentworth'): (196, 617.1112879281435),\n",
       " (b'sanctuary', b'both'): (12, 27.822406453647254),\n",
       " (b'almonds', b'gratis'): (6, 3980.486842105263),\n",
       " (b'almost', b'fancy'): (9, 14.733568732497261),\n",
       " (b'some', b'surprise'): (19, 20.08802185605737),\n",
       " (b'shalt', b'surely'): (28, 21.382676933052856),\n",
       " (b'color', b'd'): (15, 101.33214979567227),\n",
       " (b'very', b'pretty'): (40, 18.02785881936292),\n",
       " (b'whole', b'congregation'): (17, 20.585922968742913),\n",
       " (b'kill', b'e'): (8, 87.83885017421603),\n",
       " (b'continual', b'burnt'): (20, 264.9397168296599),\n",
       " (b'please', b'your'): (33, 10.535457221855305),\n",
       " (b'public', b'domain'): (7, 946.8450704225353),\n",
       " (b'two', b'years'): (53, 11.95816852658443),\n",
       " (b'deep', b'sigh'): (7, 42.620033812341504),\n",
       " (b'twenty', b'thousand'): (49, 74.70393983612077),\n",
       " (b',\"', b'added'): (51, 21.445980433857933),\n",
       " (b'by', b'accident'): (20, 16.659403636043233),\n",
       " (b'their', b'backs'): (23, 36.714713378372906),\n",
       " (b'tenth', b'deal'): (9, 79.08941176470589),\n",
       " (b'self', b'command'): (15, 129.45780554604588),\n",
       " (b'nobody', b'knows'): (7, 29.65198853194148),\n",
       " (b'soo', b'--'): (7, 31.03534239548602),\n",
       " (b'good', b'news'): (18, 22.238991398956113),\n",
       " (b'badgers', b'skins'): (13, 11524.457142857142),\n",
       " (b'very', b'early'): (25, 10.516998773665177),\n",
       " (b'prevail', b'against'): (16, 58.62061250913831),\n",
       " (b'st', b'paul'): (16, 98.6990256706856),\n",
       " (b'better', b'than'): (175, 40.46903672973475),\n",
       " (b'unreck', b'd'): (6, 38.8439907550077),\n",
       " (b'thine', b'iniquity'): (14, 18.574519033974624),\n",
       " (b'goose', b'pie'): (8, 3757.975155279503),\n",
       " (b'll', b'pay'): (9, 16.75831983048735),\n",
       " (b'everlasting', b'life'): (11, 21.44256020413588),\n",
       " (b'anne', b'elliot'): (23, 67.77658011998705),\n",
       " (b'rams', b'five'): (12, 94.6696917540291),\n",
       " (b'an', b'unnatural'): (10, 18.169407440329614),\n",
       " (b'jeremiah', b'saying'): (11, 13.954057981041998),\n",
       " (b'don', b't'): (830, 258.7786954087346),\n",
       " (b'mrs', b'harville'): (24, 82.53919224555735),\n",
       " (b'dr', b'bull'): (65, 1237.794599018003),\n",
       " (b'thine', b'ears'): (12, 16.052053486150907),\n",
       " (b'fourth', b'generation'): (7, 82.73969230769231),\n",
       " (b'began', b'talking'): (9, 12.980428544611012),\n",
       " (b'captain', b'benwick'): (56, 513.167038084151),\n",
       " (b'sperm', b'whale'): (183, 350.53885362757546),\n",
       " (b'kind', b'hearted'): (6, 22.299646174259177),\n",
       " (b'mouse', b'deer'): (9, 1390.8827586206896),\n",
       " (b'white', b'hair'): (20, 32.3515299720527),\n",
       " (b'an', b'effort'): (8, 12.355197059424137),\n",
       " (b'drink', b'offering'): (30, 42.13845150937719),\n",
       " (b'mast', b'heads'): (37, 497.5097132284921),\n",
       " (b'wilt', b'thou'): (143, 43.34425678043311),\n",
       " (b'twenty', b'minutes'): (8, 15.956660102679514),\n",
       " (b'laura', b'place'): (7, 20.594798829055758),\n",
       " (b'thus', b'michael'): (8, 16.819893618992904),\n",
       " (b'hath', b'done'): (82, 13.901481527898378),\n",
       " (b'blackberry', b'bush'): (7, 3781.4625),\n",
       " (b'never', b'forget'): (18, 19.811797243380486),\n",
       " (b'their', b'armies'): (21, 13.627927798565768),\n",
       " (b'cried', b'stubb'): (23, 38.2799658346778),\n",
       " (b'my', b'fury'): (34, 14.26749998170415),\n",
       " (b'mr', b'e'): (10, 15.658878214418817),\n",
       " (b'molten', b'image'): (13, 733.3745454545455),\n",
       " (b'domestic', b'happiness'): (6, 55.01309328968903),\n",
       " (b'river', b'euphrates'): (15, 749.2681114551084),\n",
       " (b'abraham', b'isaac'): (10, 86.49768399382397),\n",
       " (b'mr', b'gresham'): (49, 225.98893039049236),\n",
       " (b'wise', b'hearted'): (7, 57.37638691322902),\n",
       " (b'silk', b'hat'): (12, 551.46328125),\n",
       " (b'without', b'number'): (13, 10.413352437749294),\n",
       " (b'nebuchadnezzar', b'king'): (15, 32.02254684026675),\n",
       " (b'great', b'curiosity'): (13, 12.09281966721631),\n",
       " (b'bell', b'rang'): (9, 591.4310850439882),\n",
       " (b'turn', b'back'): (16, 10.061840177671076),\n",
       " (b'an', b'example'): (14, 16.847995990123824),\n",
       " (b'three', b'minutes'): (10, 10.22196466946896),\n",
       " (b'made', b'haste'): (11, 10.417012924404856),\n",
       " (b'witness', b'against'): (23, 24.353923802666035),\n",
       " (b'emma', b'could'): (61, 10.88608805283633),\n",
       " (b'poor', b'pip'): (7, 18.02896391430019),\n",
       " (b'five', b'hundred'): (67, 84.28815897682486),\n",
       " (b'cloud', b'covered'): (6, 14.383311541661714),\n",
       " (b'little', b'nightingale'): (17, 42.30020974131904),\n",
       " (b'floweth', b'with'): (12, 20.05434967895903),\n",
       " (b'any', b'harm'): (11, 11.88333382435259),\n",
       " (b'have', b'erred'): (10, 17.591061335566256),\n",
       " (b'jordan', b'near'): (8, 15.050597014925373),\n",
       " (b'accursed', b'thing'): (10, 35.63971159963243),\n",
       " (b'due', b'season'): (10, 169.1929530201342),\n",
       " (b'cape', b'horn'): (17, 1669.0593103448275),\n",
       " (b'ride', b'upon'): (10, 10.146299743422045),\n",
       " (b'too', b'late'): (56, 82.78464324520101),\n",
       " (b'seest', b'thou'): (21, 25.127105379961222),\n",
       " (b'shalt', b'offer'): (17, 12.801633438949692),\n",
       " (b'lady', b'middleton'): (95, 500.3819045606168),\n",
       " (b'from', b'whence'): (44, 15.950059078483806),\n",
       " (b'sir', b'wilson'): (13, 354.5986813186813),\n",
       " (b'joined', b'together'): (8, 12.985419945628845),\n",
       " (b'being', b'interpreted'): (7, 52.320477343479766),\n",
       " (b'old', b'age'): (51, 59.17756524475554),\n",
       " (b'taken', b'away'): (75, 32.39398354768761),\n",
       " (b'an', b'anarchist'): (17, 33.69599198024765),\n",
       " (b'found', b'grace'): (18, 22.16223024319321),\n",
       " (b'spread', b'abroad'): (14, 187.66563275434243),\n",
       " ...}"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lower_bigram.phrasegrams # (b'miss', b'fairfax') (b'any', b'thing') (b'laugh', b'at')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['jon', 'lives', 'in', 'new', 'york', 'city']"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Quick Test\n",
    "lower_bigram[\"jon lives in new york city\".split()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(b'afar', b'off'): (52, 108.14220347465505),\n",
       " (b'burnt', b'offering'): (184, 297.524653753951),\n",
       " (b'burnt', b'offerings'): (86, 299.15702343127646),\n",
       " (b'buster', b'bear'): (142, 479.87410772225826),\n",
       " (b'captain', b'benwick'): (56, 241.49037086312987),\n",
       " (b'captain', b'wentworth'): (196, 529.8756608388247),\n",
       " (b'charles', b'hayter'): (33, 92.03437785214481),\n",
       " (b'chief', b'priests'): (65, 116.31947753846512),\n",
       " (b'colonel', b'brandon'): (132, 1313.0078125),\n",
       " (b'couldn', b't'): (89, 171.76138536935215),\n",
       " (b'cut', b'off'): (217, 129.60290535032792),\n",
       " (b'dare', b'say'): (115, 89.94000515807346),\n",
       " (b'de', b'grey'): (77, 603.2109624246722),\n",
       " (b'didn', b't'): (180, 220.51081560283686),\n",
       " (b'doesn', b't'): (53, 106.2634985949418),\n",
       " (b'don', b't'): (830, 250.30957446808512),\n",
       " (b'dr', b'bull'): (65, 680.7870294599019),\n",
       " (b'dr', b'middleton'): (40, 162.73103819257668),\n",
       " (b'drawing', b'room'): (49, 84.91494947493561),\n",
       " (b'farmer', b'brown'): (100, 386.05179596892236),\n",
       " (b'father', b'brown'): (207, 91.68277248710235),\n",
       " (b'few', b'minutes'): (86, 204.16834974753786),\n",
       " (b'few', b'moments'): (43, 107.77584531675087),\n",
       " (b'fig', b'tree'): (37, 121.73722334004026),\n",
       " (b'fine', b'flour'): (36, 86.07682458386685),\n",
       " (b'fir', b'tree'): (36, 72.6789393074867),\n",
       " (b'forty', b'years'): (68, 90.60220877269607),\n",
       " (b'frank', b'churchill'): (151, 1316.4456593286038),\n",
       " (b'gathered', b'together'): (84, 103.28066074898891),\n",
       " (b'good', b'natured'): (66, 88.69936184891343),\n",
       " (b'great', b'deal'): (182, 93.36368125424357),\n",
       " (b'green', b'forest'): (66, 336.37733627667404),\n",
       " (b'guinea', b'hen'): (51, 905.8822695035461),\n",
       " (b'high', b'places'): (99, 129.8123390846559),\n",
       " (b'holy', b'ghost'): (90, 313.0305073859987),\n",
       " (b'isn', b't'): (63, 131.96593211752787),\n",
       " (b'jane', b'fairfax'): (111, 654.5565917587609),\n",
       " (b'jesus', b'christ'): (199, 172.16816954974848),\n",
       " (b'joe', b'otter'): (47, 1271.6141235813368),\n",
       " (b'john', b'knightley'): (58, 83.03755747111268),\n",
       " (b'lady', b'middleton'): (95, 350.26733319243175),\n",
       " (b'lady', b'russell'): (147, 613.6301581282135),\n",
       " (b'little', b'jackal'): (61, 69.81254128038833),\n",
       " (b'little', b'joe'): (111, 133.28784038147822),\n",
       " (b'm', b'sure'): (88, 69.15069432539002),\n",
       " (b'ma', b'am'): (216, 157.25846601094193),\n",
       " (b'mast', b'heads'): (37, 77.7358926919519),\n",
       " (b'meat', b'offering'): (122, 210.66724956379437),\n",
       " (b'mercy', b'endureth'): (41, 269.07674062361025),\n",
       " (b'miss', b'bates'): (113, 276.39588291692513),\n",
       " (b'miss', b'dashwood'): (70, 76.66830732292917),\n",
       " (b'miss', b'fairfax'): (125, 196.19987447261062),\n",
       " (b'miss', b'smith'): (58, 73.03442128232508),\n",
       " (b'miss', b'somers'): (49, 160.06190476190477),\n",
       " (b'miss', b'taylor'): (48, 156.44059469941823),\n",
       " (b'miss', b'woodhouse'): (173, 229.03802722366902),\n",
       " (b'moby', b'dick'): (84, 4115.877551020409),\n",
       " (b'mock', b'turtle'): (56, 2528.877742946708),\n",
       " (b'mr', b'elliot'): (174, 126.18129960463163),\n",
       " (b'mr', b'elton'): (214, 121.3990121932397),\n",
       " (b'mr', b'gresham'): (49, 87.31390492359931),\n",
       " (b'mr', b'knightley'): (277, 161.74131790625913),\n",
       " (b'mr', b'weston'): (162, 75.87438262077481),\n",
       " (b'mr', b'woodhouse'): (132, 82.04651843976633),\n",
       " (b'mrs', b'clay'): (66, 93.08931456265867),\n",
       " (b'mrs', b'dashwood'): (121, 115.06873605661974),\n",
       " (b'mrs', b'elton'): (142, 93.08931456265867),\n",
       " (b'mrs', b'ferrars'): (73, 102.75628184416554),\n",
       " (b'mrs', b'goddard'): (58, 143.57843432545658),\n",
       " (b'mrs', b'jennings'): (229, 279.0655756128398),\n",
       " (b'mrs', b'musgrove'): (66, 85.21252640735679),\n",
       " (b'mrs', b'smith'): (79, 84.60327207490248),\n",
       " (b'mrs', b'theresa'): (67, 170.20061244665206),\n",
       " (b'mrs', b'weston'): (249, 160.68485093258923),\n",
       " (b'o', b'clock'): (67, 89.14789088153573),\n",
       " (b'o', b'er'): (82, 108.14993564993564),\n",
       " (b'peace', b'offerings'): (83, 176.2577199456205),\n",
       " (b'sent', b'messengers'): (43, 79.21555418015616),\n",
       " (b'sin', b'offering'): (118, 129.96079665512747),\n",
       " (b'sir', b'arthur'): (71, 131.41924812030075),\n",
       " (b'sir', b'john'): (113, 95.83994133176884),\n",
       " (b'sir', b'walter'): (136, 399.5145142857143),\n",
       " (b'six', b'hundred'): (66, 73.57615079223149),\n",
       " (b'sperm', b'whale'): (183, 297.3672297627184),\n",
       " (b'sweet', b'savour'): (43, 286.17879256965944),\n",
       " (b'take', b'heed'): (58, 86.38454061712328),\n",
       " (b'ten', b'thousand'): (82, 84.00099962514057),\n",
       " (b'thou', b'shalt'): (1282, 66.88233182614454),\n",
       " (b'thousand', b'pounds'): (48, 166.51834523092802),\n",
       " (b'thus', b'saith'): (444, 144.0289127889979),\n",
       " (b'unleavened', b'bread'): (43, 237.70041787206688),\n",
       " (b'wasn', b't'): (58, 120.2225788701394),\n",
       " (b'wee', b'l'): (35, 450.39751861042186),\n",
       " (b'without', b'blemish'): (46, 83.71359108159393),\n",
       " (b'won', b't'): (219, 189.96708776595744),\n",
       " (b'wouldn', b't'): (58, 120.2225788701394),\n",
       " (b'years', b'ago'): (56, 74.31594785893046)}"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Upping the Threashold for Occurence=32, SCore=64, we will get more clear pairs\n",
    "lower_bigram = Phraser(Phrases(lower_sents, min_count=32, threshold=64))\n",
    "lower_bigram.phrasegrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# as in Maas et al. (2001):\n",
    "# - leave in stop words (\"indicative of sentiment\")\n",
    "# - no stemming (\"model learns similar representations of words of the same stem when data suggests it\")\n",
    "#for each sentence we append after passing it through the filter\n",
    "clean_sents = []\n",
    "for s in lower_sents:\n",
    "    clean_sents.append(lower_bigram[s])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['emma', 'by', 'jane', 'austen', '1816'],\n",
       " ['volume', 'i'],\n",
       " ['chapter', 'i'],\n",
       " ['emma',\n",
       "  'woodhouse',\n",
       "  'handsome',\n",
       "  'clever',\n",
       "  'and',\n",
       "  'rich',\n",
       "  'with',\n",
       "  'a',\n",
       "  'comfortable',\n",
       "  'home',\n",
       "  'and',\n",
       "  'happy',\n",
       "  'disposition',\n",
       "  'seemed',\n",
       "  'to',\n",
       "  'unite',\n",
       "  'some',\n",
       "  'of',\n",
       "  'the',\n",
       "  'best',\n",
       "  'blessings',\n",
       "  'of',\n",
       "  'existence',\n",
       "  'and',\n",
       "  'had',\n",
       "  'lived',\n",
       "  'nearly',\n",
       "  'twenty',\n",
       "  'one',\n",
       "  'years',\n",
       "  'in',\n",
       "  'the',\n",
       "  'world',\n",
       "  'with',\n",
       "  'very',\n",
       "  'little',\n",
       "  'to',\n",
       "  'distress',\n",
       "  'or',\n",
       "  'vex',\n",
       "  'her'],\n",
       " ['she',\n",
       "  'was',\n",
       "  'the',\n",
       "  'youngest',\n",
       "  'of',\n",
       "  'the',\n",
       "  'two',\n",
       "  'daughters',\n",
       "  'of',\n",
       "  'a',\n",
       "  'most',\n",
       "  'affectionate',\n",
       "  'indulgent',\n",
       "  'father',\n",
       "  'and',\n",
       "  'had',\n",
       "  'in',\n",
       "  'consequence',\n",
       "  'of',\n",
       "  'her',\n",
       "  'sister',\n",
       "  's',\n",
       "  'marriage',\n",
       "  'been',\n",
       "  'mistress',\n",
       "  'of',\n",
       "  'his',\n",
       "  'house',\n",
       "  'from',\n",
       "  'a',\n",
       "  'very',\n",
       "  'early',\n",
       "  'period'],\n",
       " ['her',\n",
       "  'mother',\n",
       "  'had',\n",
       "  'died',\n",
       "  'too',\n",
       "  'long',\n",
       "  'ago',\n",
       "  'for',\n",
       "  'her',\n",
       "  'to',\n",
       "  'have',\n",
       "  'more',\n",
       "  'than',\n",
       "  'an',\n",
       "  'indistinct',\n",
       "  'remembrance',\n",
       "  'of',\n",
       "  'her',\n",
       "  'caresses',\n",
       "  'and',\n",
       "  'her',\n",
       "  'place',\n",
       "  'had',\n",
       "  'been',\n",
       "  'supplied',\n",
       "  'by',\n",
       "  'an',\n",
       "  'excellent',\n",
       "  'woman',\n",
       "  'as',\n",
       "  'governess',\n",
       "  'who',\n",
       "  'had',\n",
       "  'fallen',\n",
       "  'little',\n",
       "  'short',\n",
       "  'of',\n",
       "  'a',\n",
       "  'mother',\n",
       "  'in',\n",
       "  'affection'],\n",
       " ['sixteen',\n",
       "  'years',\n",
       "  'had',\n",
       "  'miss_taylor',\n",
       "  'been',\n",
       "  'in',\n",
       "  'mr_woodhouse',\n",
       "  's',\n",
       "  'family',\n",
       "  'less',\n",
       "  'as',\n",
       "  'a',\n",
       "  'governess',\n",
       "  'than',\n",
       "  'a',\n",
       "  'friend',\n",
       "  'very',\n",
       "  'fond',\n",
       "  'of',\n",
       "  'both',\n",
       "  'daughters',\n",
       "  'but',\n",
       "  'particularly',\n",
       "  'of',\n",
       "  'emma'],\n",
       " ['between',\n",
       "  '_them_',\n",
       "  'it',\n",
       "  'was',\n",
       "  'more',\n",
       "  'the',\n",
       "  'intimacy',\n",
       "  'of',\n",
       "  'sisters'],\n",
       " ['even',\n",
       "  'before',\n",
       "  'miss_taylor',\n",
       "  'had',\n",
       "  'ceased',\n",
       "  'to',\n",
       "  'hold',\n",
       "  'the',\n",
       "  'nominal',\n",
       "  'office',\n",
       "  'of',\n",
       "  'governess',\n",
       "  'the',\n",
       "  'mildness',\n",
       "  'of',\n",
       "  'her',\n",
       "  'temper',\n",
       "  'had',\n",
       "  'hardly',\n",
       "  'allowed',\n",
       "  'her',\n",
       "  'to',\n",
       "  'impose',\n",
       "  'any',\n",
       "  'restraint',\n",
       "  'and',\n",
       "  'the',\n",
       "  'shadow',\n",
       "  'of',\n",
       "  'authority',\n",
       "  'being',\n",
       "  'now',\n",
       "  'long',\n",
       "  'passed',\n",
       "  'away',\n",
       "  'they',\n",
       "  'had',\n",
       "  'been',\n",
       "  'living',\n",
       "  'together',\n",
       "  'as',\n",
       "  'friend',\n",
       "  'and',\n",
       "  'friend',\n",
       "  'very',\n",
       "  'mutually',\n",
       "  'attached',\n",
       "  'and',\n",
       "  'emma',\n",
       "  'doing',\n",
       "  'just',\n",
       "  'what',\n",
       "  'she',\n",
       "  'liked',\n",
       "  'highly',\n",
       "  'esteeming',\n",
       "  'miss_taylor',\n",
       "  's',\n",
       "  'judgment',\n",
       "  'but',\n",
       "  'directed',\n",
       "  'chiefly',\n",
       "  'by',\n",
       "  'her',\n",
       "  'own']]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_sents[0:9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sixteen',\n",
       " 'years',\n",
       " 'had',\n",
       " 'miss_taylor',\n",
       " 'been',\n",
       " 'in',\n",
       " 'mr_woodhouse',\n",
       " 's',\n",
       " 'family',\n",
       " 'less',\n",
       " 'as',\n",
       " 'a',\n",
       " 'governess',\n",
       " 'than',\n",
       " 'a',\n",
       " 'friend',\n",
       " 'very',\n",
       " 'fond',\n",
       " 'of',\n",
       " 'both',\n",
       " 'daughters',\n",
       " 'but',\n",
       " 'particularly',\n",
       " 'of',\n",
       " 'emma']"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_sents[6] # could consider removing stop words or common words"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Run word2vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# max_vocab_size can be used instead of min_count (which has increased here)\n",
    "#3 min runtime with 4GB ram and core i5\n",
    "model = Word2Vec(sentences=clean_sents, size=64, sg=1, window=10, min_count=10, seed=42, workers=8)\n",
    "model.save('clean_gutenberg_model.w2v')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Explore model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# skip re-training the model with the next line:  \n",
    "model = gensim.models.Word2Vec.load('clean_gutenberg_model.w2v')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10329"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(model.wv.vocab) # down from 17k in previous notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.3766728 ,  0.25876319, -0.5080471 ,  0.28249156,  0.23865087,\n",
       "        0.14390723,  0.44638735, -0.38710511,  0.08591636, -0.4380151 ,\n",
       "       -0.34897214, -0.00249946, -0.34433517, -0.27894989, -0.04447649,\n",
       "        0.09560811,  0.31241906, -0.32027555,  0.27962631, -0.4075135 ,\n",
       "       -0.18637814, -0.39342263, -0.23533073, -0.12845472, -0.11570611,\n",
       "       -0.51977575, -0.55927455, -0.21281895,  0.14258136,  0.06874955,\n",
       "       -0.43849438,  0.44356996, -0.49349496,  0.14603022,  0.24101605,\n",
       "       -0.09670868,  0.11244334, -0.10839415,  0.06011881,  0.0663384 ,\n",
       "        0.25652117,  0.12797897, -0.0923718 ,  0.00310699,  0.22638071,\n",
       "       -0.73350906, -0.55577111,  0.266978  , -0.29816863,  0.25034562,\n",
       "        0.40704545, -0.28457001,  0.30009076,  0.02513353,  0.21761766,\n",
       "        1.14099336, -0.23552875,  0.34190479, -0.15770121, -0.03580849,\n",
       "       -0.42009705, -0.18253484, -0.4941777 ,  0.19476052], dtype=float32)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# new word from the bioagram \"ma_am\"\n",
    "model['ma_am']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('betty', 0.8653212785720825),\n",
       " ('madam', 0.8392884731292725),\n",
       " ('m_sure', 0.8314577341079712),\n",
       " ('nancy', 0.8245792984962463),\n",
       " ('goose', 0.8226374387741089),\n",
       " ('shouldn', 0.8219201564788818),\n",
       " ('mamma', 0.816972017288208),\n",
       " ('sir', 0.8163734674453735),\n",
       " ('madman', 0.8141891956329346),\n",
       " (\";'\", 0.8134243488311768)]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.most_similar('ma_am') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('dr', 0.7182788848876953),\n",
       " ('sergeant', 0.7124853730201721),\n",
       " ('hutton', 0.7111455202102661),\n",
       " ('policeman', 0.702538251876831),\n",
       " ('wilkinson', 0.6966596245765686),\n",
       " ('anyhow', 0.6954399347305298),\n",
       " ('hirsch', 0.6933173537254333),\n",
       " ('professor', 0.6880460381507874),\n",
       " ('jolly', 0.6866101622581482),\n",
       " ('bullet', 0.6860513091087341)]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# swap woman and man, expecting \"sir\", \n",
    "model.most_similar(positive=['ma_am', 'man'], negative=['woman']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('sister', 0.7776371240615845),\n",
       " ('mother', 0.7605657577514648),\n",
       " ('husband', 0.7577716112136841),\n",
       " ('daughter', 0.7470927238464355),\n",
       " ('wife', 0.7349058985710144),\n",
       " ('sarah', 0.7004030346870422),\n",
       " ('jacob', 0.691778838634491),\n",
       " ('rebekah', 0.6848896741867065),\n",
       " ('daughters', 0.6780199408531189),\n",
       " ('brother', 0.6771359443664551)]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.most_similar(positive=['father', 'woman'], negative=['man']) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Reduce word vector dimensionality with t-SNE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsne = TSNE(n_components=2, n_iter=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_2d = tsne.fit_transform(model[model.wv.vocab])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "coords_df = pd.DataFrame(X_2d, columns=['x','y'])\n",
    "coords_df['token'] = model.wv.vocab.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead tr:only-child th {\n",
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       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
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       "      <th>0</th>\n",
       "      <td>-13.057447</td>\n",
       "      <td>-48.458469</td>\n",
       "      <td>bracelets</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-34.306622</td>\n",
       "      <td>15.693257</td>\n",
       "      <td>speak</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.094606</td>\n",
       "      <td>37.087463</td>\n",
       "      <td>considerate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28.234352</td>\n",
       "      <td>34.120564</td>\n",
       "      <td>amendment</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.219818</td>\n",
       "      <td>1.695316</td>\n",
       "      <td>vice</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           x          y        token\n",
       "0 -13.057447 -48.458469    bracelets\n",
       "1 -34.306622  15.693257        speak\n",
       "2   0.094606  37.087463  considerate\n",
       "3  28.234352  34.120564    amendment\n",
       "4   4.219818   1.695316         vice"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coords_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "coords_df.to_csv('clean_gutenberg_tsne.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualise "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "coords_df = pd.read_csv('clean_gutenberg_tsne.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CJ7YNQPwRtCOiqZHJ4+OLoZxX1X4BDPz3Z0/K8DwP6fk55X628ik8PDjFfqmJ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Zs0/UWn3eRgW250cWkuOxL9kXn9TSE7mIvyf2iKZKXpjn2XYFLR5GlGbGTHmFqszee5hSfChImX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l36/lS3NSqwVzgzfaHWQl1Sd1baKOmY1iSfUKqA4H1Dab2iSj15hoRhTYHLIG29jttU035mtl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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2f19e128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = coords_df.plot.scatter('x', 'y', figsize=(12,12), marker='.', s=10, alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"dc7729b4-70fd-4130-96e8-e3c59cd5c00d\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id !== undefined) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
       "            delete Bokeh.index[element_id];\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[0].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[0]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"dc7729b4-70fd-4130-96e8-e3c59cd5c00d\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"dc7729b4-70fd-4130-96e8-e3c59cd5c00d\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'dc7729b4-70fd-4130-96e8-e3c59cd5c00d' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.13.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"dc7729b4-70fd-4130-96e8-e3c59cd5c00d\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"dc7729b4-70fd-4130-96e8-e3c59cd5c00d\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"dc7729b4-70fd-4130-96e8-e3c59cd5c00d\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'dc7729b4-70fd-4130-96e8-e3c59cd5c00d' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.13.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"dc7729b4-70fd-4130-96e8-e3c59cd5c00d\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "subset_df = coords_df.sample(n=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = figure(plot_width=800, plot_height=800)\n",
    "_ = p.text(x=subset_df.x, y=subset_df.y, text=subset_df.token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"c470c66a-b77b-496e-8f92-8e26cbc68747\"></div>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
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Application\",\"version\":\"0.12.13\"}};\n",
       "  var render_items = [{\"docid\":\"7317a118-6401-4953-a069-c60d4bf5feb7\",\"elementid\":\"c470c66a-b77b-496e-8f92-8e26cbc68747\",\"modelid\":\"6954f4a1-7cde-4c0b-b202-bc6f93195f31\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "6954f4a1-7cde-4c0b-b202-bc6f93195f31"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_file(\"W2V\", title=\"W2V\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}