Count_Vectorizer.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Vectorizing Raw Data: Count Vectorization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Count vectorization \n",
    "\n",
    "Creates a document-term matrix where the entry of each cell will be a count of the number of times that word occurred in that document."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read in text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import re\n",
    "import string\n",
    "import nltk\n",
    "pd.set_option('display.max_colwidth', 100)\n",
    "\n",
    "stopwords = nltk.corpus.stopwords.words('english')\n",
    "ps = nltk.PorterStemmer()\n",
    "\n",
    "data = pd.read_csv(\"SMSSpamCollection.tsv\", sep='\\t')\n",
    "data.columns = ['label', 'body_text']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create function to remove punctuation, tokenize, remove stopwords, and stem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def clean_text(text):\n",
    "    text = \"\".join([word.lower() for word in text if word not in string.punctuation])\n",
    "    tokens = re.split('\\W+', text)\n",
    "    text = [ps.stem(word) for word in tokens if word not in stopwords]\n",
    "    return text"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Apply CountVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5567, 8104)\n",
      "['', '0', '008704050406', '0089mi', '0121', '01223585236', '01223585334', '0125698789', '02', '020603', '0207', '02070836089', '02072069400', '02073162414', '02085076972', '020903', '021', '050703', '0578', '06', '060505', '061104', '07008009200', '07046744435', '07090201529', '07090298926', '07099833605', '071104', '07123456789', '0721072', '07732584351', '07734396839', '07742676969', '07753741225', '0776xxxxxxx', '07786200117', '077xxx', '078', '07801543489', '07808', '07808247860', '07808726822', '07815296484', '07821230901', '0784987', '0789xxxxxxx', '0794674629107880867867', '0796xxxxxx', '07973788240', '07xxxxxxxxx', '0800', '08000407165', '08000776320', '08000839402', '08000930705', '08000938767', '08001950382', '08002888812', '08002986030', '08002986906', '08002988890', '08006344447', '0808', '08081263000', '08081560665', '0825', '0844', '08448350055', '08448714184', '0845', '08450542832', '08452810071', '08452810073', '08452810075over18', '0870', '08700621170150p', 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'spiderman', 'spif', 'spile', 'spin', 'spinout', 'spiral', 'spirit', 'spiritu', 'spjanuari', 'spk', 'spl', 'splash', 'splashmobil', 'splat', 'splendid', 'split', 'splle', 'splwat', 'spoil', 'spoilt', 'spoke', 'spoken', 'sponsor', 'spontan', 'spook', 'spoon', 'sporad', 'sport', 'sportsx', 'spose', 'spot', 'spotti', 'spous', 'sppok', 'spreadsheet', 'spree', 'spring', 'sprint', 'sprwm', 'sptv', 'sptyron', 'spunout', 'sq825', 'squat', 'squeeeeez', 'squeez', 'squid', 'squishi', 'sr', 'sri', 'srsli', 'srt', 'ssi', 'ssindia', 'ssnervou', 'st', 'stabil', 'stabl', 'stadium', 'staff', 'staffsciencenusedusgphyhcmkteachingpc1323', 'stage', 'stagwood', 'stair', 'stalk', 'stamp', 'stand', 'standard', 'stapati', 'star', 'stare', 'starer', 'starshin', 'start', 'startedindia', 'starti', 'starv', 'starwars3', 'stash', 'state', 'statement', 'station', 'statu', 'stay', 'stayin', 'std', 'stdtxtrate', 'steak', 'steal', 'steam', 'steamboat', 'steed', 'steer', 'step', 'stereo', 'stereophon', 'sterl', 'sterm', 'steve', 'stevelik', 'stewarts', 'steyn', 'sth', 'sthi', 'stick', 'sticki', 'stifl', 'stil', 'still', 'stillmayb', 'stink', 'stitch', 'stock', 'stockport', 'stolen', 'stomach', 'stomp', 'stone', 'stoner', 'stool', 'stop', 'stop2', 'stop2stop', 'stopbcm', 'stopc', 'stopcost', 'stoptxt', 'stoptxtstop', 'store', 'storelik', 'stori', 'storm', 'str', 'str8', 'straight', 'strain', 'strang', 'stranger', 'strangersaw', 'stream', 'street', 'streetshal', 'stress', 'stressful', 'stretch', 'strewn', 'strict', 'strike', 'string', 'strip', 'stripe', 'stroke', 'strong', 'strongbuy', 'strongli', 'strt', 'strtd', 'struggl', 'stu', 'stubborn', 'stuck', 'studdi', 'student', 'studentfinanci', 'studentsthi', 'studi', 'studio', 'studyn', 'stuf', 'stuff', 'stuff42moro', 'stuffleav', 'stuffwhi', 'stun', 'stupid', 'stupidit', 'style', 'stylish', 'stylist', 'sub', 'subject', 'sublet', 'submit', 'subpoli', 'subscrib', 'subscribe6gbpmnth', 'subscript', 'subscriptn3gbpwk', 'subscrit', 'subsequ', 'subtoitl', 'success', 'suck', 'sucker', 'sudden', 'suddenli', 'sudn', 'sue', 'suffer', 'suffici', 'sugabab', 'suganya', 'sugar', 'sugardad', 'suggest', 'suit', 'suitem', 'sullivan', 'sum', 'sum1', 'sumf', 'summer', 'summon', 'sumthin', 'sumthinxx', 'sun', 'sun0819', 'sunday', 'sundayish', 'sunlight', 'sunni', 'sunoco', 'sunroof', 'sunscreen', 'sunshin', 'suntec', 'sup', 'super', 'superb', 'superior', 'supervisor', 'supli', 'supos', 'suppli', 'supplier', 'support', 'supportprovid', 'supportveri', 'suppos', 'suprem', 'suprman', 'sura', 'sure', 'surf', 'surgic', 'surli', 'surnam', 'surpris', 'surrend', 'surround', 'survey', 'surya', 'sutra', 'sux', 'suzi', 'svc', 'sw7', 'sw73ss', 'swalpa', 'swan', 'swann', 'swap', 'swashbuckl', 'swat', 'swatch', 'sway', 'swayz', 'swear', 'sweater', 'sweatter', 'sweet', 'sweetest', 'sweetheart', 'sweeti', 'swell', 'swhrt', 'swim', 'swimsuit', 'swing', 'swiss', 'switch', 'swollen', 'swoop', 'swt', 'swtheart', 'syd', 'syllabu', 'symbol', 'sympathet', 'symptom', 'sync', 'syria', 'syrup', 'system', 't91', 'ta', 'tabl', 'tablet', 'tackl', 'taco', 'tact', 'tactless', 'tadaaaaa', 'tag', 'tahan', 'tai', 'tait', 'taj', 'taka', 'take', 'takecar', 'taken', 'takenonli', 'takin', 'talent', 'talk', 'talkbut', 'talkin', 'tall', 'tallahasse', 'tallent', 'tamilnaduthen', 'tampa', 'tank', 'tantrum', 'tap', 'tape', 'tariff', 'tarot', 'tarpon', 'tast', 'tat', 'tata', 'tattoo', 'tau', 'taught', 'taunton', 'tax', 'taxi', 'taxless', 'taxt', 'taylor', 'tayseertissco', 'tb', 'tbspersolvo', 'tc', 'tcllc', 'tcrw1', 'tcsbcm4235wc1n3xx', 'tcsc', 'tcsstop', 'tddnewsletteremc1couk', 'tea', 'teach', 'teacher', 'teacoffe', 'team', 'tear', 'teas', 'tech', 'technic', 'technolog', 'tee', 'teenag', 'teeth', 'teethi', 'teethif', 'teju', 'tel', 'telephon', 'teletext', 'tell', 'telli', 'tellmiss', 'telphon', 'telugu', 'telugutht', 'temal', 'temp', 'temper', 'templ', 'ten', 'tenant', 'tendenc', 'tenerif', 'tens', 'tension', 'teresa', 'term', 'terminatedw', 'termsappli', 'terri', 'terribl', 'terrif', 'terrorist', 'tesco', 'tessypl', 'test', 'tex', 'texa', 'texd', 'text', 'text82228', 'textand', 'textbook', 'textbuddi', 'textcomp', 'textin', 'textoper', 'textpod', 'textsweekend', 'tgxxrz', 'th', 'thandiyachu', 'thangam', 'thangamit', 'thank', 'thanks2', 'thanksgiv', 'thanku', 'thankyou', 'thanx', 'thanx4', 'thanxxx', 'thasa', 'that', 'that2worzel', 'thatd', 'thatdont', 'thati', 'thatll', 'thatmum', 'thatnow', 'the4th', 'theacus', 'theater', 'theatr', 'thecd', 'thedailydraw', 'thekingshead', 'theme', 'themob', 'themobhit', 'themobyo', 'themp', 'thenwil', 'theoret', 'theori', 'theplac', 'thepub', 'there', 'theredo', 'theregoodnight', 'therel', 'therer', 'therexx', 'theseday', 'theseyour', 'thesi', 'thesmszonecom', 'thewend', 'theyll', 'theyr', 'thgt', 'thi', 'thia', 'thin', 'thing', 'thinghow', 'think', 'thinkin', 'thinkthi', 'thinl', 'thirunelvali', 'thisdon', 'thk', 'thkin', 'thm', 'thnk', 'thnq', 'thnx', 'tho', 'thoso', 'thot', 'thou', 'though', 'thought', 'thoughtsi', 'thousand', 'thout', 'thread', 'threat', 'three', 'threw', 'thriller', 'throat', 'throw', 'throwin', 'thrown', 'thru', 'thrurespect', 'tht', 'thu', 'thuglyf', 'thur', 'thursday', 'thx', 'ti', 'tick', 'ticket', 'tiempo', 'tiger', 'tight', 'tightli', 'tigress', 'tih', 'tiim', 'til', 'till', 'tim', 'time', 'timedhoni', 'timegud', 'timehop', 'timeslil', 'timey', 'timeyour', 'timi', 'timin', 'tini', 'tip', 'tire', 'tirunelvai', 'tirunelvali', 'tirupur', 'tisscotays', 'titl', 'titleso', 'tiwari', 'tix', 'tiz', 'tke', 'tkt', 'tlk', 'tm', 'tming', 'tmobil', 'tmorrowpl', 'tmr', 'tmrw', 'tmw', 'tnc', 'toa', 'toaday', 'tobacco', 'tobe', 'tocallshal', 'toclaim', 'today', 'todaybut', 'todaydo', 'todayfrom', 'todaygood', 'todayh', 'todaysundaysunday', 'todo', 'tog', 'togeth', 'tohar', 'toilet', 'tok', 'toke', 'token', 'tol', 'told', 'toldsh', 'toledo', 'toler', 'toleratbc', 'toll', 'tom', 'tomarrow', 'tome', 'tomeandsaidthi', 'tomo', 'tomoc', 'tomorro', 'tomorrow', 'tomorrowcal', 'tomorrowtoday', 'tomorw', 'ton', 'tone', 'tones2u', 'tones2youcouk', 'tonesrepli', 'tonex', 'tonght', 'tongu', 'tonight', 'tonit', 'tonitebusi', 'toniteth', 'tonsolitusaswel', 'took', 'tookplac', 'tool', 'toolet', 'tooo', 'toopray', 'toot', 'toothpast', 'tootsi', 'top', 'topic', 'topicsorri', 'toplay', 'toppoli', 'tor', 'torch', 'torrent', 'tortilla', 'tortur', 'tosend', 'toshiba', 'toss', 'tot', 'total', 'tote', 'touch', 'tough', 'toughest', 'tour', 'toward', 'town', 'towncud', 'towndontmatt', 'toxic', 'toyota', 'tp', 'track', 'trackmarqu', 'trade', 'tradit', 'traffic', 'train', 'trainner', 'tram', 'tranquil', 'transact', 'transcrib', 'transfer', 'transferacc', 'transfr', 'transport', 'trash', 'trauma', 'trav', 'travel', 'treacl', 'treadmil', 'treasur', 'treat', 'treatin', 'trebl', 'tree', 'trek', 'trend', 'tri', 'trial', 'trip', 'tripl', 'trishul', 'triumph', 'tron', 'troubl', 'troubleshoot', 'trouser', 'trubl', 'truck', 'true', 'truekdo', 'truffl', 'truli', 'truro', 'trust', 'truth', 'tryin', 'trywal', 'ts', 'tsandc', 'tsc', 'tscs08714740323', 'tscs087147403231winawkage16', 'tshirt', 'tsunami', 'tt', 'ttyl', 'tue', 'tuesday', 'tui', 'tuition', 'tul', 'tulip', 'tund', 'tune', 'tunji', 'turkey', 'turn', 'tuth', 'tv', 'tvhe', 'tvlol', 'twat', 'twelv', 'twenti', 'twice', 'twigg', 'twilight', 'twin', 'twink', 'twitter', 'two', 'tx', 'txt', 'txt250com', 'txtauction', 'txtauctiontxt', 'txtin', 'txting', 'txtjourney', 'txtno', 'txtx', 'tyler', 'type', 'typelyk', 'typic', 'u', 'u2moro', 'u4', 'uawakefeellikw', 'ubandu', 'ubi', 'ucal', 'ufind', 'ugadi', 'ugh', 'ugo', 'uh', 'uhhhhrmm', 'uif', 'uin', 'ujhhhhhhh', 'uk', 'ukmobiled', 'ukp2000', 'ull', 'ultim', 'ultimatum', 'um', 'umma', 'ummmawil', 'ummmmmaah', 'un', 'unabl', 'unbeliev', 'uncl', 'unclaim', 'uncomfort', 'uncondit', 'unconsci', 'unconvinc', 'uncount', 'uncut', 'underdtand', 'understand', 'understood', 'underwear', 'undrstnd', 'undrstndng', 'unemploy', 'unev', 'unfold', 'unfortun', 'unfortuntli', 'unhappi', 'uni', 'unicef', 'uniform', 'unintent', 'uniqu', 'uniquei', 'unit', 'univ', 'univers', 'unknown', 'unless', 'unlik', 'unlimit', 'unmit', 'unnecessarili', 'unni', 'unrecogn', 'unredeem', 'unsecur', 'unsold', 'unsoldmik', 'unsoldnow', 'unspoken', 'unsub', 'unsubscrib', 'unusu', 'uothrwis', 'up', 'up4', 'upcharg', 'upd8', 'updat', 'updatenow', 'upgrad', 'upgrdcentr', 'uphad', 'upload', 'upnot', 'upon', 'upset', 'upseti', 'upsetit', 'upstair', 'upto', 'uptown', 'upyeh', 'ur', 'ure', 'urfeel', 'urgent', 'urgentbut', 'urgentlyit', 'urgh', 'urgnt', 'urgoin', 'urgran', 'urin', 'url', 'urmomi', 'urn', 'urself', 'us', 'usb', 'usc', 'uscedu', 'use', 'useless', 'user', 'usf', 'usget', 'usher', 'uslet', 'usml', 'usno', 'uso', 'usp', 'usual', 'usualiam', 'uteru', 'utter', 'uu', 'uup', 'uv', 'uve', 'uwana', 'uwant', 'uworld', 'uxxxx', 'v', 'vaazhthukk', 'vagu', 'vai', 'vale', 'valentin', 'valid', 'valid12hr', 'valu', 'valuabl', 'valuemorn', 'varaya', 'vargu', 'vari', 'variou', 'varma', 'vasai', 'vat', 'vatian', 'vava', 'vco', 'vday', 'vega', 'veget', 'veggi', 'vehicl', 'velacheri', 'velli', 'velusami', 'venaam', 'venugop', 'verifi', 'version', 'versu', 'vettam', 'vewi', 'via', 'vibrant', 'vibrat', 'vic', 'victor', 'victoria', 'vid', 'video', 'videochat', 'videop', 'videophon', 'videosound', 'videosounds2', 'vidnot', 'view', 'vijay', 'vijaykanth', 'vikki', 'vikkyim', 'vilikkamt', 'vill', 'villa', 'villag', 'vinobanagar', 'violat', 'violenc', 'violet', 'vip', 'virgil', 'virgin', 'virtual', 'visa', 'visionsmscom', 'visit', 'visitne', 'visitor', 'vital', 'vitamin', 'viva', 'vivek', 'vivekanand', 'viveki', 'vl', 'vldo', 'voda', 'vodafon', 'vodka', 'voic', 'voicemail', 'voila', 'volcano', 'vomit', 'vomitin', 'vote', 'voucher', 'voucherstext', 'vpist', 'vpod', 'vri', 'vs', 'vth', 'vtire', 'vu', 'w', 'w111wx', 'w14rg', 'w1a', 'w1j', 'w1t1ji', 'w4', 'w45wq', 'w8in', 'wa', 'wa14', 'waaaat', 'wad', 'wadebridgei', 'wah', 'wahala', 'wahay', 'wahe', 'waheeda', 'wahleykkumshar', 'waht', 'wait', 'waiti', 'waitin', 'waitshould', 'waitu', 'wake', 'wale', 'walik', 'walk', 'walkabout', 'walkin', 'wall', 'wallet', 'wallpap', 'wallpaperal', 'walmart', 'walsal', 'wamma', 'wan', 'wan2', 'wana', 'wanna', 'wannatel', 'want', 'want2com', 'wap', 'waqt', 'warm', 'warn', 'warner', 'warranti', 'warwick', 'washob', 'wasnt', 'wast', 'wat', 'watch', 'watchin', 'watchng', 'wate', 'water', 'watev', 'watevr', 'watll', 'watrdayno', 'watt', 'wave', 'way', 'way2smscom', 'waythi', 'wc', 'wc1n', 'wc1n3xx', 'weak', 'weapon', 'wear', 'weasel', 'weather', 'web', 'web2mobil', 'webadr', 'webeburnin', 'webpag', 'websit', 'websitenow', 'wed', 'weddin', 'weddingfriend', 'wedlunch', 'wednesday', 'wee', 'weed', 'weeddefici', 'week', 'weekday', 'weekend', 'weekli', 'weekstop', 'weigh', 'weight', 'weighthaha', 'weightloss', 'weird', 'weirdest', 'weirdi', 'weirdo', 'weiyi', 'welcom', 'well', 'wellda', 'welli', 'welltak', 'wellyou', 'welp', 'wen', 'wendi', 'wenev', 'went', 'wenwecan', 'wer', 'werear', 'werebor', 'werent', 'wereth', 'wesley', 'west', 'western', 'westlif', 'westonzoyland', 'westshor', 'wet', 'wetherspoon', 'weve', 'wewa', 'whassup', 'what', 'whatev', 'whatsup', 'wheat', 'wheel', 'wheellock', 'when', 'whenev', 'whenevr', 'whenr', 'whenwher', 'where', 'wherear', 'wherebtw', 'wherev', 'wherevr', 'wherr', 'whether', 'whileamp', 'whilltak', 'whisper', 'white', 'whn', 'who', 'whole', 'whore', 'whose', 'whr', 'wi', 'wick', 'wicket', 'wicklow', 'wid', 'widelivecomindex', 'wif', 'wife', 'wifedont', 'wifehow', 'wifi', 'wihtuot', 'wikipediacom', 'wil', 'wild', 'wildest', 'wildlif', 'will', 'willpow', 'win', 'win150ppmx3age16', 'wind', 'windi', 'window', 'wine', 'wing', 'winner', 'winnersclub', 'winterston', 'wipe', 'wipro', 'wiproy', 'wire3net', 'wisdom', 'wise', 'wish', 'wishin', 'wishlist', 'wiskey', 'wit', 'withdraw', 'wither', 'within', 'without', 'witin', 'witot', 'witout', 'wiv', 'wizzl', 'wk', 'wkend', 'wkent150p16', 'wkg', 'wkli', 'wknd', 'wktxt', 'wlcome', 'wld', 'wmlid1b6a5ecef91ff937819firsttrue180430jul05', 'wmlid820554ad0a1705572711firsttru', 'wn', 'wnevr', 'wnt', 'wo', 'woah', 'wocay', 'woke', 'woken', 'woman', 'womdarful', 'women', 'wondar', 'wondarful', 'wonder', 'wont', 'woo', 'wood', 'woodland', 'woohoo', 'woot', 'woould', 'woozl', 'worc', 'word', 'wordcollect', 'wordnot', 'wordsevri', 'wordstart', 'work', 'workag', 'workand', 'workin', 'worklov', 'workout', 'world', 'worldgnun', 'worldmay', 'worldveri', 'worm', 'worri', 'worriedx', 'worryc', 'worryus', 'wors', 'worst', 'worth', 'worthless', 'wot', 'wotu', 'wotz', 'woul', 'would', 'woulda', 'wouldnt', 'wound', 'wow', 'wquestion', 'wrc', 'wreck', 'wrench', 'wright', 'write', 'writh', 'wrk', 'wrki', 'wrkin', 'wrking', 'wrld', 'wrnog', 'wrong', 'wrongli', 'wrongtak', 'wrote', 'ws', 'wt', 'wtc', 'wtf', 'wth', 'wthout', 'wud', 'wudnt', 'wuld', 'wuldnt', 'wun', 'www07781482378com', 'www4tcbiz', 'www80488biz', 'wwwapplausestorecom', 'wwwareyouuniquecouk', 'wwwasjesuscom', 'wwwb4utelecom', 'wwwbridalpetticoatdreamscouk', 'wwwcashbincouk', 'wwwclubmobycom', 'wwwclubzedcouk', 'wwwcnupdatescomnewslett', 'wwwcomuknet', 'wwwdbuknet', 'wwwflirtpartyu', 'wwwfullonsmscom', 'wwwgambtv', 'wwwgetzedcouk', 'wwwidewcom', 'wwwldewcom', 'wwwldewcom1win150ppmx3age16', 'wwwldewcom1win150ppmx3age16subscript', 'wwwldewcomsubs161win150ppmx3', 'wwwmovietriviatv', 'wwwmusictrivianet', 'wwworangecoukow', 'wwwphb1com', 'wwwregalportfoliocouk', 'wwwringtonekingcouk', 'wwwringtonescouk', 'wwwrtfsphostingcom', 'wwwsantacallingcom', 'wwwshortbreaksorguk', 'wwwsmsacubootydeli', 'wwwsmsacugoldvik', 'wwwsmsacuhmmross', 'wwwsmsacunat27081980', 'wwwsmsacunatalie2k9', 'wwwsmsconet', 'wwwtcbiz', 'wwwtelediscountcouk', 'wwwtextcompcom', 'wwwtextpodnet', 'wwwtklscom', 'wwwtxt2shopcom', 'wwwtxt43com', 'wwwtxt82228com', 'wwwtxttowincouk', 'wwwwin82050couk', 'wyli', 'x', 'x2', 'x29', 'x49', 'x49your', 'xafter', 'xam', 'xavier', 'xchat', 'xclusiveclubsaisai', 'xin', 'xma', 'xnet', 'xoxo', 'xt', 'xuhui', 'xx', 'xxsp', 'xxuk', 'xxx', 'xxxmobilemovieclub', 'xxxmobilemovieclubcomnqjkgighjjgcbl', 'xxxx', 'xxxxx', 'xxxxxx', 'xxxxxxx', 'xxxxxxxx', 'xxxxxxxxxxxxxx', 'xy', 'y87', 'ya', 'yago', 'yah', 'yahoo', 'yalrigu', 'yalru', 'yam', 'yan', 'yar', 'yard', 'yavnt', 'yaxx', 'yaxxx', 'yay', 'yck', 'yday', 'ye', 'yeah', 'yeahand', 'year', 'yeesh', 'yeh', 'yell', 'yellow', 'yelowi', 'yen', 'yeovil', 'yep', 'yer', 'yes165', 'yes434', 'yes440', 'yes762', 'yes910', 'yesbut', 'yesfrom', 'yesgauti', 'yesh', 'yesher', 'yesim', 'yesmum', 'yessura', 'yest', 'yesterday', 'yet', 'yetti', 'yetund', 'yi', 'yifeng', 'yiju', 'yijuehotmailcom', 'ym', 'ymca', 'yo', 'yoga', 'yogasana', 'yoher', 'yor', 'yorg', 'youani', 'youcarlo', 'youclean', 'youd', 'youdearwith', 'youdo', 'youhow', 'youi', 'youkwher', 'yould', 'youll', 'youmi', 'youmoney', 'young', 'younger', 'youphon', 'your', 'yourinclus', 'yourjob', 'youso', 'youthat', 'youto', 'youuuuu', 'youv', 'youwanna', 'youwhen', 'yovil', 'yowif', 'yoyyooo', 'yr', 'ystrdayic', 'yummi', 'yummmm', 'yun', 'yunni', 'yuo', 'yuou', 'yup', 'yupz', 'ywhere', 'z', 'zac', 'zaher', 'zealand', 'zebra', 'zed', 'zero', 'zhong', 'zindgi', 'zoe', 'zogtoriu', 'zoom', 'zouk', 'zyada', 'é', 'ü', 'üll', '〨ud']\n"
     ]
    }
   ],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "\n",
    "count_vect = CountVectorizer(analyzer=clean_text)\n",
    "X_counts = count_vect.fit_transform(data['body_text'])\n",
    "print(X_counts.shape)\n",
    "print(count_vect.get_feature_names())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Apply CountVectorizer to smaller sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(20, 192)\n",
      "['08002986030', '08452810075over18', '09061701461', '1', '100', '100000', '11', '12', '150pday', '16', '2', '20000', '2005', '21st', '3', '4', '4403ldnw1a7rw18', '4txtú120', '6day', '81010', '87077', '87121', '87575', '9', '900', 'aft', 'aid', 'alreadi', 'alright', 'anymor', 'appli', 'ard', 'around', 'b', 'brother', 'call', 'caller', 'callertun', 'camera', 'cash', 'chanc', 'claim', 'click', 'co', 'code', 'colour', 'comin', 'comp', 'copi', 'cost', 'credit', 'cri', 'csh11', 'cup', 'custom', 'da', 'date', 'dont', 'eg', 'eh', 'england', 'enough', 'entitl', 'entri', 'even', 'fa', 'feel', 'ffffffffff', 'final', 'fine', 'finish', 'first', 'free', 'friend', 'go', 'goalsteam', 'goe', 'gonna', 'gota', 'ha', 'hl', 'home', 'hour', 'httpwap', 'im', 'info', 'ive', 'jackpot', 'joke', 'k', 'kim', 'kl341', 'lar', 'latest', 'lccltd', 'like', 'link', 'live', 'lor', 'lunch', 'macedonia', 'make', 'may', 'meet', 'mell', 'membership', 'messag', 'minnaminungint', 'miss', 'mobil', 'month', 'nah', 'name', 'nation', 'naughti', 'network', 'news', 'next', 'nurungu', 'oh', 'oru', 'patent', 'pay', 'per', 'pobox', 'poboxox36504w45wq', 'pound', 'press', 'prize', 'questionstd', 'r', 'ratetc', 'receiv', 'receivea', 'rememb', 'repli', 'request', 'reward', 'scotland', 'select', 'send', 'serious', 'set', 'six', 'smth', 'soon', 'sooner', 'speak', 'spell', 'stock', 'str', 'stuff', 'sunday', 'talk', 'tc', 'team', 'text', 'think', 'though', 'tkt', 'today', 'tonight', 'treat', 'tri', 'trywal', 'tsandc', 'txt', 'u', 'updat', 'ur', 'urgent', 'use', 'usf', 'v', 'valid', 'valu', 'vettam', 'want', 'wap', 'watch', 'way', 'week', 'wet', 'win', 'winner', 'wkli', 'word', 'wwwdbuknet', 'xxxmobilemovieclub', 'xxxmobilemovieclubcomnqjkgighjjgcbl', 'ye', 'ü']\n"
     ]
    }
   ],
   "source": [
    "data_sample = data[0:20]\n",
    "\n",
    "count_vect_sample = CountVectorizer(analyzer=clean_text)\n",
    "X_counts_sample = count_vect_sample.fit_transform(data_sample['body_text'])\n",
    "print(X_counts_sample.shape)\n",
    "print(count_vect_sample.get_feature_names())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vectorizers output sparse matrices\n",
    "\n",
    "_**Sparse Matrix**: A matrix in which most entries are 0. In the interest of efficient storage, a sparse matrix will be stored by only storing the locations of the non-zero elements._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<20x192 sparse matrix of type '<class 'numpy.int64'>'\n",
       "\twith 218 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_counts_sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 192 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    0    1    2    3    4    5    6    7    8    9   ...   182  183  184  185  \\\n",
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       "7     0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "8     0    0    0    0    1    0    0    0    1    1 ...     0    1    0    0   \n",
       "9     0    0    0    1    0    1    0    0    0    0 ...     0    0    0    0   \n",
       "10    0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "11    0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "12    0    0    0    0    0    0    0    0    0    0 ...     1    0    0    0   \n",
       "13    0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "14    0    0    0    0    0    0    0    0    0    1 ...     0    0    0    0   \n",
       "15    0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "16    0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "17    0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "18    0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "19    0    0    0    0    0    0    0    0    0    0 ...     0    0    0    0   \n",
       "\n",
       "    186  187  188  189  190  191  \n",
       "0     0    0    0    0    0    0  \n",
       "1     0    0    0    0    0    0  \n",
       "2     0    0    0    0    0    0  \n",
       "3     0    0    0    0    0    0  \n",
       "4     0    0    0    0    0    0  \n",
       "5     0    0    0    0    0    0  \n",
       "6     0    0    0    0    0    0  \n",
       "7     0    0    0    0    0    0  \n",
       "8     0    0    0    0    0    0  \n",
       "9     1    1    0    0    0    0  \n",
       "10    0    0    1    1    0    0  \n",
       "11    0    0    0    0    0    0  \n",
       "12    0    0    0    0    1    0  \n",
       "13    0    0    0    0    0    0  \n",
       "14    0    0    0    0    0    0  \n",
       "15    0    0    0    0    0    0  \n",
       "16    0    0    0    0    0    0  \n",
       "17    0    0    0    0    0    1  \n",
       "18    0    0    0    0    0    0  \n",
       "19    0    0    0    0    0    0  \n",
       "\n",
       "[20 rows x 192 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_counts_df = pd.DataFrame(X_counts_sample.toarray())\n",
    "X_counts_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 192 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    08002986030  08452810075over18  09061701461  1  100  100000  11  12  \\\n",
       "0             0                  1            0  0    0       0   0   0   \n",
       "1             0                  0            0  0    0       0   0   0   \n",
       "2             0                  0            0  0    0       0   0   0   \n",
       "3             0                  0            0  0    0       0   0   0   \n",
       "4             0                  0            0  0    0       0   0   0   \n",
       "5             0                  0            1  0    0       0   0   1   \n",
       "6             1                  0            0  0    0       0   1   0   \n",
       "7             0                  0            0  0    0       0   0   0   \n",
       "8             0                  0            0  0    1       0   0   0   \n",
       "9             0                  0            0  1    0       1   0   0   \n",
       "10            0                  0            0  0    0       0   0   0   \n",
       "11            0                  0            0  0    0       0   0   0   \n",
       "12            0                  0            0  0    0       0   0   0   \n",
       "13            0                  0            0  0    0       0   0   0   \n",
       "14            0                  0            0  0    0       0   0   0   \n",
       "15            0                  0            0  0    0       0   0   0   \n",
       "16            0                  0            0  0    0       0   0   0   \n",
       "17            0                  0            0  0    0       0   0   0   \n",
       "18            0                  0            0  0    0       0   0   0   \n",
       "19            0                  0            0  0    0       0   0   0   \n",
       "\n",
       "    150pday  16 ...  wet  win  winner  wkli  word  wwwdbuknet  \\\n",
       "0         0   0 ...    0    1       0     1     0           0   \n",
       "1         0   0 ...    0    0       0     0     0           0   \n",
       "2         0   0 ...    0    0       0     0     0           0   \n",
       "3         0   0 ...    0    0       0     0     0           0   \n",
       "4         0   0 ...    0    0       0     0     0           0   \n",
       "5         0   0 ...    0    0       1     0     0           0   \n",
       "6         0   0 ...    0    0       0     0     0           0   \n",
       "7         0   0 ...    0    0       0     0     0           0   \n",
       "8         1   1 ...    0    1       0     0     0           0   \n",
       "9         0   0 ...    0    0       0     0     1           1   \n",
       "10        0   0 ...    0    0       0     0     0           0   \n",
       "11        0   0 ...    0    0       0     0     0           0   \n",
       "12        0   0 ...    1    0       0     0     0           0   \n",
       "13        0   0 ...    0    0       0     0     0           0   \n",
       "14        0   1 ...    0    0       0     0     0           0   \n",
       "15        0   0 ...    0    0       0     0     0           0   \n",
       "16        0   0 ...    0    0       0     0     0           0   \n",
       "17        0   0 ...    0    0       0     0     0           0   \n",
       "18        0   0 ...    0    0       0     0     0           0   \n",
       "19        0   0 ...    0    0       0     0     0           0   \n",
       "\n",
       "    xxxmobilemovieclub  xxxmobilemovieclubcomnqjkgighjjgcbl  ye  ü  \n",
       "0                    0                                    0   0  0  \n",
       "1                    0                                    0   0  0  \n",
       "2                    0                                    0   0  0  \n",
       "3                    0                                    0   0  0  \n",
       "4                    0                                    0   0  0  \n",
       "5                    0                                    0   0  0  \n",
       "6                    0                                    0   0  0  \n",
       "7                    0                                    0   0  0  \n",
       "8                    0                                    0   0  0  \n",
       "9                    0                                    0   0  0  \n",
       "10                   1                                    1   0  0  \n",
       "11                   0                                    0   0  0  \n",
       "12                   0                                    0   1  0  \n",
       "13                   0                                    0   0  0  \n",
       "14                   0                                    0   0  0  \n",
       "15                   0                                    0   0  0  \n",
       "16                   0                                    0   0  0  \n",
       "17                   0                                    0   0  1  \n",
       "18                   0                                    0   0  0  \n",
       "19                   0                                    0   0  0  \n",
       "\n",
       "[20 rows x 192 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_counts_df.columns = count_vect_sample.get_feature_names()\n",
    "X_counts_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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