# Notebook from manjalshah/Machine-learning
Path: Projects/Twitter_user_gender_prediction/Twitter_user_gender_prediction.ipynb

<code>
import pandas as pd
from sklearn import metrics
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import CountVectorizer
import nltk     # It is the one of most comman libraries for Natural Language Process
import re       # Regular Expression library
_____no_output_____data = pd.read_csv('gender-classifier-DFE-791531.csv',encoding='latin-1')
print(data.shape)
data.head()(20050, 26)
data = pd.concat([data.gender, data.text], axis=1)    # We are taking only text and gender data to train model
data.dropna(axis = 0, inplace = True)                 # We dropped the null rows
data.info()<class 'pandas.core.frame.DataFrame'>
Int64Index: 19953 entries, 0 to 20049
Data columns (total 2 columns):
 #   Column  Non-Null Count  Dtype
---  ------  --------------  -----
 0   gender  19953 non-null  object
 1   text    19953 non-null  object
dtypes: object(2)
memory usage: 467.6+ KB
data.gender = [1 if gender == "female" else 0 for gender in data.gender]
print(data.gender.value_counts())0    13253
1     6700
Name: gender, dtype: int64
# To download ntlk packages which we are going to use here.
nltk.download("stopwords")
nltk.download('punkt')
nltk.download('wordnet')[nltk_data] Downloading package stopwords to
[nltk_data]     C:\Users\Admin\AppData\Roaming\nltk_data...
[nltk_data]   Package stopwords is already up-to-date!
[nltk_data] Downloading package punkt to
[nltk_data]     C:\Users\Admin\AppData\Roaming\nltk_data...
[nltk_data]   Package punkt is already up-to-date!
[nltk_data] Downloading package wordnet to
[nltk_data]     C:\Users\Admin\AppData\Roaming\nltk_data...
[nltk_data]   Package wordnet is already up-to-date!
text_list = []                             # We created a list so we after these steps, we will append into this list
for text in data.text:
    text = re.sub("[^a-zA-Z]", " ", text)  # Sub method finds the given pattern ([^a-zA-Z] means, NOT letter like ":") and changes them with " " (space)
    text = text.lower()                    # We need to have all letters lowercase (because A is not equall to a)
    text = nltk.word_tokenize(text)        # We make a word list from our text
    lemma = nltk.WordNetLemmatizer()
    text = [lemma.lemmatize(word) for word in text]     # We found the roots of each words with lemma
    text = " ".join(text)                  # After all these steps,we joined the words together and remake our text.
    text_list.append(text)                 # Append these texts into the list we created._____no_output_____# Now, we will implement "bag of words" method

max_features = 10000               # We will take top 10000 feature

cv = CountVectorizer(max_features=max_features, stop_words = "english")
# In this method, we remove the stopwords (irrelevant words) in English language. (like "of", "and", "the" etc.)

sparce_matrix = cv.fit_transform(text_list).toarray()
print("top used {} words: {}".format(max_features, cv.get_feature_names()))top used 10000 words: ['aa', 'aaron', 'ab', 'abandoned', 'abba', 'abbott', 'abby', 'abc', 'ability', 'able', 'ableg', 'abortion', 'abraham', 'absolute', 'absolutely', 'abt', 'abu', 'abuja', 'abuse', 'ac', 'aca', 'academic', 'academy', 'acc', 'accent', 'accept', 'acceptable', 'acceptance', 'accepted', 'accepting', 'access', 'accessing', 'accessory', 'accident', 'accidentally', 'accomplishment', 'according', 'account', 'accountable', 'accounting', 'acct', 'accurate', 'accused', 'ace', 'ache', 'achieve', 'achieved', 'achievement', 'acoustic', 'act', 'actin', 'acting', 'action', 'active', 'activist', 'activity', 'actor', 'actress', 'actual', 'actually', 'ad', 'adam', 'add', 'added', 'addict', 'addicted', 'addiction', 'addictive', 'adding', 'addition', 'additional', 'address', 'adelaide', 'adele', 'adidas', 'admin', 'administration', 'admiration', 'admire', 'admission', 'admit', 'adonissuperman', 'adoption', 'adorable', 'adore', 'adrian', 'adrianteakdesk', 'adsh', 'adult', 'adulting', 'advance', 'advanced', 'advancing', 'advantage', 'adventure', 'adverse', 'adversity', 'advert', 'advertise', 'advertising', 'advice', 'advised', 'advising', 'advisor', 'advisory', 'advocating', 'ae', 'aerlingus', 'aesthetic', 'af', 'afc', 'afcfylde', 'affa', 'affair', 'affect', 'affected', 'affection', 'affiliate', 'affiliated', 'afford', 'affordable', 'affordablecareact', 'afghanistan', 'afifest', 'afneil', 'afraid', 'africa', 'african', 'afrikan', 'aft', 'afterlife', 'afternoon', 'ag', 'age', 'aged', 'ageing', 'agency', 'agenda', 'agent', 'aggressive', 'aggy', 'ago', 'agoldthatactuallystays', 'agree', 'agreed', 'agreement', 'agrees', 'agricultural', 'agriculture', 'aguilera', 'ah', 'aha', 'ahah', 'ahaha', 'ahahaha', 'ahahahaha', 'ahead', 'ahh', 'ahhh', 'ahmed', 'ahr', 'ahs', 'ai', 'aic', 'aid', 'aiden', 'aig', 'aight', 'ailment', 'aim', 'aimed', 'aimhbread', 'ain', 'aint', 'air', 'airbnb', 'aircanada', 'aircraft', 'airing', 'airline', 'airport', 'airway', 'aisle', 'aj', 'ajdabiya', 'ajek', 'ajhtga', 'ak', 'aka', 'akaworldwise', 'akhromatos', 'al', 'alabama', 'alan', 'alarm', 'alarmed', 'alaska', 'albert', 'alberta', 'album', 'alcohol', 'aldemir', 'aldo', 'aldubpredictions', 'alec', 'alert', 'alex', 'alexa', 'alexander', 'alexandre', 'alexia', 'alexis', 'alexmoore', 'algorithm', 'ali', 'alice', 'alicia', 'alien', 'aline', 'alison', 'alive', 'allah', 'allan', 'allblacks', 'alldaybreakfast', 'allegation', 'alleged', 'allegedly', 'allen', 'allergy', 'alleviate', 'alliance', 'allie', 'alliedeep', 'alll', 'allow', 'allowed', 'allowing', 'allows', 'ally', 'alma', 'aloe', 'alongside', 'alot', 'alpaca', 'alpha', 'alphabet', 'alright', 'alt', 'alternative', 'alubarna', 'alumnus', 'alwys', 'alzheimer', 'amal', 'amanda', 'amara', 'amas', 'amateur', 'amaze', 'amazes', 'amazing', 'amazon', 'ambassador', 'amber', 'ambiguity', 'ambition', 'amc', 'amctalkingdead', 'ame', 'amelia', 'amen', 'amendment', 'america', 'american', 'amnesty', 'amp', 'amwriting', 'amy', 'ana', 'anal', 'analysis', 'analyst', 'analytics', 'anatomy', 'anc', 'ancient', 'anderson', 'andre', 'andreasson', 'andrew', 'android', 'androidgames', 'andy', 'anent', 'anesthesia', 'ang', 'angebotsende', 'angel', 'angeles', 'angelica', 'anger', 'angie', 'angle', 'angry', 'ani', 'animal', 'animated', 'anime', 'anm', 'ann', 'anna', 'anne', 'annemariepotgi', 'annette', 'anniversary', 'announce', 'announced', 'announcement', 'announces', 'announcing', 'annoy', 'annoyed', 'annoying', 'annual', 'anomaly', 'anonymous', 'answer', 'answered', 'ant', 'anthony', 'anti', 'anticipate', 'anticipated', 'antioch', 'antique', 'antonio', 'anxiety', 'anxious', 'anybody', 'anymore', 'anyones', 'anypony', 'anytime', 'anyways', 'ao', 'ap', 'apart', 'apartment', 'apc', 'apexiscool', 'apfexgwda', 'apocalypse', 'apologise', 'apologize', 'apologizing', 'apology', 'apostrophe', 'app', 'apparel', 'apparently', 'appbounty', 'appear', 'appearance', 'appeared', 'appetizer', 'apple', 'applebees', 'application', 'applied', 'applies', 'apply', 'applying', 'appointed', 'appointment', 'appreciate', 'appreciated', 'appreciation', 'approach', 'approaching', 'appropriate', 'approval', 'approve', 'approved', 'approx', 'apps', 'appstore', 'apr', 'april', 'apush', 'apxiplcr', 'aq', 'aquarium', 'aqw', 'ar', 'arab', 'arabia', 'arabieila', 'arc', 'arch', 'archie', 'architect', 'architecture', 'archive', 'arduino', 'area', 'aren', 'arena', 'arenado', 'arent', 'arg', 'argue', 'argues', 'arguing', 'argument', 'argyle', 'aria', 'arian', 'ariana', 'arianagrande', 'arielrae', 'aries', 'aristotle', 'arizona', 'arlong', 'arm', 'armaan', 'armed', 'armor', 'armpit', 'armstrong', 'army', 'aromatherapy', 'arrange', 'arrangement', 'arrested', 'arrival', 'arrive', 'arrived', 'arrives', 'arriving', 'arrogant', 'arse', 'arsenal', 'art', 'arthur', 'article', 'artist', 'artiste', 'artisticzayn', 'artistoftheyear', 'artistry', 'artwork', 'aru', 'arvixe', 'asa', 'asap', 'asf', 'ash', 'ashamed', 'ashanti', 'ashley', 'ashleymadison', 'ashton', 'asia', 'asian', 'aside', 'ask', 'askari', 'asked', 'asking', 'asks', 'askussegl', 'asleep', 'aspect', 'ass', 'assad', 'assassin', 'assault', 'assaulted', 'assembly', 'assessment', 'asset', 'asshole', 'assignment', 'assist', 'assistant', 'assisted', 'associate', 'associated', 'association', 'assorted', 'assume', 'assumed', 'assuming', 'asterisk', 'astro', 'asu', 'aswell', 'asylum', 'ate', 'atem', 'atheist', 'athlete', 'athletic', 'atl', 'atlanta', 'atlantic', 'atleast', 'atm', 'atmosphere', 'atom', 'atomarchaeology', 'atomic', 'atrium', 'attached', 'attack', 'attacked', 'attain', 'attempt', 'attempted', 'attempting', 'attend', 'attendant', 'attended', 'attendee', 'attending', 'attention', 'atti', 'atticus', 'attitude', 'attorney', 'attract', 'attractive', 'atxjobs', 'aty', 'au', 'auction', 'auctioned', 'aud', 'audacity', 'audience', 'audio', 'audiobook', 'audrey', 'august', 'aunt', 'aunty', 'aurora', 'aussie', 'aust', 'austin', 'austinmahone', 'australia', 'australian', 'author', 'authority', 'authorrcmartin', 'authorscafe', 'autism', 'autistic', 'auto', 'autocorrect', 'autograph', 'automatically', 'automation', 'automotive', 'autumn', 'av', 'availability', 'available', 'ave', 'avenger', 'avenue', 'average', 'avfc', 'avi', 'aviation', 'avimayer', 'avocado', 'avoid', 'avoided', 'avoiding', 'avx', 'aw', 'await', 'awaited', 'awaiting', 'awaits', 'awake', 'awakening', 'awakens', 'award', 'aware', 'awareness', 'away', 'awe', 'awesome', 'awful', 'awh', 'awhile', 'awkward', 'aww', 'awww', 'ax', 'axel', 'ay', 'aye', 'ayee', 'az', 'azalea', 'ba', 'babe', 'baby', 'babygirl', 'babysitting', 'bachelor', 'backed', 'background', 'backlash', 'backpack', 'backroom', 'backstage', 'backstory', 'backtothefuture', 'backup', 'backwards', 'backyard', 'bacon', 'bad', 'badass', 'baddie', 'badge', 'badlands', 'badly', 'badoo', 'bae', 'baffled', 'bag', 'bagel', 'bagh', 'bah', 'bahamas', 'baileemadison', 'bailey', 'baileyjaytweets', 'bait', 'bajrangi', 'bake', 'baked', 'baker', 'baking', 'balamory', 'balance', 'bald', 'ball', 'ballet', 'balling', 'balloon', 'ballpool', 'balm', 'balmainxhmregentstreet', 'baltimore', 'bam', 'ban', 'banana', 'bancodeseries', 'band', 'bang', 'banged', 'bangle', 'banjo', 'bank', 'banking', 'banned', 'banning', 'bantasocialtv', 'banter', 'bap', 'bar', 'barabiredtata', 'barack', 'barbell', 'barber', 'barbie', 'barbra', 'barca', 'barcelona', 'barclays', 'bardonecchia', 'bare', 'barely', 'bargain', 'barley', 'barlow', 'barna', 'barnes', 'baron', 'baroness', 'barre', 'barrett', 'barricade', 'barrier', 'barrymore', 'bart', 'barteca', 'base', 'baseball', 'based', 'basement', 'basic', 'basically', 'basil', 'basis', 'basket', 'basketball', 'bass', 'bassem', 'bassey', 'bastard', 'bastion', 'bat', 'bath', 'bathroom', 'batman', 'batter', 'battery', 'batting', 'battle', 'battlefield', 'bay', 'baylor', 'bb', 'bbc', 'bbcafrica', 'bbclaurak', 'bbcnews', 'bbcone', 'bbq', 'bbrosh', 'bby', 'bbysoold', 'bc', 'bcbs', 'bcplace', 'bcs', 'bcus', 'bcuz', 'bd', 'bday', 'bderrington', 'bdib', 'bdo', 'beach', 'beacon', 'bead', 'beam', 'bean', 'beanie', 'bear', 'beard', 'bease', 'beast', 'beastin', 'beat', 'beaten', 'beating', 'beatles', 'beattie', 'beautiful', 'beautifully', 'beauty', 'beb', 'beck', 'beckham', 'beckons', 'becky', 'bed', 'bedding', 'bedroom', 'bee', 'beef', 'beelinegames', 'beep', 'beer', 'beetlejuice', 'beg', 'began', 'begging', 'beggining', 'begin', 'beginner', 'beginning', 'begs', 'begun', 'behave', 'behavior', 'behavioral', 'behaviour', 'beheard', 'behindthescenes', 'beige', 'beijing', 'beingsalmankhan', 'beirut', 'belief', 'believe', 'believer', 'believing', 'bell', 'bella', 'bellucci', 'belly', 'belong', 'belt', 'ben', 'bench', 'bend', 'benefit', 'bengal', 'benghazi', 'benin', 'benjamin', 'berkeley', 'berners', 'bernie', 'berry', 'best', 'bestest', 'bestfriend', 'bestfriends', 'bestie', 'bestselling', 'besttalkradio', 'bet', 'beta', 'beth', 'bethlehem', 'better', 'bey', 'beyonc', 'beyonce', 'bf', 'bfbexh', 'bff', 'bg', 'bh', 'bi', 'biafra', 'bias', 'bible', 'bid', 'bieber', 'big', 'bigger', 'biggest', 'biglari', 'bignaturals', 'bigtits', 'bih', 'bihar', 'bike', 'biker', 'bikini', 'billboard', 'billion', 'billy', 'bin', 'bindi', 'binge', 'bingo', 'bio', 'biological', 'biology', 'bird', 'birmingham', 'birth', 'birthday', 'biscuit', 'bish', 'bishop', 'bison', 'bispak', 'bit', 'bitch', 'bitcoin', 'bite', 'bitter', 'biz', 'bizarre', 'bj', 'bjp', 'bk', 'bl', 'black', 'blackberry', 'blackfish', 'blacklist', 'blackrepublican', 'blade', 'blair', 'blake', 'blame', 'blamed', 'blank', 'blanket', 'blast', 'blasted', 'blasting', 'blatantly', 'bleach', 'bleed', 'bleeding', 'blend', 'blending', 'bless', 'blessed', 'blessing', 'blew', 'blind', 'bling', 'blink', 'bliss', 'blizzard', 'bloc', 'block', 'blocked', 'blocking', 'blog', 'blogger', 'blogging', 'bloglovin', 'blond', 'blonde', 'blood', 'bloody', 'bloomberg', 'blow', 'blowing', 'blowjob', 'blown', 'blu', 'blue', 'blueberry', 'bluejays', 'blunt', 'blurred', 'blushing', 'bm', 'bn', 'bna', 'bo', 'board', 'boardgamehour', 'boat', 'bob', 'bobby', 'body', 'bodybuilding', 'bodycams', 'boe', 'boil', 'bokep', 'boko', 'bold', 'bologna', 'bolton', 'bomb', 'bomber', 'bond', 'bone', 'bonfire', 'bonus', 'boo', 'boob', 'book', 'booked', 'booking', 'boom', 'boost', 'booster', 'boot', 'booth', 'booty', 'booze', 'border', 'bored', 'boredom', 'boring', 'borland', 'born', 'borno', 'bos', 'bosch', 'boss', 'boston', 'bot', 'bother', 'bothered', 'bottle', 'bought', 'boulevard', 'bounce', 'bound', 'bounts', 'bout', 'bow', 'bowel', 'bowl', 'bowles', 'bowling', 'box', 'boxing', 'boy', 'boyfriend', 'bp', 'bpy', 'bq', 'br', 'bra', 'brace', 'bracelet', 'brad', 'bradford', 'bradley', 'brady', 'brag', 'brain', 'bran', 'branch', 'brand', 'branded', 'branding', 'brandon', 'brandy', 'branson', 'brat', 'brave', 'bravo', 'brawl', 'bray', 'brazenhunterdw', 'brazil', 'brazilian', 'brb', 'brd', 'bread', 'break', 'breakdown', 'breaker', 'breakfast', 'breaking', 'breast', 'breasted', 'breath', 'breathe', 'breathes', 'breathing', 'breed', 'breeze', 'breezie', 'brennan', 'brentford', 'brentwood', 'breslin', 'brew', 'brewer', 'brewery', 'breytonpaulse', 'brian', 'brick', 'bride', 'bridge', 'brien', 'brigade', 'bright', 'brighten', 'brighter', 'brightest', 'brilliance', 'brilliant', 'bring', 'bringing', 'bringit', 'brings', 'brink', 'brio', 'bris', 'britain', 'british', 'britney', 'britneyspears', 'britt', 'brittany', 'bro', 'broad', 'broadband', 'broadcast', 'broadly', 'broadway', 'broadwayhd', 'broccoli', 'brock', 'brocklesnar', 'broke', 'broken', 'broker', 'bronx', 'brony', 'brook', 'brooke', 'brookebcnn', 'brooklyn', 'bros', 'broth', 'brother', 'brotherhood', 'brought', 'brow', 'brown', 'brownie', 'browsing', 'bruce', 'bruh', 'brunch', 'brunette', 'bruno', 'brush', 'brushing', 'brussels', 'brutal', 'brutally', 'bryan', 'bryant', 'bt', 'btl', 'bts', 'btw', 'bu', 'bubble', 'buchanan', 'buck', 'bucket', 'buckeye', 'buckle', 'bud', 'buddha', 'buddhist', 'buddy', 'budget', 'buff', 'buffalo', 'buffer', 'buffy', 'bug', 'bugatti', 'buggy', 'bugil', 'buh', 'build', 'builder', 'building', 'built', 'buk', 'bull', 'bullet', 'bulletin', 'bullshit', 'bully', 'bullying', 'bum', 'bummed', 'bump', 'bumpin', 'bumping', 'bun', 'bunch', 'bundle', 'bundled', 'bungie', 'bunk', 'bunny', 'buq', 'burger', 'burgundy', 'buried', 'burn', 'burned', 'burning', 'burnout', 'burnt', 'burrito', 'burst', 'burton', 'burundi', 'bury', 'burying', 'bus', 'bush', 'busi', 'business', 'businessman', 'businessmgmt', 'bust', 'busted', 'busting', 'busty', 'bustyfriends', 'busy', 'butch', 'butcher', 'butler', 'butt', 'butter', 'butterfly', 'button', 'butwemaystill', 'buy', 'buyer', 'buying', 'buzz', 'buzzfeed', 'buzzing', 'bv', 'bw', 'bx', 'bxp', 'bye', 'byke', 'bz', 'ca', 'cable', 'caesar', 'cafe', 'cafeteria', 'cage', 'caitlyn', 'cake', 'cal', 'caleb', 'calendar', 'calf', 'calgary', 'cali', 'california', 'called', 'caller', 'calling', 'callofduty', 'callum', 'calm', 'calmed', 'calming', 'calorie', 'calum', 'calvin', 'cam', 'camaro', 'camaster', 'cambridge', 'camcorder', 'came', 'camelia', 'cameo', 'camera', 'cameron', 'camerondallas', 'camerons', 'camgirl', 'camp', 'campaign', 'campaigning', 'campbel', 'campbell', 'camping', 'campus', 'canada', 'canadian', 'cancel', 'cancelled', 'cancer', 'cancun', 'candice', 'candid', 'candidate', 'candle', 'candy', 'cane', 'cannabis', 'cannon', 'canny', 'canon', 'canvas', 'canwin', 'canyon', 'cap', 'capable', 'capacity', 'cape', 'capella', 'capital', 'capitalism', 'capitalismlover', 'capitalist', 'capitol', 'capsule', 'captain', 'caption', 'captivating', 'capture', 'car', 'cara', 'carb', 'carbs', 'carcinogen', 'carcinogenic', 'card', 'cardboard', 'carded', 'cardinal', 'care', 'cared', 'career', 'careerarc', 'careful', 'carefully', 'caregiver', 'carewest', 'carey', 'cargo', 'carhop', 'caribbean', 'caring', 'carl', 'carlisle', 'carlos', 'carly', 'carmeloanthony', 'carmen', 'carnage', 'carnival', 'carol', 'carole', 'carolina', 'caroline', 'carpet', 'carriage', 'carried', 'carrier', 'carrot', 'carry', 'carrying', 'carson', 'carsonsmummy', 'cart', 'carter', 'cartoon', 'carved', 'carving', 'casa', 'casamagna', 'case', 'casey', 'cash', 'cashier', 'caspar', 'casper', 'cassie', 'cast', 'castaway', 'castle', 'casual', 'casually', 'cat', 'catan', 'catch', 'catching', 'category', 'catering', 'catholic', 'caught', 'cause', 'caused', 'causing', 'caved', 'cavs', 'cb', 'cba', 'cbb', 'cbc', 'cbr', 'cbs', 'cbw', 'cc', 'ccf', 'ccfc', 'ccj', 'cd', 'cdc', 'cdk', 'cdnpoli', 'ce', 'ceiling', 'celebrate', 'celebrated', 'celebrates', 'celebrating', 'celebration', 'celebrity', 'celebs', 'celinedion', 'cell', 'celtic', 'celticfc', 'cena', 'censorship', 'census', 'cent', 'center', 'centinel', 'cento', 'central', 'centre', 'century', 'ceo', 'ceramic', 'cereal', 'ceremony', 'certain', 'certainly', 'certification', 'certified', 'ceu', 'cf', 'cfb', 'cfbmatrix', 'cfhd', 'cg', 'cgi', 'ch', 'chai', 'chain', 'chair', 'chairman', 'challenge', 'challenging', 'chamber', 'champ', 'champagne', 'champion', 'championship', 'chance', 'change', 'changed', 'changing', 'channel', 'chantelle', 'chaos', 'chapter', 'char', 'character', 'charcandrick', 'charcoal', 'charge', 'charged', 'charger', 'charging', 'charity', 'charizard', 'charles', 'charleston', 'charlie', 'charlieputh', 'charlotte', 'charm', 'chart', 'chartnews', 'chase', 'chasing', 'chat', 'cheap', 'cheaper', 'cheat', 'cheated', 'cheating', 'check', 'checked', 'checker', 'checking', 'checkout', 'cheek', 'cheeky', 'cheer', 'cheered', 'cheerful', 'cheering', 'cheerio', 'cheese', 'cheeseburger', 'cheesecake', 'cheesy', 'chef', 'chelsea', 'chem', 'chemical', 'chemistry', 'chen', 'cheney', 'cheque', 'cher', 'cherish', 'cherry', 'chesapeake', 'cheshire', 'chest', 'chester', 'chevy', 'chew', 'chewbacca', 'chewed', 'chi', 'chia', 'chic', 'chicago', 'chick', 'chicken', 'chickfila', 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'torture', 'torus', 'tory', 'tos', 'total', 'totally', 'tote', 'tothemoonxx', 'toting', 'touch', 'toucharcade', 'touched', 'touching', 'tough', 'toughness', 'tour', 'touring', 'tourism', 'tourist', 'tournament', 'towel', 'tower', 'towie', 'town', 'townhome', 'toy', 'toyota', 'tp', 'tpp', 'tq', 'tqe', 'tr', 'trace', 'track', 'tracking', 'tracy', 'trade', 'tradechat', 'traded', 'tradewinds', 'trading', 'tradition', 'traditional', 'traffic', 'trafficking', 'tragedy', 'tragic', 'trail', 'trailer', 'train', 'trained', 'trainer', 'training', 'trainor', 'trait', 'trance', 'trans', 'transfer', 'transformation', 'transformed', 'transforming', 'transit', 'transition', 'transitioning', 'translation', 'translator', 'transponder', 'transport', 'transportation', 'trap', 'trapped', 'trash', 'trauma', 'travel', 'traveler', 'traveling', 'traveller', 'travelling', 'travis', 'treadmill', 'treason', 'treasure', 'treasury', 'treat', 'treated', 'treating', 'treatment', 'treatyourfamily', 'trecru', 'tree', 'treehouse', 'trek', 'trench', 'trend', 'trending', 'trendsetters', 'trendy', 'trent', 'trentwalton', 'trevor', 'trevorhallmusic', 'trey', 'tri', 'trial', 'triangle', 'triathlon', 'tribulation', 'tribunal', 'tribute', 'trick', 'tricky', 'tried', 'trigger', 'triggered', 'trillion', 'trilogy', 'trimmed', 'trimming', 'trio', 'trip', 'tripe', 'triple', 'tripleh', 'tristan', 'triumph', 'trndnl', 'troll', 'trolling', 'troop', 'trophy', 'tropical', 'tropmed', 'trotsky', 'trouble', 'trouser', 'troy', 'tru', 'truck', 'trudeau', 'true', 'trulia', 'truly', 'truman', 'trump', 'trunk', 'trust', 'trusted', 'trustworthy', 'truth', 'try', 'tryin', 'trying', 'tryna', 'trynna', 'tshirt', 'tsnmike', 'tsu', 'tsunami', 'tt', 'ttall', 'ttt', 'tu', 'tub', 'tube', 'tucked', 'tues', 'tuesday', 'tuition', 'tumble', 'tumbler', 'tumblr', 'tummy', 'tumsfcetlg', 'tune', 'tuned', 'tunein', 'tuner', 'tunin', 'tunnel', 'turbo', 'turk', 'turkey', 'turkish', 'turn', 'turned', 'turner', 'turning', 'turnout', 'turnover', 'turnt', 'turnup', 'turtle', 'tut', 'tutor', 'tutorial', 'tuxedo', 'tv', 'tvtelehit', 'tw', 'twain', 'twat', 'twc', 'twd', 'twdbeth', 'tweak', 'tween', 'tweep', 'tweeps', 'tweet', 'tweetchoir', 'tweeted', 'tweeting', 'twentyonepilots', 'twice', 'twiigss', 'twilight', 'twilightsparkle', 'twill', 'twin', 'twirling', 'twist', 'twitch', 'twitchyteam', 'twitition', 'twitter', 'twitterweb', 'twp', 'tx', 'ty', 'tyforthelovemadlangpeople', 'tyif', 'tyler', 'tyleroakley', 'type', 'typed', 'typhoon', 'typical', 'typically', 'typing', 'typo', 'tyrfing', 'tyrone', 'tz', 'ua', 'uae', 'ub', 'uber', 'ubn', 'uc', 'uche', 'ucludebating', 'ud', 'udemy', 'udl', 'udr', 'ue', 'uf', 'ufc', 'ufo', 'ufy', 'ug', 'ugg', 'ugghhh', 'ugh', 'ughhhh', 'ugj', 'ugly', 'uh', 'uhc', 'ui', 'uil', 'uj', 'uk', 'ukenyatta', 'ukhouseoflords', 'uklabour', 'uknews', 'ukraine', 'ukrainian', 'ukrunchat', 'uktrichat', 'ukvoty', 'ul', 'ultimate', 'ultra', 'ultradavid', 'um', 'umbrella', 'umgctmj', 'umm', 'ummm', 'unable', 'unabridged', 'unbelievable', 'unbelievably', 'unborn', 'unbreakable', 'unbrick', 'unc', 'uncategorized', 'uncensored', 'uncharted', 'uncle', 'uncomfortable', 'undead', 'undefeated', 'underate', 'undergrad', 'underground', 'underneath', 'underrated', 'understand', 'understanding', 'understands', 'understood', 'undertaker', 'undertaking', 'undertale', 'underwear', 'undies', 'undo', 'undocumented', 'undone', 'unelected', 'unemployment', 'unethical', 'unexpected', 'unfair', 'unfollow', 'unfollowed', 'unfollower', 'unfollowers', 'unfortunately', 'ung', 'unhappy', 'unhealthy', 'uni', 'unicode', 'unicorn', 'unified', 'uniform', 'unify', 'unintelligent', 'union', 'unique', 'unit', 'unitarian', 'united', 'unitedstates', 'universal', 'universe', 'university', 'universitychallenge', 'unknowing', 'unknown', 'unless', 'unlimited', 'unlock', 'unlook', 'unnecessary', 'uno', 'unodc', 'unormal', 'unplugged', 'unpopular', 'unprofessional', 'unreal', 'unrealistic', 'unrelated', 'unrest', 'unsc', 'unshakeable', 'unsolved', 'unto', 'unused', 'unveiling', 'unwind', 'uo', 'uon', 'upcoming', 'update', 'updated', 'upgrade', 'upgraded', 'uplifting', 'upload', 'uploaded', 'uploading', 'upper', 'upr', 'ups', 'upset', 'upside', 'upstairs', 'uq', 'uqpj', 'ur', 'urban', 'urge', 'url', 'urself', 'usa', 'usatoday', 'usb', 'usc', 'usd', 'use', 'used', 'useful', 'useless', 'user', 'username', 'usfoods', 'usher', 'using', 'usps', 'ustheduo', 'usual', 'usually', 'ut', 'utah', 'utility', 'utilization', 'utterly', 'uu', 'uv', 'uw', 'ux', 'uy', 'uyanya', 'uz', 'uzb', 'va', 'vacation', 'vader', 'vag', 'vagina', 'vague', 'vaguely', 'val', 'vale', 'valentino', 'valeyellow', 'valid', 'valkyrie', 'valley', 'valuable', 'value', 'vamp', 'vampire', 'van', 'vance', 'vancouver', 'vaping', 'var', 'variable', 'varies', 'variety', 'various', 'varnish', 'varsity', 'vast', 'vault', 'vaw', 'vb', 'vbj', 'vbqn', 'vc', 'vcu', 'vcupav', 'vd', 'vdb', 've', 'veg', 'vega', 'vegan', 'vegetable', 'vegetarian', 'veggie', 'vehicle', 'veil', 'vein', 'velvet', 'vendor', 'venice', 'venicemase', 'venison', 'venom', 'vent', 'venture', 'venue', 'venus', 'ver', 'vera', 'verbally', 'verdict', 'verge', 'verified', 'verify', 'verizon', 'vermintide', 'vermont', 'vernacular', 'vernon', 'versa', 'verse', 'version', 'vest', 'vet', 'veteran', 'veto', 'vez', 'vf', 'vg', 'vgck', 'vgit', 'vgn', 'vh', 'vi', 'vibe', 'vibetickets', 'vic', 'vice', 'vicki', 'victim', 'victor', 'victoria', 'victorian', 'victory', 'vid', 'vida', 'video', 'videomarketing', 'vids', 'view', 'viewer', 'viewing', 'viking', 'villa', 'village', 'villain', 'vince', 'vincent', 'vine', 'vinegar', 'vinod', 'vintage', 'vinte', 'vinyl', 'violating', 'violation', 'violence', 'violent', 'violin', 'vip', 'viral', 'virgin', 'virginia', 'virgintrains', 'virtual', 'visa', 'visibility', 'visible', 'vision', 'visit', 'visited', 'visiting', 'visitor', 'visitphilly', 'vista', 'visto', 'visual', 'visuals', 'vital', 'vitamin', 'viv', 'vivid', 'vj', 'vk', 'vl', 'vlhnu', 'vlog', 'vlogging', 'vm', 'vmb', 'vmu', 'vo', 'vocabulary', 'vocal', 'vocalist', 'vodka', 'vogue', 'voice', 'voidflame', 'voiture', 'vol', 'volkswagen', 'volleyball', 'vols', 'voltaire', 'volume', 'voluntary', 'volunteer', 'vomit', 'von', 'voodoo', 'vote', 'voted', 'voteonedirection', 'voter', 'voteukip', 'voting', 'vouch', 'voucher', 'vous', 'vow', 'vp', 'vq', 'vqy', 'vr', 'vrf', 'vrizov', 'vrumi', 'vsd', 'vsw', 'vt', 'vtvk', 'vu', 'vuehelp', 'vulgar', 'vulnerable', 'vv', 'vvq', 'vw', 'vwg', 'vx', 'vy', 'vz', 'wa', 'wack', 'wade', 'wafc', 'waffle', 'wage', 'wagtail', 'waist', 'wait', 'waited', 'waiter', 'waiting', 'waiver', 'wake', 'wakeupamerica', 'waking', 'wal', 'wale', 'walk', 'walked', 'walker', 'walkie', 'walking', 'walkingdead', 'wall', 'wallaby', 'wallet', 'wallflower', 'wally', 'walmart', 'walt', 'walter', 'wan', 'wana', 'wanderer', 'wanker', 'want', 'wanted', 'wanting', 'war', 'warbucks', 'ward', 'warden', 'wardrobe', 'warehouse', 'warhammer', 'warm', 'warmer', 'warming', 'warmth', 'warn', 'warner', 'warning', 'warped', 'warren', 'warrior', 'warsaw', 'warzone', 'wash', 'washboard', 'washed', 'washer', 'washing', 'washington', 'washroom', 'wasn', 'wasnt', 'wasp', 'wast', 'waste', 'wasted', 'wasting', 'wat', 'watch', 'watched', 'watching', 'water', 'watermelon', 'wats', 'watson', 'watt', 'wave', 'wax', 'waxing', 'way', 'wayne', 'wazoo', 'wb', 'wc', 'wcf', 'wcw', 'wd', 'wdudveojoq', 'weah', 'weak', 'weakest', 'weakness', 'wealth', 'wealthy', 'weapon', 'wear', 'wearing', 'weather', 'web', 'webb', 'webber', 'webcam', 'webcamgirl', 'webcast', 'webdesign', 'webinar', 'webmail', 'webmaster', 'website', 'wed', 'wedding', 'wednesday', 'wedontsoundlikethem', 'wee', 'weed', 'weeden', 'week', 'weekend', 'weekly', 'weeknd', 'weep', 'weight', 'weightloss', 'weird', 'weirdest', 'weirdo', 'welcome', 'welfare', 'wellness', 'welovebrad', 'welp', 'welsh', 'wen', 'went', 'weo', 'weren', 'west', 'western', 'westham', 'wet', 'wetv', 'wf', 'wh', 'whats', 'whatsapp', 'whatsoever', 'wheel', 'whichever', 'whilst', 'whine', 'whining', 'whip', 'whipped', 'whiskey', 'whisky', 'white', 'whitney', 'whoa', 'whoop', 'whore', 'whs', 'whyimnotvotingforhillary', 'wi', 'wicked', 'wide', 'wife', 'wifi', 'wig', 'wih', 'wild', 'wilkerson', 'william', 'williams', 'willing', 'willow', 'wilson', 'win', 'winchester', 'wind', 'window', 'wine', 'wing', 'wink', 'winner', 'winning', 'winter', 'wipe', 'wired', 'wireless', 'wisconsin', 'wisdom', 'wise', 'wish', 'wishing', 'wit', 'witch', 'witness', 'witty', 'witwgx', 'wizard', 'wizkid', 'wj', 'wk', 'wl', 'wm', 'wn', 'wo', 'woe', 'woke', 'wolf', 'woman', 'won', 'wonder', 'wondered', 'wonderful', 'wondering', 'wonderland', 'wont', 'woo', 'wood', 'woodland', 'woodworking', 'worcestershirehour', 'word', 'wordbrain', 'wordpress', 'wordpressdotcom', 'wore', 'work', 'workbench', 'worked', 'worker', 'working', 'workout', 'workplace', 'workshop', 'world', 'worldseries', 'worldwide', 'worm', 'worried', 'worry', 'worrying', 'worse', 'worsening', 'worship', 'worst', 'worth', 'worthwhile', 'worthy', 'woulda', 'wouldn', 'wouldnt', 'wound', 'wow', 'wp', 'wpe', 'wq', 'wr', 'wrap', 'wrapped', 'wrestling', 'wrist', 'write', 'writer', 'writes', 'writing', 'written', 'wrong', 'wrote', 'wrs', 'wsj', 'wsop', 'wsu', 'wt', 'wtf', 'wu', 'wv', 'wvpmc', 'ww', 'wwe', 'wwii', 'www', 'wx', 'wy', 'wyatt', 'xa', 'xb', 'xbox', 'xboxuk', 'xc', 'xd', 'xe', 'xf', 'xg', 'xh', 'xi', 'xj', 'xk', 'xl', 'xm', 'xmas', 'xo', 'xp', 'xq', 'xr', 'xv', 'xw', 'xwa', 'xx', 'xxl', 'xxx', 'xxxx', 'ya', 'yacht', 'yahoo', 'yahooanswers', 'yall', 'yard', 'yay', 'yb', 'ybg', 'yc', 'yd', 'ye', 'yea', 'yeah', 'year', 'yeh', 'yell', 'yelled', 'yelling', 'yellow', 'yelp', 'yep', 'yes', 'yesterday', 'yf', 'yg', 'yh', 'yi', 'yj', 'yl', 'ylt', 'ym', 'yma', 'ymcglaun', 'ymyjapyvnk', 'yo', 'yoga', 'yogurt', 'yoquiero', 'york', 'yorker', 'yorkie', 'youll', 'young', 'younger', 'younis', 'youre', 'youth', 'youtube', 'yq', 'yr', 'yt', 'yu', 'yummy', 'yung', 'yup', 'yw', 'yx', 'yy', 'yz', 'yzuxb', 'za', 'zach', 'zack', 'zayn', 'zb', 'zc', 'zd', 'ze', 'zelda', 'zen', 'zero', 'zf', 'zfjl', 'zg', 'zh', 'zi', 'zimbabwe', 'zionist', 'zk', 'zl', 'zn', 'zo', 'zombie', 'zone', 'zoo', 'zoom', 'zq', 'zr', 'zt', 'zu', 'zv', 'zw', 'zx', 'zy', 'zz']
y = data.iloc[:, 0].values
x = sparce_matrix

x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.08, random_state = 40)  # Train test split_____no_output_____lr = LogisticRegression(max_iter = 2000)
lr.fit(x_train,y_train)

y_pred = lr.predict(x_test)   # Prediction_____no_output_____accuracy = 100.0 * metrics.accuracy_score(y_test, y_pred)
print("Accuracy: ", accuracy)Accuracy:  70.44458359423919

</code>