Notebook on stop words completed
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187
CM3060 Natural Language Processing/Week 4/2.3.5 Stop words.ipynb
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187
CM3060 Natural Language Processing/Week 4/2.3.5 Stop words.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "8c6f299c-031f-4e2b-8215-1232a5f72e98",
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"metadata": {},
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"source": [
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"# Stop words\n",
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"* High-frequency words, little lexical content (e.g. and, the, of)\n",
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"* When used for certain ML tasks, can add 'noise' (but not always)\n",
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"* Filter out beforehand\n",
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"* Language-specific, no universal list"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "788c368a-0f14-42a9-aacc-aa967812f83e",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[nltk_data] Downloading package stopwords to C:\\nltk_data...\n",
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"[nltk_data] Package stopwords is already up-to-date!\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import nltk\n",
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"from nltk.corpus import stopwords\n",
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"nltk.download('stopwords')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "957a4bdd-38fb-4e72-b5fd-fb994edc132c",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', \"you're\", \"you've\", \"you'll\", \"you'd\", 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she', \"she's\", 'her', 'hers', 'herself', 'it', \"it's\", 'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', \"that'll\", 'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', \"don't\", 'should', \"should've\", 'now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', \"aren't\", 'couldn', \"couldn't\", 'didn', \"didn't\", 'doesn', \"doesn't\", 'hadn', \"hadn't\", 'hasn', \"hasn't\", 'haven', \"haven't\", 'isn', \"isn't\", 'ma', 'mightn', \"mightn't\", 'mustn', \"mustn't\", 'needn', \"needn't\", 'shan', \"shan't\", 'shouldn', \"shouldn't\", 'wasn', \"wasn't\", 'weren', \"weren't\", 'won', \"won't\", 'wouldn', \"wouldn't\"]\n",
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"179\n"
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]
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}
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],
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"source": [
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"print(stopwords.words(\"english\"))\n",
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"print(len(stopwords.words(\"english\")))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "e1f2989c-3262-4cbc-b0fc-6515643efcc6",
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"metadata": {},
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"outputs": [],
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"source": [
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"text = '''Most of the time we can use white space.\n",
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"But what about fred@gmail.com or 13/01/2021?\n",
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"The students' attempts aren't working.\n",
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"Maybe it's the use of apostrophes? Or it might need a more up-to-date model.\n",
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"'''"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "e1166fb1-b04c-4eff-bbf4-758fbff92e5f",
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"metadata": {},
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"outputs": [],
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"source": [
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"stop_words = set(stopwords.words(\"english\"))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "1e0eeba3-6071-4855-a8a7-2c6489465613",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['Most', 'time', 'use', 'white', 'space', '.', 'But', 'fred', '@', 'gmail.com', '13/01/2021', '?', 'The', 'students', \"'\", 'attempts', \"n't\", 'working', '.', 'Maybe', \"'s\", 'use', 'apostrophes', '?', 'Or', 'might', 'need', 'up-to-date', 'model', '.']\n"
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]
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}
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],
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"source": [
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"words = nltk.word_tokenize(text)\n",
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"print([w for w in words if not w in stop_words])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "5e6ef823-aedd-411b-b6fa-f697267e6361",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[]\n"
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]
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}
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],
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"source": [
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"text2 = \"to be or not to be\"\n",
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"words2 = nltk.word_tokenize(text2)\n",
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"print([w for w in words2 if not w in stop_words])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "7dcc2048-bb6b-4614-ae0a-8e483c634141",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['aber', 'alle', 'allem', 'allen', 'aller', 'alles', 'als', 'also', 'am', 'an', 'ander', 'andere', 'anderem', 'anderen', 'anderer', 'anderes', 'anderm', 'andern', 'anderr', 'anders', 'auch', 'auf', 'aus', 'bei', 'bin', 'bis', 'bist', 'da', 'damit', 'dann', 'der', 'den', 'des', 'dem', 'die', 'das', 'dass', 'daß', 'derselbe', 'derselben', 'denselben', 'desselben', 'demselben', 'dieselbe', 'dieselben', 'dasselbe', 'dazu', 'dein', 'deine', 'deinem', 'deinen', 'deiner', 'deines', 'denn', 'derer', 'dessen', 'dich', 'dir', 'du', 'dies', 'diese', 'diesem', 'diesen', 'dieser', 'dieses', 'doch', 'dort', 'durch', 'ein', 'eine', 'einem', 'einen', 'einer', 'eines', 'einig', 'einige', 'einigem', 'einigen', 'einiger', 'einiges', 'einmal', 'er', 'ihn', 'ihm', 'es', 'etwas', 'euer', 'eure', 'eurem', 'euren', 'eurer', 'eures', 'für', 'gegen', 'gewesen', 'hab', 'habe', 'haben', 'hat', 'hatte', 'hatten', 'hier', 'hin', 'hinter', 'ich', 'mich', 'mir', 'ihr', 'ihre', 'ihrem', 'ihren', 'ihrer', 'ihres', 'euch', 'im', 'in', 'indem', 'ins', 'ist', 'jede', 'jedem', 'jeden', 'jeder', 'jedes', 'jene', 'jenem', 'jenen', 'jener', 'jenes', 'jetzt', 'kann', 'kein', 'keine', 'keinem', 'keinen', 'keiner', 'keines', 'können', 'könnte', 'machen', 'man', 'manche', 'manchem', 'manchen', 'mancher', 'manches', 'mein', 'meine', 'meinem', 'meinen', 'meiner', 'meines', 'mit', 'muss', 'musste', 'nach', 'nicht', 'nichts', 'noch', 'nun', 'nur', 'ob', 'oder', 'ohne', 'sehr', 'sein', 'seine', 'seinem', 'seinen', 'seiner', 'seines', 'selbst', 'sich', 'sie', 'ihnen', 'sind', 'so', 'solche', 'solchem', 'solchen', 'solcher', 'solches', 'soll', 'sollte', 'sondern', 'sonst', 'über', 'um', 'und', 'uns', 'unsere', 'unserem', 'unseren', 'unser', 'unseres', 'unter', 'viel', 'vom', 'von', 'vor', 'während', 'war', 'waren', 'warst', 'was', 'weg', 'weil', 'weiter', 'welche', 'welchem', 'welchen', 'welcher', 'welches', 'wenn', 'werde', 'werden', 'wie', 'wieder', 'will', 'wir', 'wird', 'wirst', 'wo', 'wollen', 'wollte', 'würde', 'würden', 'zu', 'zum', 'zur', 'zwar', 'zwischen']\n"
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]
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}
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],
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"source": [
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"print(stopwords.words(\"german\"))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "34386586-9425-4b75-9b1b-0ee2cdda7bb0",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['au', 'aux', 'avec', 'ce', 'ces', 'dans', 'de', 'des', 'du', 'elle', 'en', 'et', 'eux', 'il', 'ils', 'je', 'la', 'le', 'les', 'leur', 'lui', 'ma', 'mais', 'me', 'même', 'mes', 'moi', 'mon', 'ne', 'nos', 'notre', 'nous', 'on', 'ou', 'par', 'pas', 'pour', 'qu', 'que', 'qui', 'sa', 'se', 'ses', 'son', 'sur', 'ta', 'te', 'tes', 'toi', 'ton', 'tu', 'un', 'une', 'vos', 'votre', 'vous', 'c', 'd', 'j', 'l', 'à', 'm', 'n', 's', 't', 'y', 'été', 'étée', 'étées', 'étés', 'étant', 'étante', 'étants', 'étantes', 'suis', 'es', 'est', 'sommes', 'êtes', 'sont', 'serai', 'seras', 'sera', 'serons', 'serez', 'seront', 'serais', 'serait', 'serions', 'seriez', 'seraient', 'étais', 'était', 'étions', 'étiez', 'étaient', 'fus', 'fut', 'fûmes', 'fûtes', 'furent', 'sois', 'soit', 'soyons', 'soyez', 'soient', 'fusse', 'fusses', 'fût', 'fussions', 'fussiez', 'fussent', 'ayant', 'ayante', 'ayantes', 'ayants', 'eu', 'eue', 'eues', 'eus', 'ai', 'as', 'avons', 'avez', 'ont', 'aurai', 'auras', 'aura', 'aurons', 'aurez', 'auront', 'aurais', 'aurait', 'aurions', 'auriez', 'auraient', 'avais', 'avait', 'avions', 'aviez', 'avaient', 'eut', 'eûmes', 'eûtes', 'eurent', 'aie', 'aies', 'ait', 'ayons', 'ayez', 'aient', 'eusse', 'eusses', 'eût', 'eussions', 'eussiez', 'eussent']\n"
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]
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}
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],
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"source": [
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"print(stopwords.words(\"french\"))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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