BagOfWords.ipynb

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     "text": [
      "['and this is', 'document is the', 'is the first', 'is the second', 'is the third', 'the first article', 'this document is', 'this is the']\n",
      "[[0 0 1 0 0 1 0 1]\n",
      " [0 1 0 1 0 0 1 0]\n",
      " [1 0 0 0 1 0 0 1]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "corpus = [\n",
    "    'This is the first article.',\n",
    "    'This document is the second.',\n",
    "    'And this is the third.'\n",
    "]\n",
    "\n",
    "vectorizer = CountVectorizer(analyzer='word', ngram_range=(3, 3)) # or CountVectorizer()\n",
    "X = vectorizer.fit_transform(corpus)\n",
    "print(vectorizer.get_feature_names())\n",
    "\n",
    "print(X.toarray())"
   ]
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   "source": []
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