Case  Study - IMDB dataset.ipynb

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    "import pandas as pd"
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   "source": [
    "data = pd.read_csv('data/imdb-reviews/dataset.csv', encoding='latin-1')"
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      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 25000 entries, 0 to 24999\n",
      "Data columns (total 2 columns):\n",
      "SentimentText    25000 non-null object\n",
      "Sentiment        25000 non-null int64\n",
      "dtypes: int64(1), object(1)\n",
      "memory usage: 390.7+ KB\n"
     ]
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   "source": [
    "data.info()"
   ]
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       "      <td>first think another Disney movie, might good, ...</td>\n",
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       "      <td>Put aside Dr. House repeat missed, Desperate H...</td>\n",
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       "      <td>big fan Stephen King's work, film made even gr...</td>\n",
       "      <td>1</td>\n",
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       "      <td>watched horrid thing TV. Needless say one movi...</td>\n",
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       "      <td>truly enjoyed film. acting terrific plot. Jeff...</td>\n",
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       "                                       SentimentText  Sentiment\n",
       "0  first think another Disney movie, might good, ...          1\n",
       "1  Put aside Dr. House repeat missed, Desperate H...          0\n",
       "2  big fan Stephen King's work, film made even gr...          1\n",
       "3  watched horrid thing TV. Needless say one movi...          0\n",
       "4  truly enjoyed film. acting terrific plot. Jeff...          1"
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   "source": [
    "data.head()"
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   "execution_count": null,
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