Untitled.ipynb

{
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   "cell_type": "code",
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   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/priyanshunayan/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
      "  return f(*args, **kwds)\n",
      "/Users/priyanshunayan/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
      "  return f(*args, **kwds)\n",
      "/Users/priyanshunayan/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
      "  return f(*args, **kwds)\n",
      "/Users/priyanshunayan/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
      "  return f(*args, **kwds)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from nltk.corpus import stopwords\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.preprocessing.text import Tokenizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.2.0'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "hotel_review = pd.read_csv('Hotel_Reviews.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Hotel_Address</th>\n",
       "      <th>Additional_Number_of_Scoring</th>\n",
       "      <th>Review_Date</th>\n",
       "      <th>Average_Score</th>\n",
       "      <th>Hotel_Name</th>\n",
       "      <th>Reviewer_Nationality</th>\n",
       "      <th>Negative_Review</th>\n",
       "      <th>Review_Total_Negative_Word_Counts</th>\n",
       "      <th>Total_Number_of_Reviews</th>\n",
       "      <th>Positive_Review</th>\n",
       "      <th>Review_Total_Positive_Word_Counts</th>\n",
       "      <th>Total_Number_of_Reviews_Reviewer_Has_Given</th>\n",
       "      <th>Reviewer_Score</th>\n",
       "      <th>Tags</th>\n",
       "      <th>days_since_review</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>8/3/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>Russia</td>\n",
       "      <td>I am so angry that i made this post available...</td>\n",
       "      <td>397</td>\n",
       "      <td>1403</td>\n",
       "      <td>Only the park outside of the hotel was beauti...</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>2.9</td>\n",
       "      <td>[' Leisure trip ', ' Couple ', ' Duplex Double...</td>\n",
       "      <td>0 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>8/3/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>Ireland</td>\n",
       "      <td>No Negative</td>\n",
       "      <td>0</td>\n",
       "      <td>1403</td>\n",
       "      <td>No real complaints the hotel was great great ...</td>\n",
       "      <td>105</td>\n",
       "      <td>7</td>\n",
       "      <td>7.5</td>\n",
       "      <td>[' Leisure trip ', ' Couple ', ' Duplex Double...</td>\n",
       "      <td>0 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>7/31/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>Australia</td>\n",
       "      <td>Rooms are nice but for elderly a bit difficul...</td>\n",
       "      <td>42</td>\n",
       "      <td>1403</td>\n",
       "      <td>Location was good and staff were ok It is cut...</td>\n",
       "      <td>21</td>\n",
       "      <td>9</td>\n",
       "      <td>7.1</td>\n",
       "      <td>[' Leisure trip ', ' Family with young childre...</td>\n",
       "      <td>3 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>7/31/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>My room was dirty and I was afraid to walk ba...</td>\n",
       "      <td>210</td>\n",
       "      <td>1403</td>\n",
       "      <td>Great location in nice surroundings the bar a...</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>3.8</td>\n",
       "      <td>[' Leisure trip ', ' Solo traveler ', ' Duplex...</td>\n",
       "      <td>3 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>7/24/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>You When I booked with your company on line y...</td>\n",
       "      <td>140</td>\n",
       "      <td>1403</td>\n",
       "      <td>Amazing location and building Romantic setting</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>6.7</td>\n",
       "      <td>[' Leisure trip ', ' Couple ', ' Suite ', ' St...</td>\n",
       "      <td>10 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       Hotel_Address  ...       lng\n",
       "0   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...  ...  4.915968\n",
       "1   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...  ...  4.915968\n",
       "2   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...  ...  4.915968\n",
       "3   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...  ...  4.915968\n",
       "4   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...  ...  4.915968\n",
       "\n",
       "[5 rows x 17 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hotel_review.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(515738, 17)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hotel_review.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on _LocIndexer in module pandas.core.indexing object:\n",
      "\n",
      "class _LocIndexer(_LocationIndexer)\n",
      " |  Access a group of rows and columns by label(s) or a boolean array.\n",
      " |  \n",
      " |  ``.loc[]`` is primarily label based, but may also be used with a\n",
      " |  boolean array.\n",
      " |  \n",
      " |  Allowed inputs are:\n",
      " |  \n",
      " |  - A single label, e.g. ``5`` or ``'a'``, (note that ``5`` is\n",
      " |    interpreted as a *label* of the index, and **never** as an\n",
      " |    integer position along the index).\n",
      " |  - A list or array of labels, e.g. ``['a', 'b', 'c']``.\n",
      " |  - A slice object with labels, e.g. ``'a':'f'``.\n",
      " |  \n",
      " |    .. warning:: Note that contrary to usual python slices, **both** the\n",
      " |        start and the stop are included\n",
      " |  \n",
      " |  - A boolean array of the same length as the axis being sliced,\n",
      " |    e.g. ``[True, False, True]``.\n",
      " |  - A ``callable`` function with one argument (the calling Series or\n",
      " |    DataFrame) and that returns valid output for indexing (one of the above)\n",
      " |  \n",
      " |  See more at :ref:`Selection by Label <indexing.label>`\n",
      " |  \n",
      " |  Raises\n",
      " |  ------\n",
      " |  KeyError\n",
      " |      If any items are not found.\n",
      " |  \n",
      " |  See Also\n",
      " |  --------\n",
      " |  DataFrame.at : Access a single value for a row/column label pair.\n",
      " |  DataFrame.iloc : Access group of rows and columns by integer position(s).\n",
      " |  DataFrame.xs : Returns a cross-section (row(s) or column(s)) from the\n",
      " |      Series/DataFrame.\n",
      " |  Series.loc : Access group of values using labels.\n",
      " |  \n",
      " |  Examples\n",
      " |  --------\n",
      " |  **Getting values**\n",
      " |  \n",
      " |  >>> df = pd.DataFrame([[1, 2], [4, 5], [7, 8]],\n",
      " |  ...      index=['cobra', 'viper', 'sidewinder'],\n",
      " |  ...      columns=['max_speed', 'shield'])\n",
      " |  >>> df\n",
      " |              max_speed  shield\n",
      " |  cobra               1       2\n",
      " |  viper               4       5\n",
      " |  sidewinder          7       8\n",
      " |  \n",
      " |  Single label. Note this returns the row as a Series.\n",
      " |  \n",
      " |  >>> df.loc['viper']\n",
      " |  max_speed    4\n",
      " |  shield       5\n",
      " |  Name: viper, dtype: int64\n",
      " |  \n",
      " |  List of labels. Note using ``[[]]`` returns a DataFrame.\n",
      " |  \n",
      " |  >>> df.loc[['viper', 'sidewinder']]\n",
      " |              max_speed  shield\n",
      " |  viper               4       5\n",
      " |  sidewinder          7       8\n",
      " |  \n",
      " |  Single label for row and column\n",
      " |  \n",
      " |  >>> df.loc['cobra', 'shield']\n",
      " |  2\n",
      " |  \n",
      " |  Slice with labels for row and single label for column. As mentioned\n",
      " |  above, note that both the start and stop of the slice are included.\n",
      " |  \n",
      " |  >>> df.loc['cobra':'viper', 'max_speed']\n",
      " |  cobra    1\n",
      " |  viper    4\n",
      " |  Name: max_speed, dtype: int64\n",
      " |  \n",
      " |  Boolean list with the same length as the row axis\n",
      " |  \n",
      " |  >>> df.loc[[False, False, True]]\n",
      " |              max_speed  shield\n",
      " |  sidewinder          7       8\n",
      " |  \n",
      " |  Conditional that returns a boolean Series\n",
      " |  \n",
      " |  >>> df.loc[df['shield'] > 6]\n",
      " |              max_speed  shield\n",
      " |  sidewinder          7       8\n",
      " |  \n",
      " |  Conditional that returns a boolean Series with column labels specified\n",
      " |  \n",
      " |  >>> df.loc[df['shield'] > 6, ['max_speed']]\n",
      " |              max_speed\n",
      " |  sidewinder          7\n",
      " |  \n",
      " |  Callable that returns a boolean Series\n",
      " |  \n",
      " |  >>> df.loc[lambda df: df['shield'] == 8]\n",
      " |              max_speed  shield\n",
      " |  sidewinder          7       8\n",
      " |  \n",
      " |  **Setting values**\n",
      " |  \n",
      " |  Set value for all items matching the list of labels\n",
      " |  \n",
      " |  >>> df.loc[['viper', 'sidewinder'], ['shield']] = 50\n",
      " |  >>> df\n",
      " |              max_speed  shield\n",
      " |  cobra               1       2\n",
      " |  viper               4      50\n",
      " |  sidewinder          7      50\n",
      " |  \n",
      " |  Set value for an entire row\n",
      " |  \n",
      " |  >>> df.loc['cobra'] = 10\n",
      " |  >>> df\n",
      " |              max_speed  shield\n",
      " |  cobra              10      10\n",
      " |  viper               4      50\n",
      " |  sidewinder          7      50\n",
      " |  \n",
      " |  Set value for an entire column\n",
      " |  \n",
      " |  >>> df.loc[:, 'max_speed'] = 30\n",
      " |  >>> df\n",
      " |              max_speed  shield\n",
      " |  cobra              30      10\n",
      " |  viper              30      50\n",
      " |  sidewinder         30      50\n",
      " |  \n",
      " |  Set value for rows matching callable condition\n",
      " |  \n",
      " |  >>> df.loc[df['shield'] > 35] = 0\n",
      " |  >>> df\n",
      " |              max_speed  shield\n",
      " |  cobra              30      10\n",
      " |  viper               0       0\n",
      " |  sidewinder          0       0\n",
      " |  \n",
      " |  **Getting values on a DataFrame with an index that has integer labels**\n",
      " |  \n",
      " |  Another example using integers for the index\n",
      " |  \n",
      " |  >>> df = pd.DataFrame([[1, 2], [4, 5], [7, 8]],\n",
      " |  ...      index=[7, 8, 9], columns=['max_speed', 'shield'])\n",
      " |  >>> df\n",
      " |     max_speed  shield\n",
      " |  7          1       2\n",
      " |  8          4       5\n",
      " |  9          7       8\n",
      " |  \n",
      " |  Slice with integer labels for rows. As mentioned above, note that both\n",
      " |  the start and stop of the slice are included.\n",
      " |  \n",
      " |  >>> df.loc[7:9]\n",
      " |     max_speed  shield\n",
      " |  7          1       2\n",
      " |  8          4       5\n",
      " |  9          7       8\n",
      " |  \n",
      " |  **Getting values with a MultiIndex**\n",
      " |  \n",
      " |  A number of examples using a DataFrame with a MultiIndex\n",
      " |  \n",
      " |  >>> tuples = [\n",
      " |  ...    ('cobra', 'mark i'), ('cobra', 'mark ii'),\n",
      " |  ...    ('sidewinder', 'mark i'), ('sidewinder', 'mark ii'),\n",
      " |  ...    ('viper', 'mark ii'), ('viper', 'mark iii')\n",
      " |  ... ]\n",
      " |  >>> index = pd.MultiIndex.from_tuples(tuples)\n",
      " |  >>> values = [[12, 2], [0, 4], [10, 20],\n",
      " |  ...         [1, 4], [7, 1], [16, 36]]\n",
      " |  >>> df = pd.DataFrame(values, columns=['max_speed', 'shield'], index=index)\n",
      " |  >>> df\n",
      " |                       max_speed  shield\n",
      " |  cobra      mark i           12       2\n",
      " |             mark ii           0       4\n",
      " |  sidewinder mark i           10      20\n",
      " |             mark ii           1       4\n",
      " |  viper      mark ii           7       1\n",
      " |             mark iii         16      36\n",
      " |  \n",
      " |  Single label. Note this returns a DataFrame with a single index.\n",
      " |  \n",
      " |  >>> df.loc['cobra']\n",
      " |           max_speed  shield\n",
      " |  mark i          12       2\n",
      " |  mark ii          0       4\n",
      " |  \n",
      " |  Single index tuple. Note this returns a Series.\n",
      " |  \n",
      " |  >>> df.loc[('cobra', 'mark ii')]\n",
      " |  max_speed    0\n",
      " |  shield       4\n",
      " |  Name: (cobra, mark ii), dtype: int64\n",
      " |  \n",
      " |  Single label for row and column. Similar to passing in a tuple, this\n",
      " |  returns a Series.\n",
      " |  \n",
      " |  >>> df.loc['cobra', 'mark i']\n",
      " |  max_speed    12\n",
      " |  shield        2\n",
      " |  Name: (cobra, mark i), dtype: int64\n",
      " |  \n",
      " |  Single tuple. Note using ``[[]]`` returns a DataFrame.\n",
      " |  \n",
      " |  >>> df.loc[[('cobra', 'mark ii')]]\n",
      " |                 max_speed  shield\n",
      " |  cobra mark ii          0       4\n",
      " |  \n",
      " |  Single tuple for the index with a single label for the column\n",
      " |  \n",
      " |  >>> df.loc[('cobra', 'mark i'), 'shield']\n",
      " |  2\n",
      " |  \n",
      " |  Slice from index tuple to single label\n",
      " |  \n",
      " |  >>> df.loc[('cobra', 'mark i'):'viper']\n",
      " |                       max_speed  shield\n",
      " |  cobra      mark i           12       2\n",
      " |             mark ii           0       4\n",
      " |  sidewinder mark i           10      20\n",
      " |             mark ii           1       4\n",
      " |  viper      mark ii           7       1\n",
      " |             mark iii         16      36\n",
      " |  \n",
      " |  Slice from index tuple to index tuple\n",
      " |  \n",
      " |  >>> df.loc[('cobra', 'mark i'):('viper', 'mark ii')]\n",
      " |                      max_speed  shield\n",
      " |  cobra      mark i          12       2\n",
      " |             mark ii          0       4\n",
      " |  sidewinder mark i          10      20\n",
      " |             mark ii          1       4\n",
      " |  viper      mark ii          7       1\n",
      " |  \n",
      " |  Method resolution order:\n",
      " |      _LocIndexer\n",
      " |      _LocationIndexer\n",
      " |      _NDFrameIndexer\n",
      " |      pandas._libs.indexing._NDFrameIndexerBase\n",
      " |      builtins.object\n",
      " |  \n",
      " |  Methods inherited from _LocationIndexer:\n",
      " |  \n",
      " |  __getitem__(self, key)\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Methods inherited from _NDFrameIndexer:\n",
      " |  \n",
      " |  __call__(self, axis=None)\n",
      " |      Call self as a function.\n",
      " |  \n",
      " |  __setitem__(self, key, value)\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data descriptors inherited from _NDFrameIndexer:\n",
      " |  \n",
      " |  __dict__\n",
      " |      dictionary for instance variables (if defined)\n",
      " |  \n",
      " |  __weakref__\n",
      " |      list of weak references to the object (if defined)\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data and other attributes inherited from _NDFrameIndexer:\n",
      " |  \n",
      " |  __annotations__ = {'_valid_types': <class 'str'>}\n",
      " |  \n",
      " |  axis = None\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Methods inherited from pandas._libs.indexing._NDFrameIndexerBase:\n",
      " |  \n",
      " |  __init__(self, /, *args, **kwargs)\n",
      " |      Initialize self.  See help(type(self)) for accurate signature.\n",
      " |  \n",
      " |  __reduce__ = __reduce_cython__(...)\n",
      " |  \n",
      " |  __setstate__ = __setstate_cython__(...)\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Static methods inherited from pandas._libs.indexing._NDFrameIndexerBase:\n",
      " |  \n",
      " |  __new__(*args, **kwargs) from builtins.type\n",
      " |      Create and return a new object.  See help(type) for accurate signature.\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data descriptors inherited from pandas._libs.indexing._NDFrameIndexerBase:\n",
      " |  \n",
      " |  name\n",
      " |  \n",
      " |  ndim\n",
      " |  \n",
      " |  obj\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(hotel_review.loc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "positive_review = hotel_review.loc[:,['Positive_Review']]\n",
    "negative_review = hotel_review.loc[:,['Negative_Review']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove No Positive rows from Positve Reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(479792, 1)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "options = ['No Positive', 'No Negative']\n",
    "selected_positive_review = positive_review.loc[~(positive_review['Positive_Review'] == \"No Positive\"), :]\n",
    "selected_negative_review = negative_review.loc[~(negative_review['Negative_Review'] == \"No Negative\"), :]\n",
    "selected_positive_review.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(387848, 1)"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_negative_review.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_positive_review = selected_positive_review[:387848]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(selected_negative_review)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Amazing location and building Romantic setting</td>\n",
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       "      <td>Clean and well furnished room Good breakfast ...</td>\n",
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       "      <td>Needs modernisation costs around twenty quid ...</td>\n",
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       "    <tr>\n",
       "      <th>417060</th>\n",
       "      <td>Great hotel very clean staff was pleasant and...</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "                                          Positive_Review\n",
       "0        Only the park outside of the hotel was beauti...\n",
       "1        No real complaints the hotel was great great ...\n",
       "2        Location was good and staff were ok It is cut...\n",
       "3        Great location in nice surroundings the bar a...\n",
       "4         Amazing location and building Romantic setting \n",
       "...                                                   ...\n",
       "417056                                          Breakfast\n",
       "417057   Clean and well furnished room Good breakfast ...\n",
       "417058   Needs modernisation costs around twenty quid ...\n",
       "417059   Staff at the reception were friendly that is ...\n",
       "417060   Great hotel very clean staff was pleasant and...\n",
       "\n",
       "[387848 rows x 1 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "selected_positive_review"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "reviews = pd.merge(selected_positive_review, selected_negative_review, on=selected_negative_review.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
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       "      <th>1</th>\n",
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       "      <td>No real complaints the hotel was great great ...</td>\n",
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       "      <th>2</th>\n",
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       "      <th>3</th>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Amazing location and building Romantic setting</td>\n",
       "      <td>Backyard of the hotel is total mess shouldn t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <th>387843</th>\n",
       "      <td>515731</td>\n",
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       "      <td>No parking Public parking garage is 15 Euro p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>387844</th>\n",
       "      <td>515733</td>\n",
       "      <td>Clean and well furnished room Good breakfast ...</td>\n",
       "      <td>no trolly or staff to help you take the lugga...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>387845</th>\n",
       "      <td>515734</td>\n",
       "      <td>Needs modernisation costs around twenty quid ...</td>\n",
       "      <td>The hotel looks like 3 but surely not 4</td>\n",
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       "    <tr>\n",
       "      <th>387846</th>\n",
       "      <td>515735</td>\n",
       "      <td>Staff at the reception were friendly that is ...</td>\n",
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       "      <th>387847</th>\n",
       "      <td>515737</td>\n",
       "      <td>Great hotel very clean staff was pleasant and...</td>\n",
       "      <td>I was in 3rd floor It didn t work Free Wife</td>\n",
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      ],
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       "         key_0  ...                                    Negative_Review\n",
       "0            0  ...   I am so angry that i made this post available...\n",
       "1            2  ...   Rooms are nice but for elderly a bit difficul...\n",
       "2            3  ...   My room was dirty and I was afraid to walk ba...\n",
       "3            4  ...   You When I booked with your company on line y...\n",
       "4            5  ...   Backyard of the hotel is total mess shouldn t...\n",
       "...        ...  ...                                                ...\n",
       "387843  515731  ...   No parking Public parking garage is 15 Euro p...\n",
       "387844  515733  ...   no trolly or staff to help you take the lugga...\n",
       "387845  515734  ...           The hotel looks like 3 but surely not 4 \n",
       "387846  515735  ...   The ac was useless It was a hot week in vienn...\n",
       "387847  515737  ...       I was in 3rd floor It didn t work Free Wife \n",
       "\n",
       "[387848 rows x 3 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Positive_Review</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>I am so angry that i made this post available via all possible sites i use when planing my trips so no one will make the mistake of booking this place I made my booking via booking com We stayed for 6 nights in this hotel from 11 to 17 July Upon arrival we were placed in a small room on the 2nd floor of the hotel It turned out that this was not the room we booked I had specially reserved the 2 level duplex room so that we would have a big windows and high ceilings The room itself was ok if you don t mind the broken window that can not be closed hello rain and a mini fridge that contained some sort of a bio weapon at least i guessed so by the smell of it I intimately asked to change the room and after explaining 2 times that i booked a duplex btw it costs the same as a simple double but got way more volume due to the high ceiling was offered a room but only the next day SO i had to check out the next day before 11 o clock in order to get the room i waned to Not the best way to begin your holiday So we had to wait till 13 00 in order to check in my new room what a wonderful waist of my time The room 023 i got was just as i wanted to peaceful internal garden view big window We were tired from waiting the room so we placed our belongings and rushed to the city In the evening it turned out that there was a constant noise in the room i guess it was made by vibrating vent tubes or something it was constant and annoying as hell AND it did not stop even at 2 am making it hard to fall asleep for me and my wife I have an audio recording that i can not attach here but if you want i can send it via e mail The next day the technician came but was not able to determine the cause of the disturbing sound so i was offered to change the room once again the hotel was fully booked and they had only 1 room left the one that was smaller but seems newer</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rooms are nice but for elderly a bit difficult as most rooms are two story with narrow steps So ask for single level Inside the rooms are very very basic just tea coffee and boiler and no bar empty fridge</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>My room was dirty and I was afraid to walk barefoot on the floor which looked as if it was not cleaned in weeks White furniture which looked nice in pictures was dirty too and the door looked like it was attacked by an angry dog My shower drain was clogged and the staff did not respond to my request to clean it On a day with heavy rainfall a pretty common occurrence in Amsterdam the roof in my room was leaking luckily not on the bed you could also see signs of earlier water damage I also saw insects running on the floor Overall the second floor of the property looked dirty and badly kept On top of all of this a repairman who came to fix something in a room next door at midnight was very noisy as were many of the guests I understand the challenges of running a hotel in an old building but this negligence is inconsistent with prices demanded by the hotel On the last night after I complained about water damage the night shift manager offered to move me to a different room but that offer came pretty late around midnight when I was already in bed and ready to sleep</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>You When I booked with your company on line you showed me pictures of a room I thought I was getting and paying for and then when we arrived that s room was booked and the staff told me we could only book the villa suite theough them directly Which was completely false advertising After being there we realised that you have grouped lots of rooms on the photos together leaving me the consumer confused and extreamly disgruntled especially as its my my wife s 40th birthday present Please make your website more clear through pricing and photos as again I didn t really know what I was paying for and how much it had wnded up being Your photos told me I was getting something I wasn t Not happy and won t be using you again</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Backyard of the hotel is total mess shouldn t happen in hotel with 4 stars</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No parking Public parking garage is 15 Euro per day</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>no trolly or staff to help you take the luggage to the room</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The hotel looks like 3 but surely not 4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The ac was useless It was a hot week in vienna and it only gave more hot air</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I was in 3rd floor It didn t work Free Wife</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>387848 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   Positive_Review Negative_Review\n",
       "Negative_Review                                                                   \n",
       " I am so angry that i made this post available ...             NaN             NaN\n",
       " Rooms are nice but for elderly a bit difficult...             NaN             NaN\n",
       " My room was dirty and I was afraid to walk bar...             NaN             NaN\n",
       " You When I booked with your company on line yo...             NaN             NaN\n",
       " Backyard of the hotel is total mess shouldn t ...             NaN             NaN\n",
       "...                                                            ...             ...\n",
       " No parking Public parking garage is 15 Euro pe...             NaN             NaN\n",
       " no trolly or staff to help you take the luggag...             NaN             NaN\n",
       " The hotel looks like 3 but surely not 4                       NaN             NaN\n",
       " The ac was useless It was a hot week in vienna...             NaN             NaN\n",
       " I was in 3rd floor It didn t work Free Wife                   NaN             NaN\n",
       "\n",
       "[387848 rows x 2 columns]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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