EDA+Cleaning+Partition.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from collections import Counter\n",
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('data/reviews.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Counts of rows and columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11431, 2)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Checking for nans/nulls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "text      1\n",
       "label    10\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>We visited this nice place during the festive ...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>873</th>\n",
       "      <td>It is quite large in terms of space and the am...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>874</th>\n",
       "      <td>We had some prawn starter and in main course w...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875</th>\n",
       "      <td>Well we should admit that they really make one...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>876</th>\n",
       "      <td>To be very honest I am not a chinese food love...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3544</th>\n",
       "      <td>I had only Biryani from this place.Coming stra...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3545</th>\n",
       "      <td>•I don't know about the hygiene factor.</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3546</th>\n",
       "      <td>•The biryani was over-oily yet very dry.</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3547</th>\n",
       "      <td>•Price is pocket friendly.</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3548</th>\n",
       "      <td>•Quantity is sufficient.</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   text  label\n",
       "872   We visited this nice place during the festive ...    NaN\n",
       "873   It is quite large in terms of space and the am...    NaN\n",
       "874   We had some prawn starter and in main course w...    NaN\n",
       "875   Well we should admit that they really make one...    NaN\n",
       "876   To be very honest I am not a chinese food love...    NaN\n",
       "3544  I had only Biryani from this place.Coming stra...    NaN\n",
       "3545            •I don't know about the hygiene factor.    NaN\n",
       "3546           •The biryani was over-oily yet very dry.    NaN\n",
       "3547                         •Price is pocket friendly.    NaN\n",
       "3548                          •Quantity is sufficient.     NaN"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['label'].isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7370</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     text  label\n",
       "7370  NaN    1.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['text'].isna()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bidding them good bye"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.dropna().reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11420, 2)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysing article lenghts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    11420.000000\n",
       "mean       362.695972\n",
       "std        212.100970\n",
       "min          1.000000\n",
       "25%        199.000000\n",
       "50%        304.000000\n",
       "75%        483.000000\n",
       "max       1066.000000\n",
       "Name: text, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['text'].apply(len).describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Because a picture is worth a 1000 words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-50, 1200)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "text_lens = data['text'].apply(len).values\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches(15, 5)\n",
    "g = sns.distplot(text_lens, kde=False, bins=100, color='red')\n",
    "g.set_xlabel('Character length of reviews')\n",
    "g.set_ylabel('Counts')\n",
    "g.set_xticks(np.arange(-50, 1200, 50))\n",
    "g.set_title('Review length distribution')\n",
    "g.set_xlim(-50, 1200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Manually checking out the smaller articles ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(text_lens <= 2).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3620      v\n",
       "7141     ok\n",
       "9655     😚😚\n",
       "10132    ok\n",
       "10606     3\n",
       "10966     k\n",
       "Name: text, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[text_lens <= 2]['text']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ... and the longer ones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(text_lens > 1000).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2317     #25thDecember\\n\\n#ChristmasDiaries\\n\\nI had he...\n",
       "4917     Initially I was skeptical about this place. Ma...\n",
       "5814     What happens when someone tries to give a fun ...\n",
       "6208     This is a pretty new restaurant and I've been ...\n",
       "6223     One of the classiest place to chill out on a l...\n",
       "6875     Keeping the review crisp and short, since ther...\n",
       "9704     This place used to be our go to takeaway when ...\n",
       "10411    Pao Chein was once a very popular family joint...\n",
       "11176    A regular dinner from this pocket friendly dha...\n",
       "11290    Nu Wan Li is an authentic Chinese restaurant o...\n",
       "Name: text, dtype: object"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[text_lens > 1000]['text']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dropping the smaller articles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data[text_lens > 2].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Now the ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(4.0, 4388),\n",
       " (5.0, 2788),\n",
       " (3.0, 2451),\n",
       " (1.0, 694),\n",
       " (2.0, 626),\n",
       " (3.5, 226),\n",
       " (4.5, 150),\n",
       " (2.5, 69),\n",
       " (1.5, 22)]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_counts = Counter(data['label'].values)\n",
    "label_counts.most_common()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Major class imbalance noticed, but let's talk in %"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "label_counts = {k: (v/data.shape[0])*100 for k, v in label_counts.items()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{5.0: 24.426143332749255,\n",
       " 4.5: 1.3141755738566674,\n",
       " 4.0: 38.444016120553705,\n",
       " 2.0: 5.484492728228491,\n",
       " 3.0: 21.473628876817944,\n",
       " 1.0: 6.080252321710181,\n",
       " 3.5: 1.9800245312773788,\n",
       " 1.5: 0.19274575083231119,\n",
       " 2.5: 0.604520763974067}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_counts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Displying some of the examples from the _'ambiguous'_ class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"Well had been to this place a while back to attend an event. Really loved the banquet space on offer. The open area is a real show stopper. The food is good here. The starters on offer are pretty innovative and tasty. Really enjoyed the mini pizzas and fried chicken ala Kiev though it wasn't really the dish. Simply fried chicken with a tangy dip anyhow does the trick. The Dal makhni tart was innovate. However the Dal makes the casings soft and kills the fun. Food is decent here. Liked the chicken mughlai dish on offer. Need to work on their fish dishes.they use basa which is a tastless fish basically. needs stronger flavours to tingle the palate.\""
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['label'] == 3]['text'].values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Ordered 3 biriyani taste was good.\\nBut quantity was not enough for one people.\\nDelivery was fast.\\nI got the order within 15min.\\n\\nThey should increase their quantity.'"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['label'] == 3]['text'].values[10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Little expensive, ambience is good. \\nTaste is not great! \\nService is fine. \\nChutney is stale, dosa tastes better. \\nI thought rasgulla would taste good but this is the worst rasgulla I’ve ever tasted.'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['label'] == 3]['text'].values[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The best one till date existing amongst all the buffets in kolkata.has been there almost 4-5times.the live grill session is not an unknown thing to Calcuttans.i would like to emphasis about the Greek festival which was on.\\nFood was great,the live Malpoa session could have been a bit better.'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['label'] == 4]['text'].values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'It has been a wonderful Sunday lunch at this joint. Above all, Aliah Restaurant is celebrating Biryani festival at Kolkata and being a Bong, how can i missed that chance to not celebrating this awesome auspicious festival of Biryani.\\nNow something about the food,\\nThey made such a delightful Biryani at this festival too. But all were not available, but they serve quite range of them.\\nIt was a pleasure to being there. They serve Tikka Biryani, Hyderabadi Biryani, kachhi biryani, special chicken biryani.\\nAll of were having an awesome essence of aroma of there genre.\\nWith all I request aliah restaurant to celebrate this festival again'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['label'] == 4]['text'].values[20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I have always been a fan of the egg roll served here..I have eaten the double egg chicken roll a multiple time and ut is totally awesome..I have also eaten mutton biriyani from here..It was also very good...😊😊😊'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['label'] == 4]['text'].values[-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Converting the labels to _'positive'_ and _'negative'_ binary labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def label_map(lbl: float) -> str:\n",
    "    if lbl >= 4:\n",
    "        return 'positive'\n",
    "    else:\n",
    "        return 'negative'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['class'] = data['label'].apply(label_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('positive', 7326), ('negative', 4088)]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_counts = Counter(data['class'].values)\n",
    "label_counts.most_common()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>text</th>\n",
       "      <th>label</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A class service!\\nFood was as always delicious...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>What more to say about a place that we keep on...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Absolutely loved this place. They deserve ever...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>When I hear buffet this name pops up in my bra...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Probably the most famed restaurant in town. Lo...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text  label     class\n",
       "0  A class service!\\nFood was as always delicious...    5.0  positive\n",
       "1  What more to say about a place that we keep on...    4.5  positive\n",
       "2  Absolutely loved this place. They deserve ever...    5.0  positive\n",
       "3  When I hear buffet this name pops up in my bra...    5.0  positive\n",
       "4  Probably the most famed restaurant in town. Lo...    5.0  positive"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11414, 3)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop('label', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spltting the data into train, validation and test sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 80% for train\n",
    "train = data.sample(frac=0.8)\n",
    "data.drop(train.index, axis=0, inplace=True)\n",
    "\n",
    "# 10% for validation\n",
    "valid = data.sample(frac=0.5)\n",
    "data.drop(valid.index, axis=0, inplace=True)\n",
    "\n",
    "# 10% for test\n",
    "test = data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9131, 2)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>text</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3106</th>\n",
       "      <td>I ordered a biryani, and the taste of the Biry...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1927</th>\n",
       "      <td>A nice place to hangout since it has both the ...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5405</th>\n",
       "      <td>This place is awesome for having lunch or dinn...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7426</th>\n",
       "      <td>I got shell of egg in the egg roll. as a resul...</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1669</th>\n",
       "      <td>Their biryani is oily, with a bit disconcertin...</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   text     class\n",
       "3106  I ordered a biryani, and the taste of the Biry...  positive\n",
       "1927  A nice place to hangout since it has both the ...  positive\n",
       "5405  This place is awesome for having lunch or dinn...  positive\n",
       "7426  I got shell of egg in the egg roll. as a resul...  negative\n",
       "1669  Their biryani is oily, with a bit disconcertin...  negative"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1142, 2)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "valid.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>text</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5373</th>\n",
       "      <td>The food was excellent with surplus quantity. ...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7754</th>\n",
       "      <td>This place nearer to the Gitanjali metro stati...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11134</th>\n",
       "      <td>Ordered for Aloo tikki with choley just now @0...</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>Hatari is one of those restaurants that our fa...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8021</th>\n",
       "      <td>Disappointing.......\\nThey have altered the ta...</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    text     class\n",
       "5373   The food was excellent with surplus quantity. ...  positive\n",
       "7754   This place nearer to the Gitanjali metro stati...  positive\n",
       "11134  Ordered for Aloo tikki with choley just now @0...  negative\n",
       "365    Hatari is one of those restaurants that our fa...  positive\n",
       "8021   Disappointing.......\\nThey have altered the ta...  negative"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "valid.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1141, 2)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>text</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>This place is amazing. I think the best place ...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>This place has been on my list for quite some ...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>What a wonderful cold winter evening it was. M...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>BabBQ had always been a personal favorite when...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Know for its Deep Dish Pizza this place is sur...</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 text     class\n",
       "24  This place is amazing. I think the best place ...  positive\n",
       "25  This place has been on my list for quite some ...  positive\n",
       "37  What a wonderful cold winter evening it was. M...  positive\n",
       "49  BabBQ had always been a personal favorite when...  positive\n",
       "60  Know for its Deep Dish Pizza this place is sur...  negative"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finally, saving to disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.to_csv('data/train.csv')\n",
    "valid.to_csv('data/valid.csv')\n",
    "test.to_csv('data/test.csv')"
   ]
  }
 ],
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