zomato_data_set_analysis_visualization.ipynb

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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "brazilian-writer",
   "metadata": {
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    "tags": []
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   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.style.use('dark_background')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "introductory-bulgaria",
   "metadata": {
    "id": "introductory-bulgaria",
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     "start_time": "2021-06-01T09:53:42.874283",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Reading CSV"
   ]
  },
  {
   "cell_type": "code",
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   "id": "competent-hurricane",
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     "status": "completed"
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   "outputs": [
    {
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       "<div>\n",
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       "\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>url</th>\n",
       "      <th>address</th>\n",
       "      <th>name</th>\n",
       "      <th>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>phone</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>dish_liked</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>approx_cost(for two people)</th>\n",
       "      <th>reviews_list</th>\n",
       "      <th>menu_item</th>\n",
       "      <th>listed_in(type)</th>\n",
       "      <th>listed_in(city)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://www.zomato.com/bangalore/jalsa-banasha...</td>\n",
       "      <td>942, 21st Main Road, 2nd Stage, Banashankari, ...</td>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1/5</td>\n",
       "      <td>775</td>\n",
       "      <td>080 42297555\\r\\n+91 9743772233</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Pasta, Lunch Buffet, Masala Papad, Paneer Laja...</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  A beautiful place to ...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://www.zomato.com/bangalore/spice-elephan...</td>\n",
       "      <td>2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...</td>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1/5</td>\n",
       "      <td>787</td>\n",
       "      <td>080 41714161</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Momos, Lunch Buffet, Chocolate Nirvana, Thai G...</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  Had been here for din...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://www.zomato.com/SanchurroBangalore?cont...</td>\n",
       "      <td>1112, Next to KIMS Medical College, 17th Cross...</td>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8/5</td>\n",
       "      <td>918</td>\n",
       "      <td>+91 9663487993</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Churros, Cannelloni, Minestrone Soup, Hot Choc...</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>[('Rated 3.0', \"RATED\\n  Ambience is not that ...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://www.zomato.com/bangalore/addhuri-udupi...</td>\n",
       "      <td>1st Floor, Annakuteera, 3rd Stage, Banashankar...</td>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7/5</td>\n",
       "      <td>88</td>\n",
       "      <td>+91 9620009302</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>Masala Dosa</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>[('Rated 4.0', \"RATED\\n  Great food and proper...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://www.zomato.com/bangalore/grand-village...</td>\n",
       "      <td>10, 3rd Floor, Lakshmi Associates, Gandhi Baza...</td>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8/5</td>\n",
       "      <td>166</td>\n",
       "      <td>+91 8026612447\\r\\n+91 9901210005</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Panipuri, Gol Gappe</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  Very good restaurant ...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 url  \\\n",
       "0  https://www.zomato.com/bangalore/jalsa-banasha...   \n",
       "1  https://www.zomato.com/bangalore/spice-elephan...   \n",
       "2  https://www.zomato.com/SanchurroBangalore?cont...   \n",
       "3  https://www.zomato.com/bangalore/addhuri-udupi...   \n",
       "4  https://www.zomato.com/bangalore/grand-village...   \n",
       "\n",
       "                                             address                   name  \\\n",
       "0  942, 21st Main Road, 2nd Stage, Banashankari, ...                  Jalsa   \n",
       "1  2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...         Spice Elephant   \n",
       "2  1112, Next to KIMS Medical College, 17th Cross...        San Churro Cafe   \n",
       "3  1st Floor, Annakuteera, 3rd Stage, Banashankar...  Addhuri Udupi Bhojana   \n",
       "4  10, 3rd Floor, Lakshmi Associates, Gandhi Baza...          Grand Village   \n",
       "\n",
       "  online_order book_table   rate  votes                             phone  \\\n",
       "0          Yes        Yes  4.1/5    775    080 42297555\\r\\n+91 9743772233   \n",
       "1          Yes         No  4.1/5    787                      080 41714161   \n",
       "2          Yes         No  3.8/5    918                    +91 9663487993   \n",
       "3           No         No  3.7/5     88                    +91 9620009302   \n",
       "4           No         No  3.8/5    166  +91 8026612447\\r\\n+91 9901210005   \n",
       "\n",
       "       location            rest_type  \\\n",
       "0  Banashankari        Casual Dining   \n",
       "1  Banashankari        Casual Dining   \n",
       "2  Banashankari  Cafe, Casual Dining   \n",
       "3  Banashankari          Quick Bites   \n",
       "4  Basavanagudi        Casual Dining   \n",
       "\n",
       "                                          dish_liked  \\\n",
       "0  Pasta, Lunch Buffet, Masala Papad, Paneer Laja...   \n",
       "1  Momos, Lunch Buffet, Chocolate Nirvana, Thai G...   \n",
       "2  Churros, Cannelloni, Minestrone Soup, Hot Choc...   \n",
       "3                                        Masala Dosa   \n",
       "4                                Panipuri, Gol Gappe   \n",
       "\n",
       "                         cuisines approx_cost(for two people)  \\\n",
       "0  North Indian, Mughlai, Chinese                         800   \n",
       "1     Chinese, North Indian, Thai                         800   \n",
       "2          Cafe, Mexican, Italian                         800   \n",
       "3      South Indian, North Indian                         300   \n",
       "4        North Indian, Rajasthani                         600   \n",
       "\n",
       "                                        reviews_list menu_item  \\\n",
       "0  [('Rated 4.0', 'RATED\\n  A beautiful place to ...        []   \n",
       "1  [('Rated 4.0', 'RATED\\n  Had been here for din...        []   \n",
       "2  [('Rated 3.0', \"RATED\\n  Ambience is not that ...        []   \n",
       "3  [('Rated 4.0', \"RATED\\n  Great food and proper...        []   \n",
       "4  [('Rated 4.0', 'RATED\\n  Very good restaurant ...        []   \n",
       "\n",
       "  listed_in(type) listed_in(city)  \n",
       "0          Buffet    Banashankari  \n",
       "1          Buffet    Banashankari  \n",
       "2          Buffet    Banashankari  \n",
       "3          Buffet    Banashankari  \n",
       "4          Buffet    Banashankari  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
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    }
   ],
   "source": [
    "df = pd.read_csv('../input/zomato-bangalore-restaurants/zomato.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
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   "id": "eight-kidney",
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    {
     "data": {
      "text/plain": [
       "(51717, 17)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
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    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "provincial-acquisition",
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    "execution": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['url', 'address', 'name', 'online_order', 'book_table', 'rate', 'votes',\n",
       "       'phone', 'location', 'rest_type', 'dish_liked', 'cuisines',\n",
       "       'approx_cost(for two people)', 'reviews_list', 'menu_item',\n",
       "       'listed_in(type)', 'listed_in(city)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "present-letters",
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    "papermill": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>approx_cost(for two people)</th>\n",
       "      <th>listed_in(type)</th>\n",
       "      <th>listed_in(city)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1/5</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1/5</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8/5</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7/5</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8/5</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table   rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes  4.1/5    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No  4.1/5    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No  3.8/5    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No  3.7/5     88  Banashankari   \n",
       "4          Grand Village           No         No  3.8/5    166  Basavanagudi   \n",
       "\n",
       "             rest_type                        cuisines  \\\n",
       "0        Casual Dining  North Indian, Mughlai, Chinese   \n",
       "1        Casual Dining     Chinese, North Indian, Thai   \n",
       "2  Cafe, Casual Dining          Cafe, Mexican, Italian   \n",
       "3          Quick Bites      South Indian, North Indian   \n",
       "4        Casual Dining        North Indian, Rajasthani   \n",
       "\n",
       "  approx_cost(for two people) listed_in(type) listed_in(city)  \n",
       "0                         800          Buffet    Banashankari  \n",
       "1                         800          Buffet    Banashankari  \n",
       "2                         800          Buffet    Banashankari  \n",
       "3                         300          Buffet    Banashankari  \n",
       "4                         600          Buffet    Banashankari  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.drop(['url', 'address', 'phone', 'menu_item', 'dish_liked', 'reviews_list'], axis = 1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cathedral-hundred",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:54.939106Z",
     "iopub.status.busy": "2021-06-01T09:53:54.938445Z",
     "iopub.status.idle": "2021-06-01T09:53:55.004133Z",
     "shell.execute_reply": "2021-06-01T09:53:55.002535Z",
     "shell.execute_reply.started": "2021-06-01T09:33:31.754049Z"
    },
    "id": "cathedral-hundred",
    "outputId": "0c408bb0-2d42-4543-8781-00a832519573",
    "papermill": {
     "duration": 0.11748,
     "end_time": "2021-06-01T09:53:55.004288",
     "exception": false,
     "start_time": "2021-06-01T09:53:54.886808",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 51717 entries, 0 to 51716\n",
      "Data columns (total 11 columns):\n",
      " #   Column                       Non-Null Count  Dtype \n",
      "---  ------                       --------------  ----- \n",
      " 0   name                         51717 non-null  object\n",
      " 1   online_order                 51717 non-null  object\n",
      " 2   book_table                   51717 non-null  object\n",
      " 3   rate                         43942 non-null  object\n",
      " 4   votes                        51717 non-null  int64 \n",
      " 5   location                     51696 non-null  object\n",
      " 6   rest_type                    51490 non-null  object\n",
      " 7   cuisines                     51672 non-null  object\n",
      " 8   approx_cost(for two people)  51371 non-null  object\n",
      " 9   listed_in(type)              51717 non-null  object\n",
      " 10  listed_in(city)              51717 non-null  object\n",
      "dtypes: int64(1), object(10)\n",
      "memory usage: 4.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "improving-provider",
   "metadata": {
    "id": "improving-provider",
    "papermill": {
     "duration": 0.047007,
     "end_time": "2021-06-01T09:53:55.098746",
     "exception": false,
     "start_time": "2021-06-01T09:53:55.051739",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Dropping Duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "sticky-organic",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:55.201800Z",
     "iopub.status.busy": "2021-06-01T09:53:55.200825Z",
     "iopub.status.idle": "2021-06-01T09:53:55.266387Z",
     "shell.execute_reply": "2021-06-01T09:53:55.265833Z",
     "shell.execute_reply.started": "2021-06-01T09:33:31.823272Z"
    },
    "id": "sticky-organic",
    "outputId": "30d38948-794d-440a-d558-56719ea40ed0",
    "papermill": {
     "duration": 0.12026,
     "end_time": "2021-06-01T09:53:55.266530",
     "exception": false,
     "start_time": "2021-06-01T09:53:55.146270",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(51609, 11)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop_duplicates(inplace = True)\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "constant-specific",
   "metadata": {
    "id": "constant-specific",
    "papermill": {
     "duration": 0.061682,
     "end_time": "2021-06-01T09:53:55.384083",
     "exception": false,
     "start_time": "2021-06-01T09:53:55.322401",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Cleaning Rate Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "interesting-correlation",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:55.492850Z",
     "iopub.status.busy": "2021-06-01T09:53:55.492002Z",
     "iopub.status.idle": "2021-06-01T09:53:55.496035Z",
     "shell.execute_reply": "2021-06-01T09:53:55.495507Z",
     "shell.execute_reply.started": "2021-06-01T09:33:31.910065Z"
    },
    "id": "interesting-correlation",
    "outputId": "6d617a24-992f-447f-d5b2-7ebe2aa1577d",
    "papermill": {
     "duration": 0.061847,
     "end_time": "2021-06-01T09:53:55.496182",
     "exception": false,
     "start_time": "2021-06-01T09:53:55.434335",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['4.1/5', '3.8/5', '3.7/5', '3.6/5', '4.6/5', '4.0/5', '4.2/5',\n",
       "       '3.9/5', '3.1/5', '3.0/5', '3.2/5', '3.3/5', '2.8/5', '4.4/5',\n",
       "       '4.3/5', 'NEW', '2.9/5', '3.5/5', nan, '2.6/5', '3.8 /5', '3.4/5',\n",
       "       '4.5/5', '2.5/5', '2.7/5', '4.7/5', '2.4/5', '2.2/5', '2.3/5',\n",
       "       '3.4 /5', '-', '3.6 /5', '4.8/5', '3.9 /5', '4.2 /5', '4.0 /5',\n",
       "       '4.1 /5', '3.7 /5', '3.1 /5', '2.9 /5', '3.3 /5', '2.8 /5',\n",
       "       '3.5 /5', '2.7 /5', '2.5 /5', '3.2 /5', '2.6 /5', '4.5 /5',\n",
       "       '4.3 /5', '4.4 /5', '4.9/5', '2.1/5', '2.0/5', '1.8/5', '4.6 /5',\n",
       "       '4.9 /5', '3.0 /5', '4.8 /5', '2.3 /5', '4.7 /5', '2.4 /5',\n",
       "       '2.1 /5', '2.2 /5', '2.0 /5', '1.8 /5'], dtype=object)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rate'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "amateur-nicholas",
   "metadata": {
    "id": "amateur-nicholas",
    "papermill": {
     "duration": 0.047512,
     "end_time": "2021-06-01T09:53:55.590934",
     "exception": false,
     "start_time": "2021-06-01T09:53:55.543422",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Removing \"NEW\" ,  \"-\" and \"/5\" from Rate Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "advisory-patent",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:55.712121Z",
     "iopub.status.busy": "2021-06-01T09:53:55.701990Z",
     "iopub.status.idle": "2021-06-01T09:53:55.755760Z",
     "shell.execute_reply": "2021-06-01T09:53:55.756211Z",
     "shell.execute_reply.started": "2021-06-01T09:33:31.926127Z"
    },
    "id": "advisory-patent",
    "outputId": "dfef32a4-5280-400f-8241-c99a856f4af5",
    "papermill": {
     "duration": 0.117921,
     "end_time": "2021-06-01T09:53:55.756378",
     "exception": false,
     "start_time": "2021-06-01T09:53:55.638457",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    4.1\n",
       "1    4.1\n",
       "2    3.8\n",
       "3    3.7\n",
       "4    3.8\n",
       "Name: rate, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def handlerate(value):\n",
    "    if(value=='NEW' or value=='-'):\n",
    "        return np.nan\n",
    "    else:\n",
    "        value = str(value).split('/')\n",
    "        value = value[0]\n",
    "        return float(value)\n",
    "    \n",
    "df['rate'] = df['rate'].apply(handlerate)\n",
    "df['rate'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "nearby-compilation",
   "metadata": {
    "id": "nearby-compilation",
    "papermill": {
     "duration": 0.049129,
     "end_time": "2021-06-01T09:53:55.853771",
     "exception": false,
     "start_time": "2021-06-01T09:53:55.804642",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Filling Null Values in Rate Column with Mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "conscious-chess",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:55.956171Z",
     "iopub.status.busy": "2021-06-01T09:53:55.955531Z",
     "iopub.status.idle": "2021-06-01T09:53:55.961654Z",
     "shell.execute_reply": "2021-06-01T09:53:55.961074Z",
     "shell.execute_reply.started": "2021-06-01T09:33:32.013150Z"
    },
    "id": "conscious-chess",
    "outputId": "39496247-9757-42ca-a760-cb3e8b8d0e86",
    "papermill": {
     "duration": 0.059812,
     "end_time": "2021-06-01T09:53:55.961788",
     "exception": false,
     "start_time": "2021-06-01T09:53:55.901976",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rate'].fillna(df['rate'].mean(), inplace = True)\n",
    "df['rate'].isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "confidential-runner",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:56.061765Z",
     "iopub.status.busy": "2021-06-01T09:53:56.061177Z",
     "iopub.status.idle": "2021-06-01T09:53:56.114573Z",
     "shell.execute_reply": "2021-06-01T09:53:56.115415Z",
     "shell.execute_reply.started": "2021-06-01T09:33:32.027977Z"
    },
    "id": "confidential-runner",
    "outputId": "96f09446-7b89-4504-beae-4dc8de854bc6",
    "papermill": {
     "duration": 0.105089,
     "end_time": "2021-06-01T09:53:56.115650",
     "exception": false,
     "start_time": "2021-06-01T09:53:56.010561",
     "status": "completed"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 51609 entries, 0 to 51716\n",
      "Data columns (total 11 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   name                         51609 non-null  object \n",
      " 1   online_order                 51609 non-null  object \n",
      " 2   book_table                   51609 non-null  object \n",
      " 3   rate                         51609 non-null  float64\n",
      " 4   votes                        51609 non-null  int64  \n",
      " 5   location                     51588 non-null  object \n",
      " 6   rest_type                    51382 non-null  object \n",
      " 7   cuisines                     51564 non-null  object \n",
      " 8   approx_cost(for two people)  51265 non-null  object \n",
      " 9   listed_in(type)              51609 non-null  object \n",
      " 10  listed_in(city)              51609 non-null  object \n",
      "dtypes: float64(1), int64(1), object(9)\n",
      "memory usage: 4.7+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "declared-wisdom",
   "metadata": {
    "id": "declared-wisdom",
    "papermill": {
     "duration": 0.048839,
     "end_time": "2021-06-01T09:53:56.214352",
     "exception": false,
     "start_time": "2021-06-01T09:53:56.165513",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Dropping Null Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "sophisticated-cleaners",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:56.314583Z",
     "iopub.status.busy": "2021-06-01T09:53:56.314025Z",
     "iopub.status.idle": "2021-06-01T09:53:56.398512Z",
     "shell.execute_reply": "2021-06-01T09:53:56.397998Z",
     "shell.execute_reply.started": "2021-06-01T09:33:32.099526Z"
    },
    "id": "sophisticated-cleaners",
    "outputId": "dd6f608c-8e55-4456-c7f2-2c209c165cfe",
    "papermill": {
     "duration": 0.135473,
     "end_time": "2021-06-01T09:53:56.398662",
     "exception": false,
     "start_time": "2021-06-01T09:53:56.263189",
     "status": "completed"
    },
    "tags": []
   },
   "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>name</th>\n",
       "      <th>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>approx_cost(for two people)</th>\n",
       "      <th>listed_in(type)</th>\n",
       "      <th>listed_in(city)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "             rest_type                        cuisines  \\\n",
       "0        Casual Dining  North Indian, Mughlai, Chinese   \n",
       "1        Casual Dining     Chinese, North Indian, Thai   \n",
       "2  Cafe, Casual Dining          Cafe, Mexican, Italian   \n",
       "3          Quick Bites      South Indian, North Indian   \n",
       "4        Casual Dining        North Indian, Rajasthani   \n",
       "\n",
       "  approx_cost(for two people) listed_in(type) listed_in(city)  \n",
       "0                         800          Buffet    Banashankari  \n",
       "1                         800          Buffet    Banashankari  \n",
       "2                         800          Buffet    Banashankari  \n",
       "3                         300          Buffet    Banashankari  \n",
       "4                         600          Buffet    Banashankari  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dropna(inplace = True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "separate-truth",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:56.513431Z",
     "iopub.status.busy": "2021-06-01T09:53:56.512810Z",
     "iopub.status.idle": "2021-06-01T09:53:56.515888Z",
     "shell.execute_reply": "2021-06-01T09:53:56.516358Z",
     "shell.execute_reply.started": "2021-06-01T09:33:32.172403Z"
    },
    "id": "separate-truth",
    "outputId": "00e61254-1a45-4daa-d890-22e1cf70c76c",
    "papermill": {
     "duration": 0.068853,
     "end_time": "2021-06-01T09:53:56.516506",
     "exception": false,
     "start_time": "2021-06-01T09:53:56.447653",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "      <th>listed_in(city)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "             rest_type                        cuisines Cost2plates    Type  \\\n",
       "0        Casual Dining  North Indian, Mughlai, Chinese         800  Buffet   \n",
       "1        Casual Dining     Chinese, North Indian, Thai         800  Buffet   \n",
       "2  Cafe, Casual Dining          Cafe, Mexican, Italian         800  Buffet   \n",
       "3          Quick Bites      South Indian, North Indian         300  Buffet   \n",
       "4        Casual Dining        North Indian, Rajasthani         600  Buffet   \n",
       "\n",
       "  listed_in(city)  \n",
       "0    Banashankari  \n",
       "1    Banashankari  \n",
       "2    Banashankari  \n",
       "3    Banashankari  \n",
       "4    Banashankari  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.rename(columns = {'approx_cost(for two people)':'Cost2plates', 'listed_in(type)':'Type'}, inplace = True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "identified-italy",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:56.617738Z",
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     "shell.execute_reply": "2021-06-01T09:53:56.627343Z",
     "shell.execute_reply.started": "2021-06-01T09:33:32.198921Z"
    },
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    "outputId": "890d8250-7407-42f4-b806-f5952e655fd5",
    "papermill": {
     "duration": 0.061784,
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     "exception": false,
     "start_time": "2021-06-01T09:53:56.565716",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Banashankari', 'Basavanagudi', 'Mysore Road', 'Jayanagar',\n",
       "       'Kumaraswamy Layout', 'Rajarajeshwari Nagar', 'Vijay Nagar',\n",
       "       'Uttarahalli', 'JP Nagar', 'South Bangalore', 'City Market',\n",
       "       'Nagarbhavi', 'Bannerghatta Road', 'BTM', 'Kanakapura Road',\n",
       "       'Bommanahalli', 'CV Raman Nagar', 'Electronic City', 'HSR',\n",
       "       'Marathahalli', 'Wilson Garden', 'Shanti Nagar',\n",
       "       'Koramangala 5th Block', 'Koramangala 8th Block', 'Richmond Road',\n",
       "       'Koramangala 7th Block', 'Jalahalli', 'Koramangala 4th Block',\n",
       "       'Bellandur', 'Sarjapur Road', 'Whitefield', 'East Bangalore',\n",
       "       'Old Airport Road', 'Indiranagar', 'Koramangala 1st Block',\n",
       "       'Frazer Town', 'RT Nagar', 'MG Road', 'Brigade Road',\n",
       "       'Lavelle Road', 'Church Street', 'Ulsoor', 'Residency Road',\n",
       "       'Shivajinagar', 'Infantry Road', 'St. Marks Road',\n",
       "       'Cunningham Road', 'Race Course Road', 'Commercial Street',\n",
       "       'Vasanth Nagar', 'HBR Layout', 'Domlur', 'Ejipura',\n",
       "       'Jeevan Bhima Nagar', 'Old Madras Road', 'Malleshwaram',\n",
       "       'Seshadripuram', 'Kammanahalli', 'Koramangala 6th Block',\n",
       "       'Majestic', 'Langford Town', 'Central Bangalore', 'Sanjay Nagar',\n",
       "       'Brookefield', 'ITPL Main Road, Whitefield',\n",
       "       'Varthur Main Road, Whitefield', 'KR Puram',\n",
       "       'Koramangala 2nd Block', 'Koramangala 3rd Block', 'Koramangala',\n",
       "       'Hosur Road', 'Rajajinagar', 'Banaswadi', 'North Bangalore',\n",
       "       'Nagawara', 'Hennur', 'Kalyan Nagar', 'New BEL Road', 'Jakkur',\n",
       "       'Rammurthy Nagar', 'Thippasandra', 'Kaggadasapura', 'Hebbal',\n",
       "       'Kengeri', 'Sankey Road', 'Sadashiv Nagar', 'Basaveshwara Nagar',\n",
       "       'Yeshwantpur', 'West Bangalore', 'Magadi Road', 'Yelahanka',\n",
       "       'Sahakara Nagar', 'Peenya'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['location'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "likely-bryan",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:56.731690Z",
     "iopub.status.busy": "2021-06-01T09:53:56.731048Z",
     "iopub.status.idle": "2021-06-01T09:53:56.739719Z",
     "shell.execute_reply": "2021-06-01T09:53:56.740273Z",
     "shell.execute_reply.started": "2021-06-01T09:33:32.217217Z"
    },
    "id": "likely-bryan",
    "outputId": "3efa6946-54d5-4530-9b29-fa2bfcf2a3a9",
    "papermill": {
     "duration": 0.06245,
     "end_time": "2021-06-01T09:53:56.740440",
     "exception": false,
     "start_time": "2021-06-01T09:53:56.677990",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Banashankari', 'Bannerghatta Road', 'Basavanagudi', 'Bellandur',\n",
       "       'Brigade Road', 'Brookefield', 'BTM', 'Church Street',\n",
       "       'Electronic City', 'Frazer Town', 'HSR', 'Indiranagar',\n",
       "       'Jayanagar', 'JP Nagar', 'Kalyan Nagar', 'Kammanahalli',\n",
       "       'Koramangala 4th Block', 'Koramangala 5th Block',\n",
       "       'Koramangala 6th Block', 'Koramangala 7th Block', 'Lavelle Road',\n",
       "       'Malleshwaram', 'Marathahalli', 'MG Road', 'New BEL Road',\n",
       "       'Old Airport Road', 'Rajajinagar', 'Residency Road',\n",
       "       'Sarjapur Road', 'Whitefield'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['listed_in(city)'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "polished-joseph",
   "metadata": {
    "id": "polished-joseph",
    "papermill": {
     "duration": 0.053057,
     "end_time": "2021-06-01T09:53:58.208851",
     "exception": false,
     "start_time": "2021-06-01T09:53:58.155794",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Cleaning Location Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "baking-championship",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:58.866579Z",
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     "shell.execute_reply": "2021-06-01T09:53:58.881295Z",
     "shell.execute_reply.started": "2021-06-01T09:33:32.804980Z"
    },
    "id": "baking-championship",
    "outputId": "11bfc4a4-cc25-4bb5-efb9-b5919a958672",
    "papermill": {
     "duration": 0.073436,
     "end_time": "2021-06-01T09:53:58.881468",
     "exception": false,
     "start_time": "2021-06-01T09:53:58.808032",
     "status": "completed"
    },
    "tags": []
   },
   "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>name</th>\n",
       "      <th>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>others</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>others</td>\n",
       "      <td>others</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>others</td>\n",
       "      <td>600.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "       rest_type                        cuisines  Cost2plates    Type  \n",
       "0  Casual Dining  North Indian, Mughlai, Chinese        800.0  Buffet  \n",
       "1  Casual Dining                          others        800.0  Buffet  \n",
       "2         others                          others        800.0  Buffet  \n",
       "3    Quick Bites      South Indian, North Indian        300.0  Buffet  \n",
       "4  Casual Dining                          others        600.0  Buffet  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "foreign-contributor",
   "metadata": {
    "id": "foreign-contributor",
    "papermill": {
     "duration": 0.054967,
     "end_time": "2021-06-01T09:53:59.098954",
     "exception": false,
     "start_time": "2021-06-01T09:53:59.043987",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Count Plot of Various Locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "finnish-ladder",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:53:59.209830Z",
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     "shell.execute_reply": "2021-06-01T09:53:59.762166Z",
     "shell.execute_reply.started": "2021-06-01T09:37:04.547494Z"
    },
    "id": "finnish-ladder",
    "outputId": "99d9bc5f-7544-4d55-b616-ad1952d71535",
    "papermill": {
     "duration": 0.609134,
     "end_time": "2021-06-01T09:53:59.762321",
     "exception": false,
     "start_time": "2021-06-01T09:53:59.153187",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
       "        34, 35, 36, 37, 38, 39, 40, 41]),\n",
       " [Text(0, 0, 'Banashankari'),\n",
       "  Text(1, 0, 'Basavanagudi'),\n",
       "  Text(2, 0, 'others'),\n",
       "  Text(3, 0, 'Jayanagar'),\n",
       "  Text(4, 0, 'JP Nagar'),\n",
       "  Text(5, 0, 'Bannerghatta Road'),\n",
       "  Text(6, 0, 'BTM'),\n",
       "  Text(7, 0, 'Electronic City'),\n",
       "  Text(8, 0, 'HSR'),\n",
       "  Text(9, 0, 'Marathahalli'),\n",
       "  Text(10, 0, 'Shanti Nagar'),\n",
       "  Text(11, 0, 'Koramangala 5th Block'),\n",
       "  Text(12, 0, 'Richmond Road'),\n",
       "  Text(13, 0, 'Koramangala 7th Block'),\n",
       "  Text(14, 0, 'Koramangala 4th Block'),\n",
       "  Text(15, 0, 'Bellandur'),\n",
       "  Text(16, 0, 'Sarjapur Road'),\n",
       "  Text(17, 0, 'Whitefield'),\n",
       "  Text(18, 0, 'Old Airport Road'),\n",
       "  Text(19, 0, 'Indiranagar'),\n",
       "  Text(20, 0, 'Koramangala 1st Block'),\n",
       "  Text(21, 0, 'Frazer Town'),\n",
       "  Text(22, 0, 'MG Road'),\n",
       "  Text(23, 0, 'Brigade Road'),\n",
       "  Text(24, 0, 'Lavelle Road'),\n",
       "  Text(25, 0, 'Church Street'),\n",
       "  Text(26, 0, 'Ulsoor'),\n",
       "  Text(27, 0, 'Residency Road'),\n",
       "  Text(28, 0, 'Shivajinagar'),\n",
       "  Text(29, 0, 'St. Marks Road'),\n",
       "  Text(30, 0, 'Cunningham Road'),\n",
       "  Text(31, 0, 'Commercial Street'),\n",
       "  Text(32, 0, 'Domlur'),\n",
       "  Text(33, 0, 'Ejipura'),\n",
       "  Text(34, 0, 'Malleshwaram'),\n",
       "  Text(35, 0, 'Kammanahalli'),\n",
       "  Text(36, 0, 'Koramangala 6th Block'),\n",
       "  Text(37, 0, 'Brookefield'),\n",
       "  Text(38, 0, 'Rajajinagar'),\n",
       "  Text(39, 0, 'Banaswadi'),\n",
       "  Text(40, 0, 'Kalyan Nagar'),\n",
       "  Text(41, 0, 'New BEL Road')])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (16,10))\n",
    "ax = sns.countplot(df['location'])\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "loose-invitation",
   "metadata": {
    "id": "loose-invitation",
    "papermill": {
     "duration": 0.059209,
     "end_time": "2021-06-01T09:53:59.878363",
     "exception": false,
     "start_time": "2021-06-01T09:53:59.819154",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing Online Order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "adverse-horizontal",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:00.030413Z",
     "iopub.status.busy": "2021-06-01T09:54:00.029777Z",
     "iopub.status.idle": "2021-06-01T09:54:00.166670Z",
     "shell.execute_reply": "2021-06-01T09:54:00.166061Z",
     "shell.execute_reply.started": "2021-06-01T09:33:33.426595Z"
    },
    "id": "adverse-horizontal",
    "outputId": "63cfcb39-a36c-4b78-e2bb-320f0fbd0842",
    "papermill": {
     "duration": 0.229399,
     "end_time": "2021-06-01T09:54:00.166810",
     "exception": false,
     "start_time": "2021-06-01T09:53:59.937411",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='online_order', ylabel='count'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (6,6))\n",
    "sns.countplot(df['online_order'], palette = 'inferno')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "strange-divide",
   "metadata": {
    "id": "strange-divide",
    "papermill": {
     "duration": 0.059353,
     "end_time": "2021-06-01T09:54:00.285303",
     "exception": false,
     "start_time": "2021-06-01T09:54:00.225950",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing Book Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "sapphire-recall",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:00.435659Z",
     "iopub.status.busy": "2021-06-01T09:54:00.434998Z",
     "iopub.status.idle": "2021-06-01T09:54:00.559951Z",
     "shell.execute_reply": "2021-06-01T09:54:00.559359Z",
     "shell.execute_reply.started": "2021-06-01T09:33:33.616802Z"
    },
    "id": "sapphire-recall",
    "outputId": "fbbe6329-1c40-4292-b026-eb35876fcc94",
    "papermill": {
     "duration": 0.21655,
     "end_time": "2021-06-01T09:54:00.560080",
     "exception": false,
     "start_time": "2021-06-01T09:54:00.343530",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='book_table', ylabel='count'>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (6,6))\n",
    "sns.countplot(df['book_table'], palette = 'rainbow')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sweet-implementation",
   "metadata": {
    "id": "sweet-implementation",
    "papermill": {
     "duration": 0.059297,
     "end_time": "2021-06-01T09:54:00.678497",
     "exception": false,
     "start_time": "2021-06-01T09:54:00.619200",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing Online Order vs Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "convinced-coalition",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:00.817279Z",
     "iopub.status.busy": "2021-06-01T09:54:00.814478Z",
     "iopub.status.idle": "2021-06-01T09:54:00.981500Z",
     "shell.execute_reply": "2021-06-01T09:54:00.980857Z",
     "shell.execute_reply.started": "2021-06-01T09:33:33.790461Z"
    },
    "id": "convinced-coalition",
    "outputId": "877d0c89-a1c6-4fd3-81e9-b056245527d1",
    "papermill": {
     "duration": 0.244202,
     "end_time": "2021-06-01T09:54:00.981662",
     "exception": false,
     "start_time": "2021-06-01T09:54:00.737460",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='online_order', ylabel='rate'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (6,6))\n",
    "sns.boxplot(x = 'online_order', y = 'rate', data = df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "enabling-place",
   "metadata": {
    "id": "enabling-place",
    "papermill": {
     "duration": 0.060506,
     "end_time": "2021-06-01T09:54:01.105678",
     "exception": false,
     "start_time": "2021-06-01T09:54:01.045172",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing Book Table vs Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "breathing-surgery",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:01.246174Z",
     "iopub.status.busy": "2021-06-01T09:54:01.237130Z",
     "iopub.status.idle": "2021-06-01T09:54:01.413486Z",
     "shell.execute_reply": "2021-06-01T09:54:01.413948Z",
     "shell.execute_reply.started": "2021-06-01T09:33:34.299515Z"
    },
    "id": "breathing-surgery",
    "outputId": "57970e8d-8e4a-4a0c-9422-0a476f091873",
    "papermill": {
     "duration": 0.247785,
     "end_time": "2021-06-01T09:54:01.414118",
     "exception": false,
     "start_time": "2021-06-01T09:54:01.166333",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='book_table', ylabel='rate'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (6,6))\n",
    "sns.boxplot(x = 'book_table', y = 'rate', data = df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "corresponding-heath",
   "metadata": {
    "id": "corresponding-heath",
    "papermill": {
     "duration": 0.061118,
     "end_time": "2021-06-01T09:54:01.536437",
     "exception": false,
     "start_time": "2021-06-01T09:54:01.475319",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing Online Order Facility, Location Wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "rapid-console",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:01.667695Z",
     "iopub.status.busy": "2021-06-01T09:54:01.666819Z",
     "iopub.status.idle": "2021-06-01T09:54:01.819242Z",
     "shell.execute_reply": "2021-06-01T09:54:01.818161Z",
     "shell.execute_reply.started": "2021-06-01T09:33:34.485329Z"
    },
    "id": "rapid-console",
    "outputId": "5e863141-304c-4bee-8ead-bb446d5f9e72",
    "papermill": {
     "duration": 0.221708,
     "end_time": "2021-06-01T09:54:01.819399",
     "exception": false,
     "start_time": "2021-06-01T09:54:01.597691",
     "status": "completed"
    },
    "tags": []
   },
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>online_order</th>\n",
       "      <th>No</th>\n",
       "      <th>Yes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BTM</th>\n",
       "      <td>1763</td>\n",
       "      <td>3293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Banashankari</th>\n",
       "      <td>397</td>\n",
       "      <td>505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Banaswadi</th>\n",
       "      <td>302</td>\n",
       "      <td>338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bannerghatta Road</th>\n",
       "      <td>685</td>\n",
       "      <td>924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Basavanagudi</th>\n",
       "      <td>243</td>\n",
       "      <td>441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bellandur</th>\n",
       "      <td>517</td>\n",
       "      <td>751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brigade Road</th>\n",
       "      <td>552</td>\n",
       "      <td>658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brookefield</th>\n",
       "      <td>239</td>\n",
       "      <td>417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Church Street</th>\n",
       "      <td>226</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Commercial Street</th>\n",
       "      <td>228</td>\n",
       "      <td>142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cunningham Road</th>\n",
       "      <td>168</td>\n",
       "      <td>322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Domlur</th>\n",
       "      <td>247</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ejipura</th>\n",
       "      <td>214</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electronic City</th>\n",
       "      <td>676</td>\n",
       "      <td>570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frazer Town</th>\n",
       "      <td>287</td>\n",
       "      <td>427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HSR</th>\n",
       "      <td>584</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiranagar</th>\n",
       "      <td>697</td>\n",
       "      <td>1329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JP Nagar</th>\n",
       "      <td>911</td>\n",
       "      <td>1307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jayanagar</th>\n",
       "      <td>552</td>\n",
       "      <td>1364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kalyan Nagar</th>\n",
       "      <td>350</td>\n",
       "      <td>491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kammanahalli</th>\n",
       "      <td>264</td>\n",
       "      <td>375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 1st Block</th>\n",
       "      <td>384</td>\n",
       "      <td>852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 4th Block</th>\n",
       "      <td>459</td>\n",
       "      <td>558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 5th Block</th>\n",
       "      <td>866</td>\n",
       "      <td>1613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 6th Block</th>\n",
       "      <td>445</td>\n",
       "      <td>682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 7th Block</th>\n",
       "      <td>389</td>\n",
       "      <td>785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lavelle Road</th>\n",
       "      <td>315</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MG Road</th>\n",
       "      <td>520</td>\n",
       "      <td>373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malleshwaram</th>\n",
       "      <td>309</td>\n",
       "      <td>412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marathahalli</th>\n",
       "      <td>701</td>\n",
       "      <td>1104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New BEL Road</th>\n",
       "      <td>255</td>\n",
       "      <td>389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Old Airport Road</th>\n",
       "      <td>221</td>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajajinagar</th>\n",
       "      <td>286</td>\n",
       "      <td>305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Residency Road</th>\n",
       "      <td>424</td>\n",
       "      <td>247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richmond Road</th>\n",
       "      <td>557</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sarjapur Road</th>\n",
       "      <td>323</td>\n",
       "      <td>724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shanti Nagar</th>\n",
       "      <td>289</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shivajinagar</th>\n",
       "      <td>354</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St. Marks Road</th>\n",
       "      <td>176</td>\n",
       "      <td>167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ulsoor</th>\n",
       "      <td>389</td>\n",
       "      <td>622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Whitefield</th>\n",
       "      <td>986</td>\n",
       "      <td>1119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>others</th>\n",
       "      <td>2064</td>\n",
       "      <td>2890</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name      \n",
       "online_order             No   Yes\n",
       "location                         \n",
       "BTM                    1763  3293\n",
       "Banashankari            397   505\n",
       "Banaswadi               302   338\n",
       "Bannerghatta Road       685   924\n",
       "Basavanagudi            243   441\n",
       "Bellandur               517   751\n",
       "Brigade Road            552   658\n",
       "Brookefield             239   417\n",
       "Church Street           226   340\n",
       "Commercial Street       228   142\n",
       "Cunningham Road         168   322\n",
       "Domlur                  247   235\n",
       "Ejipura                 214   219\n",
       "Electronic City         676   570\n",
       "Frazer Town             287   427\n",
       "HSR                     584  1910\n",
       "Indiranagar             697  1329\n",
       "JP Nagar                911  1307\n",
       "Jayanagar               552  1364\n",
       "Kalyan Nagar            350   491\n",
       "Kammanahalli            264   375\n",
       "Koramangala 1st Block   384   852\n",
       "Koramangala 4th Block   459   558\n",
       "Koramangala 5th Block   866  1613\n",
       "Koramangala 6th Block   445   682\n",
       "Koramangala 7th Block   389   785\n",
       "Lavelle Road            315   203\n",
       "MG Road                 520   373\n",
       "Malleshwaram            309   412\n",
       "Marathahalli            701  1104\n",
       "New BEL Road            255   389\n",
       "Old Airport Road        221   216\n",
       "Rajajinagar             286   305\n",
       "Residency Road          424   247\n",
       "Richmond Road           557   246\n",
       "Sarjapur Road           323   724\n",
       "Shanti Nagar            289   219\n",
       "Shivajinagar            354   144\n",
       "St. Marks Road          176   167\n",
       "Ulsoor                  389   622\n",
       "Whitefield              986  1119\n",
       "others                 2064  2890"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = df.groupby(['location','online_order'])['name'].count()\n",
    "df1.to_csv('location_online.csv')\n",
    "df1 = pd.read_csv('location_online.csv')\n",
    "df1 = pd.pivot_table(df1, values=None, index=['location'], columns=['online_order'], fill_value=0, aggfunc=np.sum)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "rocky-pixel",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:01.949103Z",
     "iopub.status.busy": "2021-06-01T09:54:01.948466Z",
     "iopub.status.idle": "2021-06-01T09:54:02.668484Z",
     "shell.execute_reply": "2021-06-01T09:54:02.668014Z",
     "shell.execute_reply.started": "2021-06-01T09:33:34.536729Z"
    },
    "id": "rocky-pixel",
    "outputId": "37b3cc06-2aef-4941-ffd1-687bcf78f9bb",
    "papermill": {
     "duration": 0.786975,
     "end_time": "2021-06-01T09:54:02.668631",
     "exception": false,
     "start_time": "2021-06-01T09:54:01.881656",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='location'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.plot(kind = 'bar', figsize = (15,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "automatic-trigger",
   "metadata": {
    "id": "automatic-trigger",
    "papermill": {
     "duration": 0.064557,
     "end_time": "2021-06-01T09:54:02.797131",
     "exception": false,
     "start_time": "2021-06-01T09:54:02.732574",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing Book Table Facility, Location Wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "generous-burke",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:02.935382Z",
     "iopub.status.busy": "2021-06-01T09:54:02.934294Z",
     "iopub.status.idle": "2021-06-01T09:54:02.974213Z",
     "shell.execute_reply": "2021-06-01T09:54:02.973723Z",
     "shell.execute_reply.started": "2021-06-01T09:33:35.281782Z"
    },
    "id": "generous-burke",
    "outputId": "fbe6596a-c68c-486b-fc1c-20e4bdfff701",
    "papermill": {
     "duration": 0.112585,
     "end_time": "2021-06-01T09:54:02.974362",
     "exception": false,
     "start_time": "2021-06-01T09:54:02.861777",
     "status": "completed"
    },
    "tags": []
   },
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>book_table</th>\n",
       "      <th>No</th>\n",
       "      <th>Yes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BTM</th>\n",
       "      <td>4889</td>\n",
       "      <td>167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Banashankari</th>\n",
       "      <td>839</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Banaswadi</th>\n",
       "      <td>632</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bannerghatta Road</th>\n",
       "      <td>1510</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Basavanagudi</th>\n",
       "      <td>668</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bellandur</th>\n",
       "      <td>1170</td>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brigade Road</th>\n",
       "      <td>1034</td>\n",
       "      <td>176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brookefield</th>\n",
       "      <td>582</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Church Street</th>\n",
       "      <td>385</td>\n",
       "      <td>181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Commercial Street</th>\n",
       "      <td>370</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cunningham Road</th>\n",
       "      <td>315</td>\n",
       "      <td>175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Domlur</th>\n",
       "      <td>427</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ejipura</th>\n",
       "      <td>433</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electronic City</th>\n",
       "      <td>1148</td>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frazer Town</th>\n",
       "      <td>706</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HSR</th>\n",
       "      <td>2277</td>\n",
       "      <td>217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiranagar</th>\n",
       "      <td>1578</td>\n",
       "      <td>448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JP Nagar</th>\n",
       "      <td>1903</td>\n",
       "      <td>315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jayanagar</th>\n",
       "      <td>1637</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kalyan Nagar</th>\n",
       "      <td>692</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kammanahalli</th>\n",
       "      <td>590</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 1st Block</th>\n",
       "      <td>1186</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 4th Block</th>\n",
       "      <td>695</td>\n",
       "      <td>322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 5th Block</th>\n",
       "      <td>1787</td>\n",
       "      <td>692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 6th Block</th>\n",
       "      <td>1015</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 7th Block</th>\n",
       "      <td>1012</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lavelle Road</th>\n",
       "      <td>290</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MG Road</th>\n",
       "      <td>546</td>\n",
       "      <td>347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malleshwaram</th>\n",
       "      <td>632</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marathahalli</th>\n",
       "      <td>1642</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New BEL Road</th>\n",
       "      <td>588</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Old Airport Road</th>\n",
       "      <td>378</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajajinagar</th>\n",
       "      <td>550</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Residency Road</th>\n",
       "      <td>522</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richmond Road</th>\n",
       "      <td>687</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sarjapur Road</th>\n",
       "      <td>893</td>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shanti Nagar</th>\n",
       "      <td>451</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shivajinagar</th>\n",
       "      <td>475</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St. Marks Road</th>\n",
       "      <td>219</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ulsoor</th>\n",
       "      <td>834</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Whitefield</th>\n",
       "      <td>1852</td>\n",
       "      <td>253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>others</th>\n",
       "      <td>4587</td>\n",
       "      <td>367</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name     \n",
       "book_table               No  Yes\n",
       "location                        \n",
       "BTM                    4889  167\n",
       "Banashankari            839   63\n",
       "Banaswadi               632    8\n",
       "Bannerghatta Road      1510   99\n",
       "Basavanagudi            668   16\n",
       "Bellandur              1170   98\n",
       "Brigade Road           1034  176\n",
       "Brookefield             582   74\n",
       "Church Street           385  181\n",
       "Commercial Street       370    0\n",
       "Cunningham Road         315  175\n",
       "Domlur                  427   55\n",
       "Ejipura                 433    0\n",
       "Electronic City        1148   98\n",
       "Frazer Town             706    8\n",
       "HSR                    2277  217\n",
       "Indiranagar            1578  448\n",
       "JP Nagar               1903  315\n",
       "Jayanagar              1637  279\n",
       "Kalyan Nagar            692  149\n",
       "Kammanahalli            590   49\n",
       "Koramangala 1st Block  1186   50\n",
       "Koramangala 4th Block   695  322\n",
       "Koramangala 5th Block  1787  692\n",
       "Koramangala 6th Block  1015  112\n",
       "Koramangala 7th Block  1012  162\n",
       "Lavelle Road            290  228\n",
       "MG Road                 546  347\n",
       "Malleshwaram            632   89\n",
       "Marathahalli           1642  163\n",
       "New BEL Road            588   56\n",
       "Old Airport Road        378   59\n",
       "Rajajinagar             550   41\n",
       "Residency Road          522  149\n",
       "Richmond Road           687  116\n",
       "Sarjapur Road           893  154\n",
       "Shanti Nagar            451   57\n",
       "Shivajinagar            475   23\n",
       "St. Marks Road          219  124\n",
       "Ulsoor                  834  177\n",
       "Whitefield             1852  253\n",
       "others                 4587  367"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df.groupby(['location','book_table'])['name'].count()\n",
    "df2.to_csv('location_booktable.csv')\n",
    "df2 = pd.read_csv('location_booktable.csv')\n",
    "df2 = pd.pivot_table(df2, values=None, index=['location'], columns=['book_table'], fill_value=0, aggfunc=np.sum)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "emerging-trail",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:03.136451Z",
     "iopub.status.busy": "2021-06-01T09:54:03.135048Z",
     "iopub.status.idle": "2021-06-01T09:54:03.817863Z",
     "shell.execute_reply": "2021-06-01T09:54:03.817280Z",
     "shell.execute_reply.started": "2021-06-01T09:33:35.337462Z"
    },
    "id": "emerging-trail",
    "outputId": "a1a4fd7b-b214-4bd0-d1e7-8220b770f428",
    "papermill": {
     "duration": 0.777966,
     "end_time": "2021-06-01T09:54:03.817997",
     "exception": false,
     "start_time": "2021-06-01T09:54:03.040031",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='location'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.plot(kind = 'bar', figsize = (15,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "collect-motivation",
   "metadata": {
    "id": "collect-motivation",
    "papermill": {
     "duration": 0.066564,
     "end_time": "2021-06-01T09:54:03.951565",
     "exception": false,
     "start_time": "2021-06-01T09:54:03.885001",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing Types of Restaurents vs Rate "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "studied-wildlife",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:04.108956Z",
     "iopub.status.busy": "2021-06-01T09:54:04.106156Z",
     "iopub.status.idle": "2021-06-01T09:54:04.382643Z",
     "shell.execute_reply": "2021-06-01T09:54:04.382118Z",
     "shell.execute_reply.started": "2021-06-01T09:33:36.136948Z"
    },
    "id": "studied-wildlife",
    "outputId": "9a9ceb86-4f4d-4f8f-f16e-3c6bf47c2dd5",
    "papermill": {
     "duration": 0.362541,
     "end_time": "2021-06-01T09:54:04.382775",
     "exception": false,
     "start_time": "2021-06-01T09:54:04.020234",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Type', ylabel='rate'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (14, 8))\n",
    "sns.boxplot(x = 'Type', y = 'rate', data = df, palette = 'inferno')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sought-renaissance",
   "metadata": {
    "id": "sought-renaissance",
    "papermill": {
     "duration": 0.06771,
     "end_time": "2021-06-01T09:54:04.518455",
     "exception": false,
     "start_time": "2021-06-01T09:54:04.450745",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Grouping Types of Restaurents, location wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "meaning-psychology",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:04.663509Z",
     "iopub.status.busy": "2021-06-01T09:54:04.662621Z",
     "iopub.status.idle": "2021-06-01T09:54:04.711191Z",
     "shell.execute_reply": "2021-06-01T09:54:04.710660Z",
     "shell.execute_reply.started": "2021-06-01T09:33:36.465464Z"
    },
    "id": "meaning-psychology",
    "outputId": "74e76a72-db8b-4526-c3ef-25af1621ac6a",
    "papermill": {
     "duration": 0.124901,
     "end_time": "2021-06-01T09:54:04.711327",
     "exception": false,
     "start_time": "2021-06-01T09:54:04.586426",
     "status": "completed"
    },
    "tags": []
   },
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"7\" halign=\"left\">name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Type</th>\n",
       "      <th>Buffet</th>\n",
       "      <th>Cafes</th>\n",
       "      <th>Delivery</th>\n",
       "      <th>Desserts</th>\n",
       "      <th>Dine-out</th>\n",
       "      <th>Drinks &amp; nightlife</th>\n",
       "      <th>Pubs and bars</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BTM</th>\n",
       "      <td>21</td>\n",
       "      <td>83</td>\n",
       "      <td>3053</td>\n",
       "      <td>198</td>\n",
       "      <td>1660</td>\n",
       "      <td>22</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Banashankari</th>\n",
       "      <td>7</td>\n",
       "      <td>36</td>\n",
       "      <td>418</td>\n",
       "      <td>71</td>\n",
       "      <td>356</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Banaswadi</th>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>310</td>\n",
       "      <td>37</td>\n",
       "      <td>262</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bannerghatta Road</th>\n",
       "      <td>9</td>\n",
       "      <td>46</td>\n",
       "      <td>828</td>\n",
       "      <td>137</td>\n",
       "      <td>578</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Basavanagudi</th>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>344</td>\n",
       "      <td>66</td>\n",
       "      <td>251</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bellandur</th>\n",
       "      <td>28</td>\n",
       "      <td>36</td>\n",
       "      <td>617</td>\n",
       "      <td>75</td>\n",
       "      <td>479</td>\n",
       "      <td>17</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brigade Road</th>\n",
       "      <td>25</td>\n",
       "      <td>46</td>\n",
       "      <td>497</td>\n",
       "      <td>108</td>\n",
       "      <td>455</td>\n",
       "      <td>57</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brookefield</th>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>339</td>\n",
       "      <td>45</td>\n",
       "      <td>245</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Church Street</th>\n",
       "      <td>19</td>\n",
       "      <td>51</td>\n",
       "      <td>193</td>\n",
       "      <td>29</td>\n",
       "      <td>215</td>\n",
       "      <td>36</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Commercial Street</th>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>121</td>\n",
       "      <td>77</td>\n",
       "      <td>159</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cunningham Road</th>\n",
       "      <td>29</td>\n",
       "      <td>34</td>\n",
       "      <td>194</td>\n",
       "      <td>26</td>\n",
       "      <td>184</td>\n",
       "      <td>16</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Domlur</th>\n",
       "      <td>15</td>\n",
       "      <td>13</td>\n",
       "      <td>261</td>\n",
       "      <td>35</td>\n",
       "      <td>135</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ejipura</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>245</td>\n",
       "      <td>16</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electronic City</th>\n",
       "      <td>23</td>\n",
       "      <td>24</td>\n",
       "      <td>570</td>\n",
       "      <td>71</td>\n",
       "      <td>516</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frazer Town</th>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>470</td>\n",
       "      <td>56</td>\n",
       "      <td>172</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HSR</th>\n",
       "      <td>19</td>\n",
       "      <td>49</td>\n",
       "      <td>1694</td>\n",
       "      <td>120</td>\n",
       "      <td>580</td>\n",
       "      <td>14</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiranagar</th>\n",
       "      <td>38</td>\n",
       "      <td>97</td>\n",
       "      <td>1091</td>\n",
       "      <td>140</td>\n",
       "      <td>529</td>\n",
       "      <td>65</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JP Nagar</th>\n",
       "      <td>45</td>\n",
       "      <td>76</td>\n",
       "      <td>1151</td>\n",
       "      <td>166</td>\n",
       "      <td>722</td>\n",
       "      <td>51</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jayanagar</th>\n",
       "      <td>27</td>\n",
       "      <td>77</td>\n",
       "      <td>1043</td>\n",
       "      <td>182</td>\n",
       "      <td>575</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kalyan Nagar</th>\n",
       "      <td>9</td>\n",
       "      <td>45</td>\n",
       "      <td>366</td>\n",
       "      <td>88</td>\n",
       "      <td>315</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kammanahalli</th>\n",
       "      <td>2</td>\n",
       "      <td>27</td>\n",
       "      <td>329</td>\n",
       "      <td>35</td>\n",
       "      <td>240</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 1st Block</th>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>716</td>\n",
       "      <td>70</td>\n",
       "      <td>398</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 4th Block</th>\n",
       "      <td>21</td>\n",
       "      <td>53</td>\n",
       "      <td>464</td>\n",
       "      <td>81</td>\n",
       "      <td>302</td>\n",
       "      <td>62</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 5th Block</th>\n",
       "      <td>65</td>\n",
       "      <td>146</td>\n",
       "      <td>1075</td>\n",
       "      <td>209</td>\n",
       "      <td>842</td>\n",
       "      <td>84</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 6th Block</th>\n",
       "      <td>18</td>\n",
       "      <td>43</td>\n",
       "      <td>511</td>\n",
       "      <td>70</td>\n",
       "      <td>411</td>\n",
       "      <td>51</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 7th Block</th>\n",
       "      <td>25</td>\n",
       "      <td>52</td>\n",
       "      <td>503</td>\n",
       "      <td>127</td>\n",
       "      <td>417</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lavelle Road</th>\n",
       "      <td>30</td>\n",
       "      <td>27</td>\n",
       "      <td>127</td>\n",
       "      <td>50</td>\n",
       "      <td>191</td>\n",
       "      <td>59</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MG Road</th>\n",
       "      <td>51</td>\n",
       "      <td>76</td>\n",
       "      <td>266</td>\n",
       "      <td>68</td>\n",
       "      <td>343</td>\n",
       "      <td>53</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malleshwaram</th>\n",
       "      <td>11</td>\n",
       "      <td>31</td>\n",
       "      <td>269</td>\n",
       "      <td>85</td>\n",
       "      <td>291</td>\n",
       "      <td>20</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marathahalli</th>\n",
       "      <td>34</td>\n",
       "      <td>32</td>\n",
       "      <td>980</td>\n",
       "      <td>105</td>\n",
       "      <td>630</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New BEL Road</th>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>338</td>\n",
       "      <td>33</td>\n",
       "      <td>224</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Old Airport Road</th>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>200</td>\n",
       "      <td>35</td>\n",
       "      <td>164</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajajinagar</th>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>258</td>\n",
       "      <td>55</td>\n",
       "      <td>251</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Residency Road</th>\n",
       "      <td>20</td>\n",
       "      <td>31</td>\n",
       "      <td>187</td>\n",
       "      <td>63</td>\n",
       "      <td>289</td>\n",
       "      <td>55</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richmond Road</th>\n",
       "      <td>63</td>\n",
       "      <td>21</td>\n",
       "      <td>257</td>\n",
       "      <td>78</td>\n",
       "      <td>356</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sarjapur Road</th>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>558</td>\n",
       "      <td>82</td>\n",
       "      <td>319</td>\n",
       "      <td>19</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shanti Nagar</th>\n",
       "      <td>9</td>\n",
       "      <td>22</td>\n",
       "      <td>198</td>\n",
       "      <td>39</td>\n",
       "      <td>229</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shivajinagar</th>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>143</td>\n",
       "      <td>37</td>\n",
       "      <td>280</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St. Marks Road</th>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>111</td>\n",
       "      <td>10</td>\n",
       "      <td>145</td>\n",
       "      <td>40</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ulsoor</th>\n",
       "      <td>16</td>\n",
       "      <td>56</td>\n",
       "      <td>456</td>\n",
       "      <td>71</td>\n",
       "      <td>359</td>\n",
       "      <td>23</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Whitefield</th>\n",
       "      <td>28</td>\n",
       "      <td>51</td>\n",
       "      <td>1041</td>\n",
       "      <td>137</td>\n",
       "      <td>768</td>\n",
       "      <td>47</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>others</th>\n",
       "      <td>83</td>\n",
       "      <td>133</td>\n",
       "      <td>2787</td>\n",
       "      <td>276</td>\n",
       "      <td>1553</td>\n",
       "      <td>75</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name                                   \\\n",
       "Type                  Buffet Cafes Delivery Desserts Dine-out   \n",
       "location                                                        \n",
       "BTM                       21    83     3053      198     1660   \n",
       "Banashankari               7    36      418       71      356   \n",
       "Banaswadi                  0    24      310       37      262   \n",
       "Bannerghatta Road          9    46      828      137      578   \n",
       "Basavanagudi               7    11      344       66      251   \n",
       "Bellandur                 28    36      617       75      479   \n",
       "Brigade Road              25    46      497      108      455   \n",
       "Brookefield                6    17      339       45      245   \n",
       "Church Street             19    51      193       29      215   \n",
       "Commercial Street          0    13      121       77      159   \n",
       "Cunningham Road           29    34      194       26      184   \n",
       "Domlur                    15    13      261       35      135   \n",
       "Ejipura                    0     0      245       16      172   \n",
       "Electronic City           23    24      570       71      516   \n",
       "Frazer Town                1    11      470       56      172   \n",
       "HSR                       19    49     1694      120      580   \n",
       "Indiranagar               38    97     1091      140      529   \n",
       "JP Nagar                  45    76     1151      166      722   \n",
       "Jayanagar                 27    77     1043      182      575   \n",
       "Kalyan Nagar               9    45      366       88      315   \n",
       "Kammanahalli               2    27      329       35      240   \n",
       "Koramangala 1st Block      3    26      716       70      398   \n",
       "Koramangala 4th Block     21    53      464       81      302   \n",
       "Koramangala 5th Block     65   146     1075      209      842   \n",
       "Koramangala 6th Block     18    43      511       70      411   \n",
       "Koramangala 7th Block     25    52      503      127      417   \n",
       "Lavelle Road              30    27      127       50      191   \n",
       "MG Road                   51    76      266       68      343   \n",
       "Malleshwaram              11    31      269       85      291   \n",
       "Marathahalli              34    32      980      105      630   \n",
       "New BEL Road               4    29      338       33      224   \n",
       "Old Airport Road          12     5      200       35      164   \n",
       "Rajajinagar               10     4      258       55      251   \n",
       "Residency Road            20    31      187       63      289   \n",
       "Richmond Road             63    21      257       78      356   \n",
       "Sarjapur Road             25    22      558       82      319   \n",
       "Shanti Nagar               9    22      198       39      229   \n",
       "Shivajinagar               6    17      143       37      280   \n",
       "St. Marks Road             5    10      111       10      145   \n",
       "Ulsoor                    16    56      456       71      359   \n",
       "Whitefield                28    51     1041      137      768   \n",
       "others                    83   133     2787      276     1553   \n",
       "\n",
       "                                                        \n",
       "Type                  Drinks & nightlife Pubs and bars  \n",
       "location                                                \n",
       "BTM                                   22            19  \n",
       "Banashankari                          14             0  \n",
       "Banaswadi                              6             1  \n",
       "Bannerghatta Road                      9             2  \n",
       "Basavanagudi                           5             0  \n",
       "Bellandur                             17            16  \n",
       "Brigade Road                          57            22  \n",
       "Brookefield                            4             0  \n",
       "Church Street                         36            23  \n",
       "Commercial Street                      0             0  \n",
       "Cunningham Road                       16             7  \n",
       "Domlur                                12            11  \n",
       "Ejipura                                0             0  \n",
       "Electronic City                       21            21  \n",
       "Frazer Town                            2             2  \n",
       "HSR                                   14            18  \n",
       "Indiranagar                           65            66  \n",
       "JP Nagar                              51             7  \n",
       "Jayanagar                             12             0  \n",
       "Kalyan Nagar                          18             0  \n",
       "Kammanahalli                           6             0  \n",
       "Koramangala 1st Block                  7            16  \n",
       "Koramangala 4th Block                 62            34  \n",
       "Koramangala 5th Block                 84            58  \n",
       "Koramangala 6th Block                 51            23  \n",
       "Koramangala 7th Block                 25            25  \n",
       "Lavelle Road                          59            34  \n",
       "MG Road                               53            36  \n",
       "Malleshwaram                          20            14  \n",
       "Marathahalli                          22             2  \n",
       "New BEL Road                           8             8  \n",
       "Old Airport Road                      12             9  \n",
       "Rajajinagar                            3            10  \n",
       "Residency Road                        55            26  \n",
       "Richmond Road                         16            12  \n",
       "Sarjapur Road                         19            22  \n",
       "Shanti Nagar                           9             2  \n",
       "Shivajinagar                           7             8  \n",
       "St. Marks Road                        40            22  \n",
       "Ulsoor                                23            30  \n",
       "Whitefield                            47            33  \n",
       "others                                75            47  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = df.groupby(['location','Type'])['name'].count()\n",
    "df3.to_csv('location_Type.csv')\n",
    "df3 = pd.read_csv('location_Type.csv')\n",
    "df3 = pd.pivot_table(df3, values=None, index=['location'], columns=['Type'], fill_value=0, aggfunc=np.sum)\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "expressed-happiness",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:04.883149Z",
     "iopub.status.busy": "2021-06-01T09:54:04.881713Z",
     "iopub.status.idle": "2021-06-01T09:54:06.220854Z",
     "shell.execute_reply": "2021-06-01T09:54:06.221311Z",
     "shell.execute_reply.started": "2021-06-01T09:33:36.535410Z"
    },
    "id": "expressed-happiness",
    "outputId": "16bf55e4-2a60-4dea-a254-f8ad1fc70747",
    "papermill": {
     "duration": 1.441312,
     "end_time": "2021-06-01T09:54:06.221466",
     "exception": false,
     "start_time": "2021-06-01T09:54:04.780154",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='location'>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2592x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df3.plot(kind = 'bar', figsize = (36,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "public-theory",
   "metadata": {
    "id": "public-theory",
    "papermill": {
     "duration": 0.098341,
     "end_time": "2021-06-01T09:54:06.392675",
     "exception": false,
     "start_time": "2021-06-01T09:54:06.294334",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## No. of Votes, Location Wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "falling-battlefield",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:06.543083Z",
     "iopub.status.busy": "2021-06-01T09:54:06.542391Z",
     "iopub.status.idle": "2021-06-01T09:54:06.567370Z",
     "shell.execute_reply": "2021-06-01T09:54:06.566728Z",
     "shell.execute_reply.started": "2021-06-01T09:41:49.578105Z"
    },
    "id": "falling-battlefield",
    "outputId": "198d0889-0d5d-4066-f224-88594b994499",
    "papermill": {
     "duration": 0.102753,
     "end_time": "2021-06-01T09:54:06.567499",
     "exception": false,
     "start_time": "2021-06-01T09:54:06.464746",
     "status": "completed"
    },
    "tags": []
   },
   "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>votes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Koramangala 5th Block</th>\n",
       "      <td>2214083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiranagar</th>\n",
       "      <td>1165909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koramangala 4th Block</th>\n",
       "      <td>685156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Church Street</th>\n",
       "      <td>590306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JP Nagar</th>\n",
       "      <td>586522</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         votes\n",
       "location                      \n",
       "Koramangala 5th Block  2214083\n",
       "Indiranagar            1165909\n",
       "Koramangala 4th Block   685156\n",
       "Church Street           590306\n",
       "JP Nagar                586522"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4 = df[['location', 'votes']]\n",
    "df4.drop_duplicates()\n",
    "df5 = df4.groupby(['location'])['votes'].sum()\n",
    "df5 = df5.to_frame()\n",
    "df5 = df5.sort_values('votes', ascending=False)\n",
    "df5.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "studied-slovenia",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:06.757711Z",
     "iopub.status.busy": "2021-06-01T09:54:06.741931Z",
     "iopub.status.idle": "2021-06-01T09:54:07.376007Z",
     "shell.execute_reply": "2021-06-01T09:54:07.375481Z",
     "shell.execute_reply.started": "2021-06-01T09:42:51.938417Z"
    },
    "id": "studied-slovenia",
    "outputId": "70fb7e4c-72bd-445d-fc02-1f385367b650",
    "papermill": {
     "duration": 0.734685,
     "end_time": "2021-06-01T09:54:07.376138",
     "exception": false,
     "start_time": "2021-06-01T09:54:06.641453",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
       "        34, 35, 36, 37, 38, 39, 40, 41]),\n",
       " [Text(0, 0, 'Koramangala 5th Block'),\n",
       "  Text(1, 0, 'Indiranagar'),\n",
       "  Text(2, 0, 'Koramangala 4th Block'),\n",
       "  Text(3, 0, 'Church Street'),\n",
       "  Text(4, 0, 'JP Nagar'),\n",
       "  Text(5, 0, 'BTM'),\n",
       "  Text(6, 0, 'others'),\n",
       "  Text(7, 0, 'HSR'),\n",
       "  Text(8, 0, 'Lavelle Road'),\n",
       "  Text(9, 0, 'Koramangala 7th Block'),\n",
       "  Text(10, 0, 'Jayanagar'),\n",
       "  Text(11, 0, 'Whitefield'),\n",
       "  Text(12, 0, 'Koramangala 6th Block'),\n",
       "  Text(13, 0, 'Marathahalli'),\n",
       "  Text(14, 0, 'MG Road'),\n",
       "  Text(15, 0, 'Brigade Road'),\n",
       "  Text(16, 0, 'Sarjapur Road'),\n",
       "  Text(17, 0, 'Residency Road'),\n",
       "  Text(18, 0, 'Cunningham Road'),\n",
       "  Text(19, 0, 'St. Marks Road'),\n",
       "  Text(20, 0, 'Koramangala 1st Block'),\n",
       "  Text(21, 0, 'Malleshwaram'),\n",
       "  Text(22, 0, 'Bannerghatta Road'),\n",
       "  Text(23, 0, 'Bellandur'),\n",
       "  Text(24, 0, 'Ulsoor'),\n",
       "  Text(25, 0, 'New BEL Road'),\n",
       "  Text(26, 0, 'Kalyan Nagar'),\n",
       "  Text(27, 0, 'Banashankari'),\n",
       "  Text(28, 0, 'Old Airport Road'),\n",
       "  Text(29, 0, 'Brookefield'),\n",
       "  Text(30, 0, 'Richmond Road'),\n",
       "  Text(31, 0, 'Electronic City'),\n",
       "  Text(32, 0, 'Kammanahalli'),\n",
       "  Text(33, 0, 'Frazer Town'),\n",
       "  Text(34, 0, 'Domlur'),\n",
       "  Text(35, 0, 'Basavanagudi'),\n",
       "  Text(36, 0, 'Rajajinagar'),\n",
       "  Text(37, 0, 'Shanti Nagar'),\n",
       "  Text(38, 0, 'Banaswadi'),\n",
       "  Text(39, 0, 'Commercial Street'),\n",
       "  Text(40, 0, 'Ejipura'),\n",
       "  Text(41, 0, 'Shivajinagar')])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15,8))\n",
    "sns.barplot(df5.index , df5['votes'])\n",
    "plt.xticks(rotation = 90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "wooden-monday",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:07.530620Z",
     "iopub.status.busy": "2021-06-01T09:54:07.530012Z",
     "iopub.status.idle": "2021-06-01T09:54:07.543712Z",
     "shell.execute_reply": "2021-06-01T09:54:07.543179Z",
     "shell.execute_reply.started": "2021-06-01T09:33:40.831364Z"
    },
    "id": "wooden-monday",
    "outputId": "8a906ee1-8410-4451-e01c-32f19e2035b9",
    "papermill": {
     "duration": 0.092587,
     "end_time": "2021-06-01T09:54:07.543845",
     "exception": false,
     "start_time": "2021-06-01T09:54:07.451258",
     "status": "completed"
    },
    "tags": []
   },
   "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>name</th>\n",
       "      <th>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>others</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>others</td>\n",
       "      <td>others</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>others</td>\n",
       "      <td>600.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "       rest_type                        cuisines  Cost2plates    Type  \n",
       "0  Casual Dining  North Indian, Mughlai, Chinese        800.0  Buffet  \n",
       "1  Casual Dining                          others        800.0  Buffet  \n",
       "2         others                          others        800.0  Buffet  \n",
       "3    Quick Bites      South Indian, North Indian        300.0  Buffet  \n",
       "4  Casual Dining                          others        600.0  Buffet  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "comfortable-comparative",
   "metadata": {
    "id": "comfortable-comparative",
    "papermill": {
     "duration": 0.074452,
     "end_time": "2021-06-01T09:54:07.692793",
     "exception": false,
     "start_time": "2021-06-01T09:54:07.618341",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Visualizing Top Cuisines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "positive-snowboard",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:07.851779Z",
     "iopub.status.busy": "2021-06-01T09:54:07.851161Z",
     "iopub.status.idle": "2021-06-01T09:54:07.871060Z",
     "shell.execute_reply": "2021-06-01T09:54:07.871608Z",
     "shell.execute_reply.started": "2021-06-01T09:46:03.838722Z"
    },
    "id": "positive-snowboard",
    "outputId": "cf6452d4-683b-4be0-ad5e-5aaba0b86df7",
    "papermill": {
     "duration": 0.103319,
     "end_time": "2021-06-01T09:54:07.871769",
     "exception": false,
     "start_time": "2021-06-01T09:54:07.768450",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>votes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cuisines</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>others</th>\n",
       "      <td>11542182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Indian</th>\n",
       "      <td>516310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Indian, Chinese</th>\n",
       "      <td>258225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Indian</th>\n",
       "      <td>161975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Indian, Mughlai</th>\n",
       "      <td>103706</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          votes\n",
       "cuisines                       \n",
       "others                 11542182\n",
       "North Indian             516310\n",
       "North Indian, Chinese    258225\n",
       "South Indian             161975\n",
       "North Indian, Mughlai    103706"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df6 = df[['cuisines', 'votes']]\n",
    "df6.drop_duplicates()\n",
    "df7 = df6.groupby(['cuisines'])['votes'].sum()\n",
    "df7 = df7.to_frame()\n",
    "df7 = df7.sort_values('votes', ascending=False)\n",
    "df7.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "reasonable-shape",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:08.026965Z",
     "iopub.status.busy": "2021-06-01T09:54:08.026356Z",
     "iopub.status.idle": "2021-06-01T09:54:08.034286Z",
     "shell.execute_reply": "2021-06-01T09:54:08.034872Z",
     "shell.execute_reply.started": "2021-06-01T09:48:05.758474Z"
    },
    "id": "reasonable-shape",
    "outputId": "8665a1bb-bef4-4146-864b-a2f9e9528931",
    "papermill": {
     "duration": 0.088597,
     "end_time": "2021-06-01T09:54:08.035049",
     "exception": false,
     "start_time": "2021-06-01T09:54:07.946452",
     "status": "completed"
    },
    "tags": []
   },
   "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>votes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cuisines</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>North Indian</th>\n",
       "      <td>516310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Indian, Chinese</th>\n",
       "      <td>258225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Indian</th>\n",
       "      <td>161975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Indian, Mughlai</th>\n",
       "      <td>103706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chinese</th>\n",
       "      <td>101728</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        votes\n",
       "cuisines                     \n",
       "North Indian           516310\n",
       "North Indian, Chinese  258225\n",
       "South Indian           161975\n",
       "North Indian, Mughlai  103706\n",
       "Chinese                101728"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df7 = df7.iloc[1:, :]\n",
    "df7.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "expired-effect",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T09:54:08.189467Z",
     "iopub.status.busy": "2021-06-01T09:54:08.188908Z",
     "iopub.status.idle": "2021-06-01T09:54:09.710214Z",
     "shell.execute_reply": "2021-06-01T09:54:09.710937Z",
     "shell.execute_reply.started": "2021-06-01T09:48:09.068524Z"
    },
    "id": "expired-effect",
    "outputId": "f8233a4f-28e1-4618-c417-9e757d20e3c2",
    "papermill": {
     "duration": 1.600366,
     "end_time": "2021-06-01T09:54:09.711146",
     "exception": false,
     "start_time": "2021-06-01T09:54:08.110780",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
       "        34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50,\n",
       "        51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,\n",
       "        68]),\n",
       " [Text(0, 0, 'North Indian'),\n",
       "  Text(1, 0, 'North Indian, Chinese'),\n",
       "  Text(2, 0, 'South Indian'),\n",
       "  Text(3, 0, 'North Indian, Mughlai'),\n",
       "  Text(4, 0, 'Chinese'),\n",
       "  Text(5, 0, 'Cafe'),\n",
       "  Text(6, 0, 'North Indian, South Indian'),\n",
       "  Text(7, 0, 'Desserts'),\n",
       "  Text(8, 0, 'Chinese, Momos'),\n",
       "  Text(9, 0, 'Ice Cream, Desserts'),\n",
       "  Text(10, 0, 'Cafe, Continental'),\n",
       "  Text(11, 0, 'Biryani, North Indian, Chinese'),\n",
       "  Text(12, 0, 'Chinese, Thai, Momos'),\n",
       "  Text(13, 0, 'South Indian, North Indian, Chinese'),\n",
       "  Text(14, 0, 'Desserts, Beverages'),\n",
       "  Text(15, 0, 'Biryani'),\n",
       "  Text(16, 0, 'Finger Food'),\n",
       "  Text(17, 0, 'Bakery, Desserts'),\n",
       "  Text(18, 0, 'Burger, Fast Food'),\n",
       "  Text(19, 0, 'Continental'),\n",
       "  Text(20, 0, 'Cafe, Desserts'),\n",
       "  Text(21, 0, 'Andhra, Biryani'),\n",
       "  Text(22, 0, 'North Indian, Continental'),\n",
       "  Text(23, 0, 'Pizza, Fast Food'),\n",
       "  Text(24, 0, 'Chinese, Thai'),\n",
       "  Text(25, 0, 'North Indian, Chinese, Biryani'),\n",
       "  Text(26, 0, 'South Indian, North Indian, Chinese, Street Food'),\n",
       "  Text(27, 0, 'Mithai, Street Food'),\n",
       "  Text(28, 0, 'North Indian, South Indian, Chinese'),\n",
       "  Text(29, 0, 'Desserts, Ice Cream'),\n",
       "  Text(30, 0, 'Biryani, North Indian'),\n",
       "  Text(31, 0, 'North Indian, Street Food'),\n",
       "  Text(32, 0, 'Fast Food'),\n",
       "  Text(33, 0, 'North Indian, Chinese, Seafood'),\n",
       "  Text(34, 0, 'Chinese, North Indian'),\n",
       "  Text(35, 0, 'North Indian, Biryani'),\n",
       "  Text(36, 0, 'Biryani, Kebab'),\n",
       "  Text(37, 0, 'Italian, Pizza'),\n",
       "  Text(38, 0, 'North Indian, Chinese, Fast Food'),\n",
       "  Text(39, 0, 'North Indian, Chinese, Continental'),\n",
       "  Text(40, 0, 'Desserts, Bakery'),\n",
       "  Text(41, 0, 'Arabian'),\n",
       "  Text(42, 0, 'North Indian, Chinese, South Indian'),\n",
       "  Text(43, 0, 'Pizza'),\n",
       "  Text(44, 0, 'South Indian, North Indian'),\n",
       "  Text(45, 0, 'North Indian, Mughlai, Chinese'),\n",
       "  Text(46, 0, 'Beverages, Fast Food'),\n",
       "  Text(47, 0, 'South Indian, Biryani'),\n",
       "  Text(48, 0, 'Fast Food, Rolls'),\n",
       "  Text(49, 0, 'Bakery'),\n",
       "  Text(50, 0, 'Andhra'),\n",
       "  Text(51, 0, 'Street Food'),\n",
       "  Text(52, 0, 'Kerala'),\n",
       "  Text(53, 0, 'Cafe, Bakery'),\n",
       "  Text(54, 0, 'Biryani, Fast Food'),\n",
       "  Text(55, 0, 'South Indian, Fast Food'),\n",
       "  Text(56, 0, 'North Indian, Fast Food'),\n",
       "  Text(57, 0, 'Bakery, Fast Food'),\n",
       "  Text(58, 0, 'Fast Food, Burger'),\n",
       "  Text(59, 0, 'Cafe, Fast Food'),\n",
       "  Text(60, 0, 'South Indian, Chinese'),\n",
       "  Text(61, 0, 'Beverages, Desserts'),\n",
       "  Text(62, 0, 'Ice Cream'),\n",
       "  Text(63, 0, 'Beverages'),\n",
       "  Text(64, 0, 'Biryani, South Indian'),\n",
       "  Text(65, 0, 'Kerala, South Indian'),\n",
       "  Text(66, 0, 'Fast Food, Beverages'),\n",
       "  Text(67, 0, 'South Indian, Chinese, North Indian'),\n",
       "  Text(68, 0, 'Mithai')])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15,8))\n",
    "sns.barplot(df7.index , df7['votes'])\n",
    "plt.xticks(rotation = 90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "operational-jaguar",
   "metadata": {
    "id": "operational-jaguar",
    "papermill": {
     "duration": 0.080221,
     "end_time": "2021-06-01T09:54:09.872102",
     "exception": false,
     "start_time": "2021-06-01T09:54:09.791881",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [
    "nearby-compilation",
    "foreign-contributor",
    "loose-invitation",
    "strange-divide",
    "sweet-implementation",
    "enabling-place",
    "corresponding-heath",
    "automatic-trigger",
    "collect-motivation",
    "sought-renaissance",
    "public-theory"
   ],
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.0"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 36.668039,
   "end_time": "2021-06-01T09:54:10.763857",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2021-06-01T09:53:34.095818",
   "version": "2.3.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}