zomato-dataset-eda-visualisation.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":352891,"sourceType":"datasetVersion","datasetId":153420}],"dockerImageVersionId":30635,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2024-01-26T13:53:08.687340Z","iopub.execute_input":"2024-01-26T13:53:08.687833Z","iopub.status.idle":"2024-01-26T13:53:09.109584Z","shell.execute_reply.started":"2024-01-26T13:53:08.687792Z","shell.execute_reply":"2024-01-26T13:53:09.108377Z"},"trusted":true},"execution_count":1,"outputs":[{"name":"stdout","text":"/kaggle/input/zomato-bangalore-restaurants/zomato.csv\n","output_type":"stream"}]},{"cell_type":"markdown","source":"## Importing Libraries","metadata":{}},{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nplt.style.use('dark_background')","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:09.111752Z","iopub.execute_input":"2024-01-26T13:53:09.112187Z","iopub.status.idle":"2024-01-26T13:53:09.697128Z","shell.execute_reply.started":"2024-01-26T13:53:09.112158Z","shell.execute_reply":"2024-01-26T13:53:09.695986Z"},"trusted":true},"execution_count":2,"outputs":[]},{"cell_type":"markdown","source":"## Loading the CSV Data","metadata":{}},{"cell_type":"code","source":"df = pd.read_csv(\"/kaggle/input/zomato-bangalore-restaurants/zomato.csv\")\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:09.698422Z","iopub.execute_input":"2024-01-26T13:53:09.698715Z","iopub.status.idle":"2024-01-26T13:53:21.551283Z","shell.execute_reply.started":"2024-01-26T13:53:09.698688Z","shell.execute_reply":"2024-01-26T13:53:21.550166Z"},"trusted":true},"execution_count":3,"outputs":[{"execution_count":3,"output_type":"execute_result","data":{"text/plain":"                                                 url  \\\n0  https://www.zomato.com/bangalore/jalsa-banasha...   \n1  https://www.zomato.com/bangalore/spice-elephan...   \n2  https://www.zomato.com/SanchurroBangalore?cont...   \n3  https://www.zomato.com/bangalore/addhuri-udupi...   \n4  https://www.zomato.com/bangalore/grand-village...   \n\n                                             address                   name  \\\n0  942, 21st Main Road, 2nd Stage, Banashankari, ...                  Jalsa   \n1  2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...         Spice Elephant   \n2  1112, Next to KIMS Medical College, 17th Cross...        San Churro Cafe   \n3  1st Floor, Annakuteera, 3rd Stage, Banashankar...  Addhuri Udupi Bhojana   \n4  10, 3rd Floor, Lakshmi Associates, Gandhi Baza...          Grand Village   \n\n  online_order book_table   rate  votes                             phone  \\\n0          Yes        Yes  4.1/5    775    080 42297555\\r\\n+91 9743772233   \n1          Yes         No  4.1/5    787                      080 41714161   \n2          Yes         No  3.8/5    918                    +91 9663487993   \n3           No         No  3.7/5     88                    +91 9620009302   \n4           No         No  3.8/5    166  +91 8026612447\\r\\n+91 9901210005   \n\n       location            rest_type  \\\n0  Banashankari        Casual Dining   \n1  Banashankari        Casual Dining   \n2  Banashankari  Cafe, Casual Dining   \n3  Banashankari          Quick Bites   \n4  Basavanagudi        Casual Dining   \n\n                                          dish_liked  \\\n0  Pasta, Lunch Buffet, Masala Papad, Paneer Laja...   \n1  Momos, Lunch Buffet, Chocolate Nirvana, Thai G...   \n2  Churros, Cannelloni, Minestrone Soup, Hot Choc...   \n3                                        Masala Dosa   \n4                                Panipuri, Gol Gappe   \n\n                         cuisines approx_cost(for two people)  \\\n0  North Indian, Mughlai, Chinese                         800   \n1     Chinese, North Indian, Thai                         800   \n2          Cafe, Mexican, Italian                         800   \n3      South Indian, North Indian                         300   \n4        North Indian, Rajasthani                         600   \n\n                                        reviews_list menu_item  \\\n0  [('Rated 4.0', 'RATED\\n  A beautiful place to ...        []   \n1  [('Rated 4.0', 'RATED\\n  Had been here for din...        []   \n2  [('Rated 3.0', \"RATED\\n  Ambience is not that ...        []   \n3  [('Rated 4.0', \"RATED\\n  Great food and proper...        []   \n4  [('Rated 4.0', 'RATED\\n  Very good restaurant ...        []   \n\n  listed_in(type) listed_in(city)  \n0          Buffet    Banashankari  \n1          Buffet    Banashankari  \n2          Buffet    Banashankari  \n3          Buffet    Banashankari  \n4          Buffet    Banashankari  ","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>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>"},"metadata":{}}]},{"cell_type":"markdown","source":"## Analysis ","metadata":{}},{"cell_type":"code","source":"df.shape","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.552996Z","iopub.execute_input":"2024-01-26T13:53:21.553462Z","iopub.status.idle":"2024-01-26T13:53:21.560969Z","shell.execute_reply.started":"2024-01-26T13:53:21.553404Z","shell.execute_reply":"2024-01-26T13:53:21.559821Z"},"trusted":true},"execution_count":4,"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":"(51717, 17)"},"metadata":{}}]},{"cell_type":"code","source":"df.columns","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.564677Z","iopub.execute_input":"2024-01-26T13:53:21.565137Z","iopub.status.idle":"2024-01-26T13:53:21.578216Z","shell.execute_reply.started":"2024-01-26T13:53:21.565105Z","shell.execute_reply":"2024-01-26T13:53:21.576923Z"},"trusted":true},"execution_count":5,"outputs":[{"execution_count":5,"output_type":"execute_result","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')"},"metadata":{}}]},{"cell_type":"code","source":"df.drop(['url', 'address', 'menu_item', 'dish_liked', 'reviews_list'], axis=1, inplace=True)\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.579766Z","iopub.execute_input":"2024-01-26T13:53:21.580249Z","iopub.status.idle":"2024-01-26T13:53:21.618571Z","shell.execute_reply.started":"2024-01-26T13:53:21.580208Z","shell.execute_reply":"2024-01-26T13:53:21.617514Z"},"trusted":true},"execution_count":6,"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"                    name online_order book_table   rate  votes  \\\n0                  Jalsa          Yes        Yes  4.1/5    775   \n1         Spice Elephant          Yes         No  4.1/5    787   \n2        San Churro Cafe          Yes         No  3.8/5    918   \n3  Addhuri Udupi Bhojana           No         No  3.7/5     88   \n4          Grand Village           No         No  3.8/5    166   \n\n                              phone      location            rest_type  \\\n0    080 42297555\\r\\n+91 9743772233  Banashankari        Casual Dining   \n1                      080 41714161  Banashankari        Casual Dining   \n2                    +91 9663487993  Banashankari  Cafe, Casual Dining   \n3                    +91 9620009302  Banashankari          Quick Bites   \n4  +91 8026612447\\r\\n+91 9901210005  Basavanagudi        Casual Dining   \n\n                         cuisines approx_cost(for two people) listed_in(type)  \\\n0  North Indian, Mughlai, Chinese                         800          Buffet   \n1     Chinese, North Indian, Thai                         800          Buffet   \n2          Cafe, Mexican, Italian                         800          Buffet   \n3      South Indian, North Indian                         300          Buffet   \n4        North Indian, Rajasthani                         600          Buffet   \n\n  listed_in(city)  \n0    Banashankari  \n1    Banashankari  \n2    Banashankari  \n3    Banashankari  \n4    Banashankari  ","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>phone</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>080 42297555\\r\\n+91 9743772233</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>080 41714161</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>+91 9663487993</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>+91 9620009302</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>+91 8026612447\\r\\n+91 9901210005</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>"},"metadata":{}}]},{"cell_type":"code","source":"df.info()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.619800Z","iopub.execute_input":"2024-01-26T13:53:21.620152Z","iopub.status.idle":"2024-01-26T13:53:21.755400Z","shell.execute_reply.started":"2024-01-26T13:53:21.620123Z","shell.execute_reply":"2024-01-26T13:53:21.754231Z"},"trusted":true},"execution_count":7,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 51717 entries, 0 to 51716\nData columns (total 12 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   phone                        50509 non-null  object\n 6   location                     51696 non-null  object\n 7   rest_type                    51490 non-null  object\n 8   cuisines                     51672 non-null  object\n 9   approx_cost(for two people)  51371 non-null  object\n 10  listed_in(type)              51717 non-null  object\n 11  listed_in(city)              51717 non-null  object\ndtypes: int64(1), object(11)\nmemory usage: 4.7+ MB\n","output_type":"stream"}]},{"cell_type":"markdown","source":"### dropping duplicates","metadata":{}},{"cell_type":"code","source":"df.drop_duplicates(inplace=True)\ndf.shape","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.756986Z","iopub.execute_input":"2024-01-26T13:53:21.757560Z","iopub.status.idle":"2024-01-26T13:53:21.839088Z","shell.execute_reply.started":"2024-01-26T13:53:21.757515Z","shell.execute_reply":"2024-01-26T13:53:21.837878Z"},"trusted":true},"execution_count":8,"outputs":[{"execution_count":8,"output_type":"execute_result","data":{"text/plain":"(51621, 12)"},"metadata":{}}]},{"cell_type":"markdown","source":"### Cleaning the rate column","metadata":{}},{"cell_type":"code","source":"df['rate'].unique()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.840642Z","iopub.execute_input":"2024-01-26T13:53:21.841016Z","iopub.status.idle":"2024-01-26T13:53:21.851225Z","shell.execute_reply.started":"2024-01-26T13:53:21.840986Z","shell.execute_reply":"2024-01-26T13:53:21.849794Z"},"trusted":true},"execution_count":9,"outputs":[{"execution_count":9,"output_type":"execute_result","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)"},"metadata":{}}]},{"cell_type":"code","source":"def handle_rate(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    \ndf['rate'] = df['rate'].apply(handle_rate)\ndf['rate'][:5]","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.852150Z","iopub.execute_input":"2024-01-26T13:53:21.852490Z","iopub.status.idle":"2024-01-26T13:53:21.907749Z","shell.execute_reply.started":"2024-01-26T13:53:21.852452Z","shell.execute_reply":"2024-01-26T13:53:21.906309Z"},"trusted":true},"execution_count":10,"outputs":[{"execution_count":10,"output_type":"execute_result","data":{"text/plain":"0    4.1\n1    4.1\n2    3.8\n3    3.7\n4    3.8\nName: rate, dtype: float64"},"metadata":{}}]},{"cell_type":"markdown","source":"Checking for the presence of null values","metadata":{}},{"cell_type":"code","source":"df.rate.isnull().sum()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.909340Z","iopub.execute_input":"2024-01-26T13:53:21.910102Z","iopub.status.idle":"2024-01-26T13:53:21.918887Z","shell.execute_reply.started":"2024-01-26T13:53:21.910052Z","shell.execute_reply":"2024-01-26T13:53:21.917643Z"},"trusted":true},"execution_count":11,"outputs":[{"execution_count":11,"output_type":"execute_result","data":{"text/plain":"10023"},"metadata":{}}]},{"cell_type":"markdown","source":"### Filling the null values with the mean","metadata":{}},{"cell_type":"code","source":"df['rate'].fillna(df['rate'].mean(), inplace=True)\ndf.rate.isnull().sum()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.920506Z","iopub.execute_input":"2024-01-26T13:53:21.920858Z","iopub.status.idle":"2024-01-26T13:53:21.935394Z","shell.execute_reply.started":"2024-01-26T13:53:21.920826Z","shell.execute_reply":"2024-01-26T13:53:21.934480Z"},"trusted":true},"execution_count":12,"outputs":[{"execution_count":12,"output_type":"execute_result","data":{"text/plain":"0"},"metadata":{}}]},{"cell_type":"code","source":"df.info()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.936865Z","iopub.execute_input":"2024-01-26T13:53:21.937457Z","iopub.status.idle":"2024-01-26T13:53:21.979771Z","shell.execute_reply.started":"2024-01-26T13:53:21.937395Z","shell.execute_reply":"2024-01-26T13:53:21.978873Z"},"trusted":true},"execution_count":13,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nIndex: 51621 entries, 0 to 51716\nData columns (total 12 columns):\n #   Column                       Non-Null Count  Dtype  \n---  ------                       --------------  -----  \n 0   name                         51621 non-null  object \n 1   online_order                 51621 non-null  object \n 2   book_table                   51621 non-null  object \n 3   rate                         51621 non-null  float64\n 4   votes                        51621 non-null  int64  \n 5   phone                        50416 non-null  object \n 6   location                     51600 non-null  object \n 7   rest_type                    51394 non-null  object \n 8   cuisines                     51576 non-null  object \n 9   approx_cost(for two people)  51277 non-null  object \n 10  listed_in(type)              51621 non-null  object \n 11  listed_in(city)              51621 non-null  object \ndtypes: float64(1), int64(1), object(10)\nmemory usage: 5.1+ MB\n","output_type":"stream"}]},{"cell_type":"markdown","source":"### Dropping Null Values and Renaming Columns","metadata":{}},{"cell_type":"code","source":"df.dropna(inplace=True)\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:21.984606Z","iopub.execute_input":"2024-01-26T13:53:21.985181Z","iopub.status.idle":"2024-01-26T13:53:22.037273Z","shell.execute_reply.started":"2024-01-26T13:53:21.985145Z","shell.execute_reply":"2024-01-26T13:53:22.036087Z"},"trusted":true},"execution_count":14,"outputs":[{"execution_count":14,"output_type":"execute_result","data":{"text/plain":"                    name online_order book_table  rate  votes  \\\n0                  Jalsa          Yes        Yes   4.1    775   \n1         Spice Elephant          Yes         No   4.1    787   \n2        San Churro Cafe          Yes         No   3.8    918   \n3  Addhuri Udupi Bhojana           No         No   3.7     88   \n4          Grand Village           No         No   3.8    166   \n\n                              phone      location            rest_type  \\\n0    080 42297555\\r\\n+91 9743772233  Banashankari        Casual Dining   \n1                      080 41714161  Banashankari        Casual Dining   \n2                    +91 9663487993  Banashankari  Cafe, Casual Dining   \n3                    +91 9620009302  Banashankari          Quick Bites   \n4  +91 8026612447\\r\\n+91 9901210005  Basavanagudi        Casual Dining   \n\n                         cuisines approx_cost(for two people) listed_in(type)  \\\n0  North Indian, Mughlai, Chinese                         800          Buffet   \n1     Chinese, North Indian, Thai                         800          Buffet   \n2          Cafe, Mexican, Italian                         800          Buffet   \n3      South Indian, North Indian                         300          Buffet   \n4        North Indian, Rajasthani                         600          Buffet   \n\n  listed_in(city)  \n0    Banashankari  \n1    Banashankari  \n2    Banashankari  \n3    Banashankari  \n4    Banashankari  ","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>phone</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>080 42297555\\r\\n+91 9743772233</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>080 41714161</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>+91 9663487993</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>+91 9620009302</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>+91 8026612447\\r\\n+91 9901210005</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>"},"metadata":{}}]},{"cell_type":"code","source":"df.rename(columns={'approx_cost(for two people)': \"cost2plates\",\n                   'listed_in(type)': 'type',\n                   'listed_in(city)': 'city'},\n         inplace=True)\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.038874Z","iopub.execute_input":"2024-01-26T13:53:22.039626Z","iopub.status.idle":"2024-01-26T13:53:22.057573Z","shell.execute_reply.started":"2024-01-26T13:53:22.039580Z","shell.execute_reply":"2024-01-26T13:53:22.056712Z"},"trusted":true},"execution_count":15,"outputs":[{"execution_count":15,"output_type":"execute_result","data":{"text/plain":"                    name online_order book_table  rate  votes  \\\n0                  Jalsa          Yes        Yes   4.1    775   \n1         Spice Elephant          Yes         No   4.1    787   \n2        San Churro Cafe          Yes         No   3.8    918   \n3  Addhuri Udupi Bhojana           No         No   3.7     88   \n4          Grand Village           No         No   3.8    166   \n\n                              phone      location            rest_type  \\\n0    080 42297555\\r\\n+91 9743772233  Banashankari        Casual Dining   \n1                      080 41714161  Banashankari        Casual Dining   \n2                    +91 9663487993  Banashankari  Cafe, Casual Dining   \n3                    +91 9620009302  Banashankari          Quick Bites   \n4  +91 8026612447\\r\\n+91 9901210005  Basavanagudi        Casual Dining   \n\n                         cuisines cost2plates    type          city  \n0  North Indian, Mughlai, Chinese         800  Buffet  Banashankari  \n1     Chinese, North Indian, Thai         800  Buffet  Banashankari  \n2          Cafe, Mexican, Italian         800  Buffet  Banashankari  \n3      South Indian, North Indian         300  Buffet  Banashankari  \n4        North Indian, Rajasthani         600  Buffet  Banashankari  ","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>phone</th>\n      <th>location</th>\n      <th>rest_type</th>\n      <th>cuisines</th>\n      <th>cost2plates</th>\n      <th>type</th>\n      <th>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>080 42297555\\r\\n+91 9743772233</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>080 41714161</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>+91 9663487993</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>+91 9620009302</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>+91 8026612447\\r\\n+91 9901210005</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>"},"metadata":{}}]},{"cell_type":"code","source":"df['location'].unique()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.058640Z","iopub.execute_input":"2024-01-26T13:53:22.059639Z","iopub.status.idle":"2024-01-26T13:53:22.074850Z","shell.execute_reply.started":"2024-01-26T13:53:22.059578Z","shell.execute_reply":"2024-01-26T13:53:22.073993Z"},"trusted":true},"execution_count":16,"outputs":[{"execution_count":16,"output_type":"execute_result","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       'Bannerghatta Road', 'BTM', 'Kanakapura Road', 'Bommanahalli',\n       'CV Raman Nagar', 'Electronic City', 'HSR', 'Marathahalli',\n       'Wilson Garden', 'Shanti Nagar', 'Koramangala 5th Block',\n       'Koramangala 8th Block', 'Richmond Road', 'Koramangala 7th Block',\n       'Jalahalli', 'Koramangala 4th Block', 'Bellandur', 'Sarjapur Road',\n       'Whitefield', 'East Bangalore', 'Old Airport Road', 'Indiranagar',\n       'Koramangala 1st Block', 'Frazer Town', 'RT Nagar', 'MG Road',\n       'Brigade Road', 'Lavelle Road', 'Church Street', 'Ulsoor',\n       'Residency Road', 'Shivajinagar', 'Infantry Road',\n       'St. Marks Road', 'Cunningham Road', 'Race Course Road',\n       'Commercial Street', 'Vasanth Nagar', 'HBR Layout', 'Domlur',\n       'Ejipura', 'Jeevan Bhima Nagar', 'Old Madras Road',\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', 'Nagarbhavi', 'Sankey Road', 'Malleshwaram',\n       'Sadashiv Nagar', 'Basaveshwara Nagar', 'Yeshwantpur',\n       'West Bangalore', 'Magadi Road', 'Yelahanka', 'Sahakara Nagar',\n       'Peenya'], dtype=object)"},"metadata":{}}]},{"cell_type":"code","source":"df['city'].unique()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.076329Z","iopub.execute_input":"2024-01-26T13:53:22.077450Z","iopub.status.idle":"2024-01-26T13:53:22.089462Z","shell.execute_reply.started":"2024-01-26T13:53:22.077391Z","shell.execute_reply":"2024-01-26T13:53:22.088286Z"},"trusted":true},"execution_count":17,"outputs":[{"execution_count":17,"output_type":"execute_result","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)"},"metadata":{}}]},{"cell_type":"markdown","source":"Elements in location and city both are similar so let's keep one","metadata":{}},{"cell_type":"code","source":"df.drop(['city'], axis=1, inplace=True)\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.090646Z","iopub.execute_input":"2024-01-26T13:53:22.090940Z","iopub.status.idle":"2024-01-26T13:53:22.116046Z","shell.execute_reply.started":"2024-01-26T13:53:22.090914Z","shell.execute_reply":"2024-01-26T13:53:22.114623Z"},"trusted":true},"execution_count":18,"outputs":[{"execution_count":18,"output_type":"execute_result","data":{"text/plain":"                    name online_order book_table  rate  votes  \\\n0                  Jalsa          Yes        Yes   4.1    775   \n1         Spice Elephant          Yes         No   4.1    787   \n2        San Churro Cafe          Yes         No   3.8    918   \n3  Addhuri Udupi Bhojana           No         No   3.7     88   \n4          Grand Village           No         No   3.8    166   \n\n                              phone      location            rest_type  \\\n0    080 42297555\\r\\n+91 9743772233  Banashankari        Casual Dining   \n1                      080 41714161  Banashankari        Casual Dining   \n2                    +91 9663487993  Banashankari  Cafe, Casual Dining   \n3                    +91 9620009302  Banashankari          Quick Bites   \n4  +91 8026612447\\r\\n+91 9901210005  Basavanagudi        Casual Dining   \n\n                         cuisines cost2plates    type  \n0  North Indian, Mughlai, Chinese         800  Buffet  \n1     Chinese, North Indian, Thai         800  Buffet  \n2          Cafe, Mexican, Italian         800  Buffet  \n3      South Indian, North Indian         300  Buffet  \n4        North Indian, Rajasthani         600  Buffet  ","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>phone</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>080 42297555\\r\\n+91 9743772233</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    </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>080 41714161</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    </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>+91 9663487993</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    </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>+91 9620009302</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    </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>+91 8026612447\\r\\n+91 9901210005</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    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df['cost2plates'].unique()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.118345Z","iopub.execute_input":"2024-01-26T13:53:22.119030Z","iopub.status.idle":"2024-01-26T13:53:22.129534Z","shell.execute_reply.started":"2024-01-26T13:53:22.118996Z","shell.execute_reply":"2024-01-26T13:53:22.128448Z"},"trusted":true},"execution_count":19,"outputs":[{"execution_count":19,"output_type":"execute_result","data":{"text/plain":"array(['800', '300', '600', '700', '550', '500', '450', '650', '400',\n       '900', '200', '750', '150', '850', '100', '1,200', '350', '250',\n       '950', '1,000', '1,500', '1,300', '199', '80', '1,100', '160',\n       '1,600', '230', '130', '50', '190', '1,700', '1,400', '180',\n       '1,350', '2,200', '2,000', '1,800', '1,900', '330', '2,500',\n       '2,100', '3,000', '2,800', '3,400', '40', '1,250', '3,500',\n       '4,000', '2,400', '2,600', '120', '1,450', '469', '70', '3,200',\n       '60', '560', '240', '360', '6,000', '1,050', '2,300', '4,100',\n       '5,000', '3,700', '1,650', '2,700', '4,500', '140'], dtype=object)"},"metadata":{}}]},{"cell_type":"markdown","source":"Removing , from cost2plates values","metadata":{}},{"cell_type":"code","source":"def handle_comma(value):\n    value = str(value)\n    if ',' in value:\n        value = value.replace(\",\", \"\")\n        return float(value)\n    else:\n        return float(value)\n    \ndf['cost2plates'] = df['cost2plates'].apply(handle_comma)\ndf['cost2plates'].unique()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.131292Z","iopub.execute_input":"2024-01-26T13:53:22.132018Z","iopub.status.idle":"2024-01-26T13:53:22.169470Z","shell.execute_reply.started":"2024-01-26T13:53:22.131975Z","shell.execute_reply":"2024-01-26T13:53:22.168500Z"},"trusted":true},"execution_count":20,"outputs":[{"execution_count":20,"output_type":"execute_result","data":{"text/plain":"array([ 800.,  300.,  600.,  700.,  550.,  500.,  450.,  650.,  400.,\n        900.,  200.,  750.,  150.,  850.,  100., 1200.,  350.,  250.,\n        950., 1000., 1500., 1300.,  199.,   80., 1100.,  160., 1600.,\n        230.,  130.,   50.,  190., 1700., 1400.,  180., 1350., 2200.,\n       2000., 1800., 1900.,  330., 2500., 2100., 3000., 2800., 3400.,\n         40., 1250., 3500., 4000., 2400., 2600.,  120., 1450.,  469.,\n         70., 3200.,   60.,  560.,  240.,  360., 6000., 1050., 2300.,\n       4100., 5000., 3700., 1650., 2700., 4500.,  140.])"},"metadata":{}}]},{"cell_type":"code","source":"df.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.170763Z","iopub.execute_input":"2024-01-26T13:53:22.171062Z","iopub.status.idle":"2024-01-26T13:53:22.189443Z","shell.execute_reply.started":"2024-01-26T13:53:22.171036Z","shell.execute_reply":"2024-01-26T13:53:22.188080Z"},"trusted":true},"execution_count":21,"outputs":[{"execution_count":21,"output_type":"execute_result","data":{"text/plain":"                    name online_order book_table  rate  votes  \\\n0                  Jalsa          Yes        Yes   4.1    775   \n1         Spice Elephant          Yes         No   4.1    787   \n2        San Churro Cafe          Yes         No   3.8    918   \n3  Addhuri Udupi Bhojana           No         No   3.7     88   \n4          Grand Village           No         No   3.8    166   \n\n                              phone      location            rest_type  \\\n0    080 42297555\\r\\n+91 9743772233  Banashankari        Casual Dining   \n1                      080 41714161  Banashankari        Casual Dining   \n2                    +91 9663487993  Banashankari  Cafe, Casual Dining   \n3                    +91 9620009302  Banashankari          Quick Bites   \n4  +91 8026612447\\r\\n+91 9901210005  Basavanagudi        Casual Dining   \n\n                         cuisines  cost2plates    type  \n0  North Indian, Mughlai, Chinese        800.0  Buffet  \n1     Chinese, North Indian, Thai        800.0  Buffet  \n2          Cafe, Mexican, Italian        800.0  Buffet  \n3      South Indian, North Indian        300.0  Buffet  \n4        North Indian, Rajasthani        600.0  Buffet  ","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>phone</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>080 42297555\\r\\n+91 9743772233</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>080 41714161</td>\n      <td>Banashankari</td>\n      <td>Casual Dining</td>\n      <td>Chinese, North Indian, Thai</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>+91 9663487993</td>\n      <td>Banashankari</td>\n      <td>Cafe, Casual Dining</td>\n      <td>Cafe, Mexican, Italian</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>+91 9620009302</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>+91 8026612447\\r\\n+91 9901210005</td>\n      <td>Basavanagudi</td>\n      <td>Casual Dining</td>\n      <td>North Indian, Rajasthani</td>\n      <td>600.0</td>\n      <td>Buffet</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"### Cleaning rest_type column","metadata":{}},{"cell_type":"code","source":"df['rest_type'].value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.191498Z","iopub.execute_input":"2024-01-26T13:53:22.191881Z","iopub.status.idle":"2024-01-26T13:53:22.210715Z","shell.execute_reply.started":"2024-01-26T13:53:22.191839Z","shell.execute_reply":"2024-01-26T13:53:22.209489Z"},"trusted":true},"execution_count":22,"outputs":[{"execution_count":22,"output_type":"execute_result","data":{"text/plain":"rest_type\nQuick Bites                   18600\nCasual Dining                 10216\nCafe                           3605\nDelivery                       2510\nDessert Parlor                 2200\n                              ...  \nFood Court, Beverage Shop         2\nDessert Parlor, Food Court        2\nQuick Bites, Kiosk                1\nSweet Shop, Dessert Parlor        1\nBakery, Food Court                1\nName: count, Length: 91, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"rest_types = df.rest_type.value_counts()\nrest_types","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.212014Z","iopub.execute_input":"2024-01-26T13:53:22.212340Z","iopub.status.idle":"2024-01-26T13:53:22.230024Z","shell.execute_reply.started":"2024-01-26T13:53:22.212309Z","shell.execute_reply":"2024-01-26T13:53:22.229241Z"},"trusted":true},"execution_count":23,"outputs":[{"execution_count":23,"output_type":"execute_result","data":{"text/plain":"rest_type\nQuick Bites                   18600\nCasual Dining                 10216\nCafe                           3605\nDelivery                       2510\nDessert Parlor                 2200\n                              ...  \nFood Court, Beverage Shop         2\nDessert Parlor, Food Court        2\nQuick Bites, Kiosk                1\nSweet Shop, Dessert Parlor        1\nBakery, Food Court                1\nName: count, Length: 91, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"rest_types_lessthan_1000 = rest_types[rest_types < 1000]\nrest_types_lessthan_1000","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.231454Z","iopub.execute_input":"2024-01-26T13:53:22.231996Z","iopub.status.idle":"2024-01-26T13:53:22.245308Z","shell.execute_reply.started":"2024-01-26T13:53:22.231957Z","shell.execute_reply":"2024-01-26T13:53:22.244268Z"},"trusted":true},"execution_count":24,"outputs":[{"execution_count":24,"output_type":"execute_result","data":{"text/plain":"rest_type\nBeverage Shop                 844\nBar                           676\nFood Court                    576\nSweet Shop                    465\nBar, Casual Dining            403\n                             ... \nFood Court, Beverage Shop       2\nDessert Parlor, Food Court      2\nQuick Bites, Kiosk              1\nSweet Shop, Dessert Parlor      1\nBakery, Food Court              1\nName: count, Length: 83, dtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"Making the rest_type less than 1000 in frequency as `others`","metadata":{}},{"cell_type":"code","source":"def handle_rest_type(value):\n    if value in rest_types_lessthan_1000:\n        return 'others'\n    else:\n        return value\ndf['rest_type'] = df.rest_type.apply(handle_rest_type)\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.246775Z","iopub.execute_input":"2024-01-26T13:53:22.247187Z","iopub.status.idle":"2024-01-26T13:53:22.364711Z","shell.execute_reply.started":"2024-01-26T13:53:22.247148Z","shell.execute_reply":"2024-01-26T13:53:22.363629Z"},"trusted":true},"execution_count":25,"outputs":[{"execution_count":25,"output_type":"execute_result","data":{"text/plain":"                    name online_order book_table  rate  votes  \\\n0                  Jalsa          Yes        Yes   4.1    775   \n1         Spice Elephant          Yes         No   4.1    787   \n2        San Churro Cafe          Yes         No   3.8    918   \n3  Addhuri Udupi Bhojana           No         No   3.7     88   \n4          Grand Village           No         No   3.8    166   \n\n                              phone      location      rest_type  \\\n0    080 42297555\\r\\n+91 9743772233  Banashankari  Casual Dining   \n1                      080 41714161  Banashankari  Casual Dining   \n2                    +91 9663487993  Banashankari         others   \n3                    +91 9620009302  Banashankari    Quick Bites   \n4  +91 8026612447\\r\\n+91 9901210005  Basavanagudi  Casual Dining   \n\n                         cuisines  cost2plates    type  \n0  North Indian, Mughlai, Chinese        800.0  Buffet  \n1     Chinese, North Indian, Thai        800.0  Buffet  \n2          Cafe, Mexican, Italian        800.0  Buffet  \n3      South Indian, North Indian        300.0  Buffet  \n4        North Indian, Rajasthani        600.0  Buffet  ","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>phone</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>080 42297555\\r\\n+91 9743772233</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>080 41714161</td>\n      <td>Banashankari</td>\n      <td>Casual Dining</td>\n      <td>Chinese, North Indian, Thai</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>+91 9663487993</td>\n      <td>Banashankari</td>\n      <td>others</td>\n      <td>Cafe, Mexican, Italian</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>+91 9620009302</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>+91 8026612447\\r\\n+91 9901210005</td>\n      <td>Basavanagudi</td>\n      <td>Casual Dining</td>\n      <td>North Indian, Rajasthani</td>\n      <td>600.0</td>\n      <td>Buffet</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df.rest_type.value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.366517Z","iopub.execute_input":"2024-01-26T13:53:22.366941Z","iopub.status.idle":"2024-01-26T13:53:22.379605Z","shell.execute_reply.started":"2024-01-26T13:53:22.366900Z","shell.execute_reply":"2024-01-26T13:53:22.378731Z"},"trusted":true},"execution_count":26,"outputs":[{"execution_count":26,"output_type":"execute_result","data":{"text/plain":"rest_type\nQuick Bites           18600\nCasual Dining         10216\nothers                 8835\nCafe                   3605\nDelivery               2510\nDessert Parlor         2200\nTakeaway, Delivery     1975\nCasual Dining, Bar     1125\nBakery                 1120\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"### Cleaning the Location Column","metadata":{}},{"cell_type":"code","source":"location = df.location.value_counts()\nlocation","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.380903Z","iopub.execute_input":"2024-01-26T13:53:22.382137Z","iopub.status.idle":"2024-01-26T13:53:22.402063Z","shell.execute_reply.started":"2024-01-26T13:53:22.382091Z","shell.execute_reply":"2024-01-26T13:53:22.400639Z"},"trusted":true},"execution_count":27,"outputs":[{"execution_count":27,"output_type":"execute_result","data":{"text/plain":"location\nBTM                      4966\nHSR                      2477\nKoramangala 5th Block    2445\nJP Nagar                 2199\nWhitefield               2076\n                         ... \nWest Bangalore              6\nYelahanka                   5\nJakkur                      3\nRajarajeshwari Nagar        2\nPeenya                      1\nName: count, Length: 93, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"location_lessthan_300 = location[location < 300]\nlocation_lessthan_300","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.403750Z","iopub.execute_input":"2024-01-26T13:53:22.404219Z","iopub.status.idle":"2024-01-26T13:53:22.419248Z","shell.execute_reply.started":"2024-01-26T13:53:22.404177Z","shell.execute_reply":"2024-01-26T13:53:22.418119Z"},"trusted":true},"execution_count":28,"outputs":[{"execution_count":28,"output_type":"execute_result","data":{"text/plain":"location\nKoramangala 8th Block            294\nVasanth Nagar                    290\nJeevan Bhima Nagar               268\nWilson Garden                    244\nBommanahalli                     235\nKoramangala 3rd Block            215\nKumaraswamy Layout               191\nThippasandra                     189\nBasaveshwara Nagar               186\nNagawara                         184\nSeshadripuram                    165\nHennur                           158\nInfantry Road                    150\nHBR Layout                       147\nMajestic                         145\nRace Course Road                 135\nYeshwantpur                      119\nCity Market                      118\nITPL Main Road, Whitefield       113\nKoramangala 2nd Block            102\nKaggadasapura                    100\nVarthur Main Road, Whitefield     98\nHosur Road                        98\nSouth Bangalore                   94\nCV Raman Nagar                    88\nVijay Nagar                       78\nSanjay Nagar                      74\nRT Nagar                          74\nSadashiv Nagar                    60\nSahakara Nagar                    52\nKoramangala                       48\nEast Bangalore                    39\nJalahalli                         38\nMagadi Road                       34\nRammurthy Nagar                   32\nLangford Town                     27\nSankey Road                       27\nOld Madras Road                   22\nMysore Road                       20\nKanakapura Road                   19\nKR Puram                          18\nUttarahalli                       16\nHebbal                            14\nNorth Bangalore                   14\nKengeri                            8\nCentral Bangalore                  8\nNagarbhavi                         6\nWest Bangalore                     6\nYelahanka                          5\nJakkur                             3\nRajarajeshwari Nagar               2\nPeenya                             1\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"def handle_location(value):\n    if value in location_lessthan_300:\n        return \"others\"\n    else:\n        return value\n    \ndf['location'] = df.location.apply(handle_location)\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.420669Z","iopub.execute_input":"2024-01-26T13:53:22.421848Z","iopub.status.idle":"2024-01-26T13:53:22.544764Z","shell.execute_reply.started":"2024-01-26T13:53:22.421802Z","shell.execute_reply":"2024-01-26T13:53:22.543933Z"},"trusted":true},"execution_count":29,"outputs":[{"execution_count":29,"output_type":"execute_result","data":{"text/plain":"                    name online_order book_table  rate  votes  \\\n0                  Jalsa          Yes        Yes   4.1    775   \n1         Spice Elephant          Yes         No   4.1    787   \n2        San Churro Cafe          Yes         No   3.8    918   \n3  Addhuri Udupi Bhojana           No         No   3.7     88   \n4          Grand Village           No         No   3.8    166   \n\n                              phone      location      rest_type  \\\n0    080 42297555\\r\\n+91 9743772233  Banashankari  Casual Dining   \n1                      080 41714161  Banashankari  Casual Dining   \n2                    +91 9663487993  Banashankari         others   \n3                    +91 9620009302  Banashankari    Quick Bites   \n4  +91 8026612447\\r\\n+91 9901210005  Basavanagudi  Casual Dining   \n\n                         cuisines  cost2plates    type  \n0  North Indian, Mughlai, Chinese        800.0  Buffet  \n1     Chinese, North Indian, Thai        800.0  Buffet  \n2          Cafe, Mexican, Italian        800.0  Buffet  \n3      South Indian, North Indian        300.0  Buffet  \n4        North Indian, Rajasthani        600.0  Buffet  ","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>phone</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>080 42297555\\r\\n+91 9743772233</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>080 41714161</td>\n      <td>Banashankari</td>\n      <td>Casual Dining</td>\n      <td>Chinese, North Indian, Thai</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>+91 9663487993</td>\n      <td>Banashankari</td>\n      <td>others</td>\n      <td>Cafe, Mexican, Italian</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>+91 9620009302</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>+91 8026612447\\r\\n+91 9901210005</td>\n      <td>Basavanagudi</td>\n      <td>Casual Dining</td>\n      <td>North Indian, Rajasthani</td>\n      <td>600.0</td>\n      <td>Buffet</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df.location.value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.545819Z","iopub.execute_input":"2024-01-26T13:53:22.546844Z","iopub.status.idle":"2024-01-26T13:53:22.558544Z","shell.execute_reply.started":"2024-01-26T13:53:22.546810Z","shell.execute_reply":"2024-01-26T13:53:22.557314Z"},"trusted":true},"execution_count":30,"outputs":[{"execution_count":30,"output_type":"execute_result","data":{"text/plain":"location\nBTM                      4966\nothers                   4871\nHSR                      2477\nKoramangala 5th Block    2445\nJP Nagar                 2199\nWhitefield               2076\nIndiranagar              1996\nJayanagar                1872\nMarathahalli             1783\nBannerghatta Road        1589\nKoramangala 1st Block    1235\nBellandur                1234\nElectronic City          1233\nBrigade Road             1188\nKoramangala 7th Block    1132\nKoramangala 6th Block    1114\nSarjapur Road            1042\nKoramangala 4th Block     994\nUlsoor                    989\nBanashankari              896\nMG Road                   875\nKalyan Nagar              834\nRichmond Road             746\nMalleshwaram              703\nResidency Road            672\nBasavanagudi              669\nFrazer Town               665\nBrookefield               652\nNew BEL Road              641\nKammanahalli              634\nBanaswadi                 622\nRajajinagar               584\nChurch Street             550\nLavelle Road              519\nShanti Nagar              499\nDomlur                    482\nCunningham Road           474\nShivajinagar              457\nEjipura                   433\nOld Airport Road          432\nCommercial Street         369\nSt. Marks Road            343\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"### Cleaning Cuisines Column","metadata":{}},{"cell_type":"code","source":"cuisine = df.cuisines.value_counts()\ncuisine","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.560002Z","iopub.execute_input":"2024-01-26T13:53:22.560835Z","iopub.status.idle":"2024-01-26T13:53:22.577933Z","shell.execute_reply.started":"2024-01-26T13:53:22.560804Z","shell.execute_reply":"2024-01-26T13:53:22.576907Z"},"trusted":true},"execution_count":31,"outputs":[{"execution_count":31,"output_type":"execute_result","data":{"text/plain":"cuisines\nNorth Indian                                   2769\nNorth Indian, Chinese                          2345\nSouth Indian                                   1739\nBakery, Desserts                                887\nBiryani                                         887\n                                               ... \nNorth Indian, Biryani, Asian                      1\nAndhra, North Indian, Chinese, South Indian       1\nSouth Indian, Mangalorean, Chinese                1\nNorth Indian, Chinese, South Indian, Juices       1\nNorth Indian, Chinese, Arabian, Momos             1\nName: count, Length: 2686, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"cuisines_lessthan_100 = cuisine[cuisine < 100]\ncuisines_lessthan_100","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.579109Z","iopub.execute_input":"2024-01-26T13:53:22.579617Z","iopub.status.idle":"2024-01-26T13:53:22.594282Z","shell.execute_reply.started":"2024-01-26T13:53:22.579578Z","shell.execute_reply":"2024-01-26T13:53:22.593022Z"},"trusted":true},"execution_count":32,"outputs":[{"execution_count":32,"output_type":"execute_result","data":{"text/plain":"cuisines\nNorth Indian, Continental, Chinese             97\nItalian, Pizza                                 93\nJuices                                         93\nFast Food, North Indian                        93\nTibetan, Momos                                 90\n                                               ..\nNorth Indian, Biryani, Asian                    1\nAndhra, North Indian, Chinese, South Indian     1\nSouth Indian, Mangalorean, Chinese              1\nNorth Indian, Chinese, South Indian, Juices     1\nNorth Indian, Chinese, Arabian, Momos           1\nName: count, Length: 2618, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"def handle_cuisines(value):\n    if value in cuisines_lessthan_100:\n        return \"others\"\n    else:\n        return value\ndf['cuisines'] = df['cuisines'].apply(handle_cuisines)\ndf.cuisines.value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.595732Z","iopub.execute_input":"2024-01-26T13:53:22.596049Z","iopub.status.idle":"2024-01-26T13:53:22.701018Z","shell.execute_reply.started":"2024-01-26T13:53:22.596022Z","shell.execute_reply":"2024-01-26T13:53:22.699572Z"},"trusted":true},"execution_count":33,"outputs":[{"execution_count":33,"output_type":"execute_result","data":{"text/plain":"cuisines\nothers                                 25910\nNorth Indian                            2769\nNorth Indian, Chinese                   2345\nSouth Indian                            1739\nBiryani                                  887\n                                       ...  \nCafe, Desserts                           104\nNorth Indian, Mughlai, Chinese           104\nSouth Indian, Chinese, North Indian      104\nSouth Indian, Fast Food                  102\nNorth Indian, Chinese, Seafood           102\nName: count, Length: 69, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"df.head()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.702474Z","iopub.execute_input":"2024-01-26T13:53:22.702815Z","iopub.status.idle":"2024-01-26T13:53:22.721615Z","shell.execute_reply.started":"2024-01-26T13:53:22.702785Z","shell.execute_reply":"2024-01-26T13:53:22.720433Z"},"trusted":true},"execution_count":34,"outputs":[{"execution_count":34,"output_type":"execute_result","data":{"text/plain":"                    name online_order book_table  rate  votes  \\\n0                  Jalsa          Yes        Yes   4.1    775   \n1         Spice Elephant          Yes         No   4.1    787   \n2        San Churro Cafe          Yes         No   3.8    918   \n3  Addhuri Udupi Bhojana           No         No   3.7     88   \n4          Grand Village           No         No   3.8    166   \n\n                              phone      location      rest_type  \\\n0    080 42297555\\r\\n+91 9743772233  Banashankari  Casual Dining   \n1                      080 41714161  Banashankari  Casual Dining   \n2                    +91 9663487993  Banashankari         others   \n3                    +91 9620009302  Banashankari    Quick Bites   \n4  +91 8026612447\\r\\n+91 9901210005  Basavanagudi  Casual Dining   \n\n                         cuisines  cost2plates    type  \n0  North Indian, Mughlai, Chinese        800.0  Buffet  \n1                          others        800.0  Buffet  \n2                          others        800.0  Buffet  \n3      South Indian, North Indian        300.0  Buffet  \n4                          others        600.0  Buffet  ","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>phone</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>080 42297555\\r\\n+91 9743772233</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>080 41714161</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>+91 9663487993</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>+91 9620009302</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>+91 8026612447\\r\\n+91 9901210005</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>"},"metadata":{}}]},{"cell_type":"code","source":"df.type.value_counts()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.724078Z","iopub.execute_input":"2024-01-26T13:53:22.724452Z","iopub.status.idle":"2024-01-26T13:53:22.740156Z","shell.execute_reply.started":"2024-01-26T13:53:22.724395Z","shell.execute_reply":"2024-01-26T13:53:22.738833Z"},"trusted":true},"execution_count":35,"outputs":[{"execution_count":35,"output_type":"execute_result","data":{"text/plain":"type\nDelivery              25208\nDine-out              17249\nDesserts               3457\nCafes                  1663\nDrinks & nightlife     1070\nBuffet                  868\nPubs and bars           671\nName: count, dtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"## Visualization","metadata":{"execution":{"iopub.status.busy":"2024-01-26T10:06:22.751624Z","iopub.execute_input":"2024-01-26T10:06:22.752104Z","iopub.status.idle":"2024-01-26T10:06:22.757876Z","shell.execute_reply.started":"2024-01-26T10:06:22.752067Z","shell.execute_reply":"2024-01-26T10:06:22.756485Z"}}},{"cell_type":"markdown","source":"### Count Plot of Various Locations","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize=(16, 10))\ndf['location'] = pd.Categorical(df['location'])\nsns.countplot(x='location', data=df)\nplt.xticks(rotation=90);","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:22.741802Z","iopub.execute_input":"2024-01-26T13:53:22.742154Z","iopub.status.idle":"2024-01-26T13:53:23.482828Z","shell.execute_reply.started":"2024-01-26T13:53:22.742081Z","shell.execute_reply":"2024-01-26T13:53:23.481521Z"},"trusted":true},"execution_count":36,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1600x1000 with 1 Axes>","image/png":"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Visualizing Online Orders","metadata":{}},{"cell_type":"code","source":"df.info()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:23.484661Z","iopub.execute_input":"2024-01-26T13:53:23.485119Z","iopub.status.idle":"2024-01-26T13:53:23.519005Z","shell.execute_reply.started":"2024-01-26T13:53:23.485075Z","shell.execute_reply":"2024-01-26T13:53:23.517801Z"},"trusted":true},"execution_count":37,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nIndex: 50186 entries, 0 to 51716\nData columns (total 11 columns):\n #   Column        Non-Null Count  Dtype   \n---  ------        --------------  -----   \n 0   name          50186 non-null  object  \n 1   online_order  50186 non-null  object  \n 2   book_table    50186 non-null  object  \n 3   rate          50186 non-null  float64 \n 4   votes         50186 non-null  int64   \n 5   phone         50186 non-null  object  \n 6   location      50186 non-null  category\n 7   rest_type     50186 non-null  object  \n 8   cuisines      50186 non-null  object  \n 9   cost2plates   50186 non-null  float64 \n 10  type          50186 non-null  object  \ndtypes: category(1), float64(2), int64(1), object(7)\nmemory usage: 4.3+ MB\n","output_type":"stream"}]},{"cell_type":"code","source":"plt.figure(figsize=(6, 6))\ndf['online_order'] = pd.Categorical(df['online_order'])\nsns.countplot(x='online_order', data=df, palette='flare');","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:23.522676Z","iopub.execute_input":"2024-01-26T13:53:23.523035Z","iopub.status.idle":"2024-01-26T13:53:23.733053Z","shell.execute_reply.started":"2024-01-26T13:53:23.523004Z","shell.execute_reply":"2024-01-26T13:53:23.731829Z"},"trusted":true},"execution_count":38,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 600x600 with 1 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"},"metadata":{}}]},{"cell_type":"markdown","source":"### Visualizing book table facilty","metadata":{}},{"cell_type":"code","source":"df.info()","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:23.734645Z","iopub.execute_input":"2024-01-26T13:53:23.735348Z","iopub.status.idle":"2024-01-26T13:53:23.767185Z","shell.execute_reply.started":"2024-01-26T13:53:23.735306Z","shell.execute_reply":"2024-01-26T13:53:23.765863Z"},"trusted":true},"execution_count":39,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nIndex: 50186 entries, 0 to 51716\nData columns (total 11 columns):\n #   Column        Non-Null Count  Dtype   \n---  ------        --------------  -----   \n 0   name          50186 non-null  object  \n 1   online_order  50186 non-null  category\n 2   book_table    50186 non-null  object  \n 3   rate          50186 non-null  float64 \n 4   votes         50186 non-null  int64   \n 5   phone         50186 non-null  object  \n 6   location      50186 non-null  category\n 7   rest_type     50186 non-null  object  \n 8   cuisines      50186 non-null  object  \n 9   cost2plates   50186 non-null  float64 \n 10  type          50186 non-null  object  \ndtypes: category(2), float64(2), int64(1), object(6)\nmemory usage: 3.9+ MB\n","output_type":"stream"}]},{"cell_type":"code","source":"plt.figure(figsize=(6, 6))\ndf['book_table'] = pd.Categorical(df['book_table'])\nsns.countplot(x='book_table', data=df, palette='pastel');","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:23.768502Z","iopub.execute_input":"2024-01-26T13:53:23.768829Z","iopub.status.idle":"2024-01-26T13:53:23.970617Z","shell.execute_reply.started":"2024-01-26T13:53:23.768801Z","shell.execute_reply":"2024-01-26T13:53:23.969495Z"},"trusted":true},"execution_count":40,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 600x600 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"### Visualizing Online order vs Rate","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize=(6, 6))\nsns.boxplot(x='online_order', y='rate', data=df, palette='husl');","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:23.977596Z","iopub.execute_input":"2024-01-26T13:53:23.977961Z","iopub.status.idle":"2024-01-26T13:53:24.189932Z","shell.execute_reply.started":"2024-01-26T13:53:23.977931Z","shell.execute_reply":"2024-01-26T13:53:24.188808Z"},"trusted":true},"execution_count":41,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 600x600 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"### Visualizing Book table vs Rate","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize=(6, 6))\nsns.boxplot(x='book_table', y='rate', data=df, palette='Set2');","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:24.193853Z","iopub.execute_input":"2024-01-26T13:53:24.194215Z","iopub.status.idle":"2024-01-26T13:53:24.389792Z","shell.execute_reply.started":"2024-01-26T13:53:24.194182Z","shell.execute_reply":"2024-01-26T13:53:24.388634Z"},"trusted":true},"execution_count":42,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 600x600 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"### Visualizing online order facility, location wise","metadata":{}},{"cell_type":"code","source":"df1 = df.groupby(['location', 'online_order'])['name'].count()\ndf1.to_csv('location_online.csv')\ndf1 = pd.read_csv('location_online.csv')\ndf1 = pd.pivot_table(df1, values=None, index=['location'], columns=['online_order'], fill_value=0, aggfunc=np.sum)\ndf1","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:24.391082Z","iopub.execute_input":"2024-01-26T13:53:24.391379Z","iopub.status.idle":"2024-01-26T13:53:24.433757Z","shell.execute_reply.started":"2024-01-26T13:53:24.391353Z","shell.execute_reply":"2024-01-26T13:53:24.432695Z"},"trusted":true},"execution_count":43,"outputs":[{"execution_count":43,"output_type":"execute_result","data":{"text/plain":"                       name      \nonline_order             No   Yes\nlocation                         \nBTM                    1721  3245\nBanashankari            391   505\nBanaswadi               288   334\nBannerghatta Road       669   920\nBasavanagudi            235   434\nBellandur               495   739\nBrigade Road            534   654\nBrookefield             239   413\nChurch Street           209   341\nCommercial Street       227   142\nCunningham Road         161   313\nDomlur                  247   235\nEjipura                 214   219\nElectronic City         665   568\nFrazer Town             254   411\nHSR                     572  1905\nIndiranagar             677  1319\nJP Nagar                896  1303\nJayanagar               523  1349\nKalyan Nagar            343   491\nKammanahalli            259   375\nKoramangala 1st Block   384   851\nKoramangala 4th Block   448   546\nKoramangala 5th Block   836  1609\nKoramangala 6th Block   433   681\nKoramangala 7th Block   358   774\nLavelle Road            314   205\nMG Road                 502   373\nMalleshwaram            301   402\nMarathahalli            690  1093\nNew BEL Road            255   386\nOld Airport Road        220   212\nRajajinagar             281   303\nResidency Road          424   248\nRichmond Road           510   236\nSarjapur Road           320   722\nShanti Nagar            279   220\nShivajinagar            319   138\nSt. Marks Road          176   167\nUlsoor                  379   610\nWhitefield              969  1107\nothers                 2011  2860","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>1721</td>\n      <td>3245</td>\n    </tr>\n    <tr>\n      <th>Banashankari</th>\n      <td>391</td>\n      <td>505</td>\n    </tr>\n    <tr>\n      <th>Banaswadi</th>\n      <td>288</td>\n      <td>334</td>\n    </tr>\n    <tr>\n      <th>Bannerghatta Road</th>\n      <td>669</td>\n      <td>920</td>\n    </tr>\n    <tr>\n      <th>Basavanagudi</th>\n      <td>235</td>\n      <td>434</td>\n    </tr>\n    <tr>\n      <th>Bellandur</th>\n      <td>495</td>\n      <td>739</td>\n    </tr>\n    <tr>\n      <th>Brigade Road</th>\n      <td>534</td>\n      <td>654</td>\n    </tr>\n    <tr>\n      <th>Brookefield</th>\n      <td>239</td>\n      <td>413</td>\n    </tr>\n    <tr>\n      <th>Church Street</th>\n      <td>209</td>\n      <td>341</td>\n    </tr>\n    <tr>\n      <th>Commercial Street</th>\n      <td>227</td>\n      <td>142</td>\n    </tr>\n    <tr>\n      <th>Cunningham Road</th>\n      <td>161</td>\n      <td>313</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>665</td>\n      <td>568</td>\n    </tr>\n    <tr>\n      <th>Frazer Town</th>\n      <td>254</td>\n      <td>411</td>\n    </tr>\n    <tr>\n      <th>HSR</th>\n      <td>572</td>\n      <td>1905</td>\n    </tr>\n    <tr>\n      <th>Indiranagar</th>\n      <td>677</td>\n      <td>1319</td>\n    </tr>\n    <tr>\n      <th>JP Nagar</th>\n      <td>896</td>\n      <td>1303</td>\n    </tr>\n    <tr>\n      <th>Jayanagar</th>\n      <td>523</td>\n      <td>1349</td>\n    </tr>\n    <tr>\n      <th>Kalyan Nagar</th>\n      <td>343</td>\n      <td>491</td>\n    </tr>\n    <tr>\n      <th>Kammanahalli</th>\n      <td>259</td>\n      <td>375</td>\n    </tr>\n    <tr>\n      <th>Koramangala 1st Block</th>\n      <td>384</td>\n      <td>851</td>\n    </tr>\n    <tr>\n      <th>Koramangala 4th Block</th>\n      <td>448</td>\n      <td>546</td>\n    </tr>\n    <tr>\n      <th>Koramangala 5th Block</th>\n      <td>836</td>\n      <td>1609</td>\n    </tr>\n    <tr>\n      <th>Koramangala 6th Block</th>\n      <td>433</td>\n      <td>681</td>\n    </tr>\n    <tr>\n      <th>Koramangala 7th Block</th>\n      <td>358</td>\n      <td>774</td>\n    </tr>\n    <tr>\n      <th>Lavelle Road</th>\n      <td>314</td>\n      <td>205</td>\n    </tr>\n    <tr>\n      <th>MG Road</th>\n      <td>502</td>\n      <td>373</td>\n    </tr>\n    <tr>\n      <th>Malleshwaram</th>\n      <td>301</td>\n      <td>402</td>\n    </tr>\n    <tr>\n      <th>Marathahalli</th>\n      <td>690</td>\n      <td>1093</td>\n    </tr>\n    <tr>\n      <th>New BEL Road</th>\n      <td>255</td>\n      <td>386</td>\n    </tr>\n    <tr>\n      <th>Old Airport Road</th>\n      <td>220</td>\n      <td>212</td>\n    </tr>\n    <tr>\n      <th>Rajajinagar</th>\n      <td>281</td>\n      <td>303</td>\n    </tr>\n    <tr>\n      <th>Residency Road</th>\n      <td>424</td>\n      <td>248</td>\n    </tr>\n    <tr>\n      <th>Richmond Road</th>\n      <td>510</td>\n      <td>236</td>\n    </tr>\n    <tr>\n      <th>Sarjapur Road</th>\n      <td>320</td>\n      <td>722</td>\n    </tr>\n    <tr>\n      <th>Shanti Nagar</th>\n      <td>279</td>\n      <td>220</td>\n    </tr>\n    <tr>\n      <th>Shivajinagar</th>\n      <td>319</td>\n      <td>138</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>379</td>\n      <td>610</td>\n    </tr>\n    <tr>\n      <th>Whitefield</th>\n      <td>969</td>\n      <td>1107</td>\n    </tr>\n    <tr>\n      <th>others</th>\n      <td>2011</td>\n      <td>2860</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df1.plot(kind = 'bar', figsize = 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"},"metadata":{}}]},{"cell_type":"markdown","source":"### Visualizing Booking Table facility, Location wise","metadata":{}},{"cell_type":"code","source":"df2 = df.groupby(['location','book_table'])['name'].count()\ndf2.to_csv('location_booktable.csv')\ndf2 = pd.read_csv('location_booktable.csv')\ndf2 = pd.pivot_table(df2, values=None, index=['location'], columns=['book_table'], fill_value=0, aggfunc=np.sum)\ndf2","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:53:25.219678Z","iopub.execute_input":"2024-01-26T13:53:25.220565Z","iopub.status.idle":"2024-01-26T13:53:25.256963Z","shell.execute_reply.started":"2024-01-26T13:53:25.220523Z","shell.execute_reply":"2024-01-26T13:53:25.256005Z"},"trusted":true},"execution_count":45,"outputs":[{"execution_count":45,"output_type":"execute_result","data":{"text/plain":"                       name     \nbook_table               No  Yes\nlocation                        \nBTM                    4799  167\nBanashankari            833   63\nBanaswadi               614    8\nBannerghatta Road      1490   99\nBasavanagudi            653   16\nBellandur              1136   98\nBrigade Road           1012  176\nBrookefield             578   74\nChurch Street           368  182\nCommercial Street       369    0\nCunningham Road         299  175\nDomlur                  427   55\nEjipura                 433    0\nElectronic City        1135   98\nFrazer Town             657    8\nHSR                    2260  217\nIndiranagar            1547  449\nJP Nagar               1884  315\nJayanagar              1593  279\nKalyan Nagar            685  149\nKammanahalli            585   49\nKoramangala 1st Block  1185   50\nKoramangala 4th Block   684  310\nKoramangala 5th Block  1753  692\nKoramangala 6th Block  1002  112\nKoramangala 7th Block   970  162\nLavelle Road            289  230\nMG Road                 534  341\nMalleshwaram            614   89\nMarathahalli           1620  163\nNew BEL Road            585   56\nOld Airport Road        373   59\nRajajinagar             543   41\nResidency Road          523  149\nRichmond Road           630  116\nSarjapur Road           888  154\nShanti Nagar            442   57\nShivajinagar            434   23\nSt. Marks Road          219  124\nUlsoor                  812  177\nWhitefield             1825  251\nothers                 4504  367","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>4799</td>\n      <td>167</td>\n    </tr>\n    <tr>\n      <th>Banashankari</th>\n      <td>833</td>\n      <td>63</td>\n    </tr>\n    <tr>\n      <th>Banaswadi</th>\n      <td>614</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>Bannerghatta Road</th>\n      <td>1490</td>\n      <td>99</td>\n    </tr>\n    <tr>\n      <th>Basavanagudi</th>\n      <td>653</td>\n      <td>16</td>\n    </tr>\n    <tr>\n      <th>Bellandur</th>\n      <td>1136</td>\n      <td>98</td>\n    </tr>\n    <tr>\n      <th>Brigade Road</th>\n      <td>1012</td>\n      <td>176</td>\n    </tr>\n    <tr>\n      <th>Brookefield</th>\n      <td>578</td>\n      <td>74</td>\n    </tr>\n    <tr>\n      <th>Church Street</th>\n      <td>368</td>\n      <td>182</td>\n    </tr>\n    <tr>\n      <th>Commercial Street</th>\n      <td>369</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Cunningham Road</th>\n      <td>299</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>1135</td>\n      <td>98</td>\n    </tr>\n    <tr>\n      <th>Frazer Town</th>\n      <td>657</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>HSR</th>\n      <td>2260</td>\n      <td>217</td>\n    </tr>\n    <tr>\n      <th>Indiranagar</th>\n      <td>1547</td>\n      <td>449</td>\n    </tr>\n    <tr>\n      <th>JP Nagar</th>\n      <td>1884</td>\n      <td>315</td>\n    </tr>\n    <tr>\n      <th>Jayanagar</th>\n      <td>1593</td>\n      <td>279</td>\n    </tr>\n    <tr>\n      <th>Kalyan Nagar</th>\n      <td>685</td>\n      <td>149</td>\n    </tr>\n    <tr>\n      <th>Kammanahalli</th>\n      <td>585</td>\n      <td>49</td>\n    </tr>\n    <tr>\n      <th>Koramangala 1st Block</th>\n      <td>1185</td>\n      <td>50</td>\n    </tr>\n    <tr>\n      <th>Koramangala 4th Block</th>\n      <td>684</td>\n      <td>310</td>\n    </tr>\n    <tr>\n      <th>Koramangala 5th Block</th>\n      <td>1753</td>\n      <td>692</td>\n    </tr>\n    <tr>\n      <th>Koramangala 6th Block</th>\n      <td>1002</td>\n      <td>112</td>\n    </tr>\n    <tr>\n      <th>Koramangala 7th Block</th>\n      <td>970</td>\n      <td>162</td>\n    </tr>\n    <tr>\n      <th>Lavelle Road</th>\n      <td>289</td>\n      <td>230</td>\n    </tr>\n    <tr>\n      <th>MG Road</th>\n      <td>534</td>\n      <td>341</td>\n    </tr>\n    <tr>\n      <th>Malleshwaram</th>\n      <td>614</td>\n      <td>89</td>\n    </tr>\n    <tr>\n      <th>Marathahalli</th>\n      <td>1620</td>\n      <td>163</td>\n    </tr>\n    <tr>\n      <th>New BEL Road</th>\n      <td>585</td>\n      <td>56</td>\n    </tr>\n    <tr>\n      <th>Old Airport Road</th>\n      <td>373</td>\n      <td>59</td>\n    </tr>\n    <tr>\n      <th>Rajajinagar</th>\n      <td>543</td>\n      <td>41</td>\n    </tr>\n    <tr>\n      <th>Residency Road</th>\n      <td>523</td>\n      <td>149</td>\n    </tr>\n    <tr>\n      <th>Richmond Road</th>\n      <td>630</td>\n      <td>116</td>\n    </tr>\n    <tr>\n      <th>Sarjapur Road</th>\n      <td>888</td>\n      <td>154</td>\n    </tr>\n    <tr>\n      <th>Shanti Nagar</th>\n      <td>442</td>\n      <td>57</td>\n    </tr>\n    <tr>\n      <th>Shivajinagar</th>\n      <td>434</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>812</td>\n      <td>177</td>\n    </tr>\n    <tr>\n      <th>Whitefield</th>\n      <td>1825</td>\n      <td>251</td>\n    </tr>\n    <tr>\n      <th>others</th>\n      <td>4504</td>\n      <td>367</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df2.plot(kind = 'bar', figsize = (15,8))","metadata":{"execution":{"iopub.status.busy":"2024-01-26T13:58:35.825447Z","iopub.execute_input":"2024-01-26T13:58:35.825915Z","iopub.status.idle":"2024-01-26T13:58:36.628754Z","shell.execute_reply.started":"2024-01-26T13:58:35.825878Z","shell.execute_reply":"2024-01-26T13:58:36.627520Z"},"trusted":true},"execution_count":46,"outputs":[{"execution_count":46,"output_type":"execute_result","data":{"text/plain":"<Axes: xlabel='location'>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x800 with 1 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"},"metadata":{}}]},{"cell_type":"markdown","source":"### Grouping Types of Restaurants Location Wise","metadata":{}},{"cell_type":"code","source":"df3 = df.groupby(['location','type'])['name'].count()\ndf3.to_csv('location_Type.csv')\ndf3 = pd.read_csv('location_Type.csv')\ndf3 = pd.pivot_table(df3, values=None, index=['location'], columns=['type'], fill_value=0, aggfunc=np.sum)\ndf3","metadata":{"execution":{"iopub.status.busy":"2024-01-26T14:08:17.830381Z","iopub.execute_input":"2024-01-26T14:08:17.830795Z","iopub.status.idle":"2024-01-26T14:08:17.876099Z","shell.execute_reply.started":"2024-01-26T14:08:17.830754Z","shell.execute_reply":"2024-01-26T14:08:17.874915Z"},"trusted":true},"execution_count":48,"outputs":[{"execution_count":48,"output_type":"execute_result","data":{"text/plain":"                        name                                   \\\ntype                  Buffet Cafes Delivery Desserts Dine-out   \nlocation                                                        \nBTM                       21    83     3003      190     1628   \nBanashankari               7    36      417       71      351   \nBanaswadi                  0    24      301       32      258   \nBannerghatta Road          9    45      824      132      568   \nBasavanagudi               7    11      337       66      243   \nBellandur                 28    35      603       69      466   \nBrigade Road              25    46      490      103      445   \nBrookefield                6    17      337       45      243   \nChurch Street             19    45      193       27      215   \nCommercial Street          0    12      121       77      159   \nCunningham Road           29    34      190       21      177   \nDomlur                    15    13      261       35      135   \nEjipura                    0     0      245       16      172   \nElectronic City           23    24      564       71      509   \nFrazer Town                1    11      437       53      159   \nHSR                       19    49     1686      119      574   \nIndiranagar               38    94     1078      135      520   \nJP Nagar                  45    76     1147      162      711   \nJayanagar                 27    75     1022      179      557   \nKalyan Nagar               9    45      364       86      312   \nKammanahalli               2    25      329       35      237   \nKoramangala 1st Block      3    26      715       70      398   \nKoramangala 4th Block     21    48      453       81      295   \nKoramangala 5th Block     65   146     1067      200      826   \nKoramangala 6th Block     18    43      510       70      404   \nKoramangala 7th Block     25    46      491      117      403   \nLavelle Road              29    27      129       50      191   \nMG Road                   51    72      262       64      341   \nMalleshwaram              11    29      261       83      287   \nMarathahalli              34    32      968      104      621   \nNew BEL Road               4    29      336       33      223   \nOld Airport Road          12     5      198       35      161   \nRajajinagar               10     4      254       55      248   \nResidency Road            20    31      188       63      289   \nRichmond Road             63    21      222       71      341   \nSarjapur Road             25    22      554       82      318   \nShanti Nagar               9    22      198       39      220   \nShivajinagar               6    17      125       37      257   \nSt. Marks Road             5    10      111       10      145   \nUlsoor                    16    56      446       71      353   \nWhitefield                28    47     1029      131      762   \nothers                    83   130     2742      267     1527   \n\n                                                        \ntype                  Drinks & nightlife Pubs and bars  \nlocation                                                \nBTM                                   22            19  \nBanashankari                          14             0  \nBanaswadi                              6             1  \nBannerghatta Road                      9             2  \nBasavanagudi                           5             0  \nBellandur                             17            16  \nBrigade Road                          57            22  \nBrookefield                            4             0  \nChurch Street                         31            20  \nCommercial Street                      0             0  \nCunningham Road                       16             7  \nDomlur                                12            11  \nEjipura                                0             0  \nElectronic City                       21            21  \nFrazer Town                            2             2  \nHSR                                   13            17  \nIndiranagar                           65            66  \nJP Nagar                              51             7  \nJayanagar                             12             0  \nKalyan Nagar                          18             0  \nKammanahalli                           6             0  \nKoramangala 1st Block                  7            16  \nKoramangala 4th Block                 62            34  \nKoramangala 5th Block                 84            57  \nKoramangala 6th Block                 48            21  \nKoramangala 7th Block                 25            25  \nLavelle Road                          59            34  \nMG Road                               51            34  \nMalleshwaram                          18            14  \nMarathahalli                          22             2  \nNew BEL Road                           8             8  \nOld Airport Road                      12             9  \nRajajinagar                            3            10  \nResidency Road                        55            26  \nRichmond Road                         16            12  \nSarjapur Road                         19            22  \nShanti Nagar                           9             2  \nShivajinagar                           7             8  \nSt. Marks Road                        40            22  \nUlsoor                                22            25  \nWhitefield                            47            32  \nothers                                75            47  ","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>3003</td>\n      <td>190</td>\n      <td>1628</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>417</td>\n      <td>71</td>\n      <td>351</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>301</td>\n      <td>32</td>\n      <td>258</td>\n      <td>6</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>Bannerghatta Road</th>\n      <td>9</td>\n      <td>45</td>\n      <td>824</td>\n      <td>132</td>\n      <td>568</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>337</td>\n      <td>66</td>\n      <td>243</td>\n      <td>5</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Bellandur</th>\n      <td>28</td>\n      <td>35</td>\n      <td>603</td>\n      <td>69</td>\n      <td>466</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>490</td>\n      <td>103</td>\n      <td>445</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>337</td>\n      <td>45</td>\n      <td>243</td>\n      <td>4</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Church Street</th>\n      <td>19</td>\n      <td>45</td>\n      <td>193</td>\n      <td>27</td>\n      <td>215</td>\n      <td>31</td>\n      <td>20</td>\n    </tr>\n    <tr>\n      <th>Commercial Street</th>\n      <td>0</td>\n      <td>12</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>190</td>\n      <td>21</td>\n      <td>177</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>564</td>\n      <td>71</td>\n      <td>509</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>437</td>\n      <td>53</td>\n      <td>159</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>1686</td>\n      <td>119</td>\n      <td>574</td>\n      <td>13</td>\n      <td>17</td>\n    </tr>\n    <tr>\n      <th>Indiranagar</th>\n      <td>38</td>\n      <td>94</td>\n      <td>1078</td>\n      <td>135</td>\n      <td>520</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>1147</td>\n      <td>162</td>\n      <td>711</td>\n      <td>51</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>Jayanagar</th>\n      <td>27</td>\n      <td>75</td>\n      <td>1022</td>\n      <td>179</td>\n      <td>557</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>364</td>\n      <td>86</td>\n      <td>312</td>\n      <td>18</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Kammanahalli</th>\n      <td>2</td>\n      <td>25</td>\n      <td>329</td>\n      <td>35</td>\n      <td>237</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>715</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>48</td>\n      <td>453</td>\n      <td>81</td>\n      <td>295</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>1067</td>\n      <td>200</td>\n      <td>826</td>\n      <td>84</td>\n      <td>57</td>\n    </tr>\n    <tr>\n      <th>Koramangala 6th Block</th>\n      <td>18</td>\n      <td>43</td>\n      <td>510</td>\n      <td>70</td>\n      <td>404</td>\n      <td>48</td>\n      <td>21</td>\n    </tr>\n    <tr>\n      <th>Koramangala 7th Block</th>\n      <td>25</td>\n      <td>46</td>\n      <td>491</td>\n      <td>117</td>\n      <td>403</td>\n      <td>25</td>\n      <td>25</td>\n    </tr>\n    <tr>\n      <th>Lavelle Road</th>\n      <td>29</td>\n      <td>27</td>\n      <td>129</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>72</td>\n      <td>262</td>\n      <td>64</td>\n      <td>341</td>\n      <td>51</td>\n      <td>34</td>\n    </tr>\n    <tr>\n      <th>Malleshwaram</th>\n      <td>11</td>\n      <td>29</td>\n      <td>261</td>\n      <td>83</td>\n      <td>287</td>\n      <td>18</td>\n      <td>14</td>\n    </tr>\n    <tr>\n      <th>Marathahalli</th>\n      <td>34</td>\n      <td>32</td>\n      <td>968</td>\n      <td>104</td>\n      <td>621</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>336</td>\n      <td>33</td>\n      <td>223</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>198</td>\n      <td>35</td>\n      <td>161</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>254</td>\n      <td>55</td>\n      <td>248</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>188</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>222</td>\n      <td>71</td>\n      <td>341</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>554</td>\n      <td>82</td>\n      <td>318</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>220</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>125</td>\n      <td>37</td>\n      <td>257</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>446</td>\n      <td>71</td>\n      <td>353</td>\n      <td>22</td>\n      <td>25</td>\n    </tr>\n    <tr>\n      <th>Whitefield</th>\n      <td>28</td>\n      <td>47</td>\n      <td>1029</td>\n      <td>131</td>\n      <td>762</td>\n      <td>47</td>\n      <td>32</td>\n    </tr>\n    <tr>\n      <th>others</th>\n      <td>83</td>\n      <td>130</td>\n      <td>2742</td>\n      <td>267</td>\n      <td>1527</td>\n      <td>75</td>\n      <td>47</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df3.plot(kind = 'bar', figsize = (36,8))","metadata":{"execution":{"iopub.status.busy":"2024-01-26T14:08:33.451074Z","iopub.execute_input":"2024-01-26T14:08:33.451503Z","iopub.status.idle":"2024-01-26T14:08:34.903030Z","shell.execute_reply.started":"2024-01-26T14:08:33.451462Z","shell.execute_reply":"2024-01-26T14:08:34.901945Z"},"trusted":true},"execution_count":49,"outputs":[{"execution_count":49,"output_type":"execute_result","data":{"text/plain":"<Axes: xlabel='location'>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 3600x800 with 1 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