The purpose is to use the different libraries of python i.e., numpy, pandas, matplotlib and seaborn. Therefore finding missing values and visualization with piecharts and bargraphs, thus giving observation out of it. The dataset I used is from Kaggle.
The dataset is being retrieved from kaggle (https://www.kaggle.com/datasets/shrutimehta/zomato-restaurants-data). THe dataset has 5 json files, one csv and one xls file.
The collected data has been stored in the Comma Separated Value file Zomato.csv. Each restaurant in the dataset is uniquely identified by its Restaurant Id. Every Restaurant contains the following variables:
- Restaurant Id: Unique id of every restaurant across various cities of the world.
- Restaurant Name: Name of the restaurant
- Country Code: Country in which restaurant is located
- City: City in which restaurant is located
- Address: Address of the restaurant
- Locality: Location in the city
- Locality Verbose: Detailed description of the locality
- Longitude: Longitude coordinate of the restaurant's location
- Latitude: Latitude coordinate of the restaurant's location
- Cuisines: Cuisines offered by the restaurant
- Average Cost for two: Cost for two people in different currencies 👫
- Currency: Currency of the country
- Has Table booking: yes/no
- Has Online delivery: yes/ no
- Is delivering: yes/ no
- Switch to order menu: yes/no
- Price range: range of price of food
- Aggregate Rating: Average rating out of 5
- Rating color: depending upon the average rating color
- Rating text: text on the basis of rating of rating
- Votes: Number of ratings casted by people
- Python
- Jupyter Notebooks
- numpy
- Pandas
- Matplotlib
- Seaborn
- Missing Values
- Explored about the Numerical Values
- Explored about Categorical Variables
- Finding relationship between features.