Welcome to the Zomato Data Exploration project! In this project, we will be exploring a dataset containing information on various restaurants and their ratings, location, and other attributes. This data has been collected from Zomato, a popular restaurant search and discovery platform.

To get started with this project, you will need to have the following packages installed:

• Pandas
• Numpy
• Matplotlib
• Seaborn You can install these packages by running the following command in your terminal/command prompt:

 pip install pandas numpy matplotlib seaborn

The dataset we will be using contains the following columns:

• Restaurant ID
• Restaurant Name
• Country Code
• City
• Address
• Locality
• Locality Verbose
• Longitude
• Latitude
• Cuisines
• Average Cost for two
• Currency
• Has Table booking
• Has Online delivery
• Is delivering now
• Switch to order menu
• Price range
• Aggregate rating
• Rating color
• Rating text
• Votes

We will begin by loading the data into a pandas dataframe and getting some basic information about the data. We will then proceed to perform some exploratory data analysis to get a better understanding of the data.

• Zomato has maximum records from India, followed by the USA and the United Kingdom.
• The majority of the ratings are between 2.5 and 3.4.
• Maximum number of 0 ratings are from Indian customers.
• Online delivery is available in India and the UAE.

In conclusion, this project provides a good starting point for further exploration and analysis of the Zomato dataset. By understanding the key patterns and relationships in the data, we can gain valuable insights into the restaurant industry and use this information to make better decisions.

I hope you found this project informative and enjoyable. If you have any questions or suggestions, feel free to reach out to me!