Exploratory-data-analysis-Zomato-data

This is an exploratory data analysis project on the Bangalore Zomato dataset. The goal of this project is to analyze the data and gain insights into the restaurant industry in Bangalore.

Prerequisites

• pandas
• numpy
• matplotlib
• seaborn

Data

You can download the dataset here: https://www.kaggle.com/himanshupoddar/zomato-bangalore-restaurants/download

Phase 1: Data Cleaning and Preprocessing

In this phase, the data is cleaned and preprocessed to remove any missing or invalid values. This involves:

• Removing duplicates
• Handling missing values
• Standardizing the data types
• Removing unwanted columns
• Renaming columns

Phase 2: Exploratory Data Analysis

In this phase, the cleaned data is analyzed to gain insights into the restaurant industry in Bangalore. This involves:

• Visualizing the distribution of various features such as ratings, price range, and types of cuisine
• Analyzing the correlation between different features
• Identifying the top restaurants based on various criteria such as rating and cost
• The types of cuisine that are most popular in Bangalore
• The price range that is most preferred by customers
• The areas in Bangalore with the highest concentration of restaurants