This project focuses on performing Exploratory Data Analysis (EDA) on the Zomato dataset to gain insights into the data related to restaurants, ratings, and customer reviews. The dataset includes information about various aspects of Zomato in different countries.
The dataset used in this project is obtained from Zomato and includes features such as restaurant details, ratings, country information, and more.
- Python
- Pandas
- NumPy
- Seaborn
- Matplotlib
Performed basic EDA to understand the structure and characteristics of the dataset. Explored numerical and categorical variables, checked for missing values, and visualized data distributions.
- Handled missing values using appropriate techniques.
- Merged the dataset with country information to include country names.
- Investigated and visualized null values.
- Explored the distribution of ratings using bar plots.
- Visualized the percentage distribution of transactions across the top three countries using a pie chart.
- Analyzed the distribution of aggregate ratings using a bar plot.
- Investigated countries with zero ratings and visualized the data.
- Explored which countries offer online delivery using a pie chart.
- Created a pie chart to visualize the distribution of records across the top five cities.
- Most transactions on Zomato are from India, followed by the USA and the UK.
- Ratings are mostly between 2.8 and 3.9.
- India has the highest number of null ratings.
- Explored the currency used by each country.
- Identified countries with online delivery options.
- Python
- Pandas
- NumPy
- Seaborn
- Matplotlib
- Clone the repository.
- Ensure you have the required dependencies installed.
- Run the Jupyter Notebook to execute the EDA on the Zomato dataset.
pip install -r requirements.txt