This repository contains code and analysis for the exploratory data analysis (EDA) of the Zomato dataset. The aim of this project is to gain insights into various aspects of the restaurant industry using data from Zomato, a popular online food delivery platform.
The dataset used in this project is sourced from Zomato's API and contains information about restaurants including their location, user ratings, cuisines, cost for two, and more. The dataset is provided in CSV format and can be found in the data directory.
Ensure you have the following dependencies installed:
- Python 3.x
- Jupyter Notebook
- pandas
- numpy
- matplotlib
- seaborn
You can install the dependencies using pip:
pip install pandas numpy matplotlib seaborn- Clone this repository:
git clone https://github.com/Ansarimajid/EDA
cd EDA-
Install the dependencies as mentioned above.
-
Open and run the Jupyter Notebook
EDA and Feature Engineering.ipynbto see the analysis and visualizations.
The analysis in EDA and Feature Engineering.ipynb covers the following aspects:
- Data cleaning and preprocessing
- Exploratory data analysis including:
- Distribution of restaurant ratings
- Most popular cuisines
- Relationship between cost and rating
- Geographical analysis of restaurants
- Correlation between variables
- Visualizations to illustrate key findings
Contributions are welcome! If you find any issues or have suggestions for improvement, feel free to open an issue or create a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.