Data Analysis and Visualization Project

This project contains exploratory data analysis (EDA) and visualization of various datasets. The goal is to extract meaningful insights and present them in a visually appealing manner.

Project Structure

The project consists of the following Jupyter notebooks:

1. exploratory-data-analysis-of-superstore-sales-data.ipynb

   • This notebook performs EDA on the Superstore Sales dataset. It includes data cleaning, transformation, and visualization to uncover trends and patterns in sales data.

2. online-shopping-dataset-analysis.ipynb

   • This notebook analyzes an online shopping dataset. It covers data preprocessing, exploratory analysis, and visualization to understand customer behavior and sales performance.

3. zomato-dataset-eda.ipynb

   • This notebook focuses on EDA of the Zomato dataset. It includes data cleaning, exploratory analysis, and visualization to gain insights into restaurant data.

Getting Started

To get started with this project, follow these steps:

1. Clone the repository to your local machine.
2. Install the required dependencies.
3. Open the Jupyter notebooks and run the cells to perform the analysis.

Dependencies

• Python 3.x
• Jupyter Notebook
• Pandas
• NumPy
• Matplotlib
• Seaborn

You can install the dependencies using the following command:

pip install pandas numpy matplotlib seaborn jupyter

Usage

1. Open a terminal and navigate to the project directory.
2. Start Jupyter Notebook by running the following command:

jupyter notebook

3. Open any of the notebooks listed above and run the cells to perform the analysis.

Contributing

Contributions are welcome! If you have any suggestions or improvements, feel free to create a pull request.

License

This project is licensed under the MIT License.