Supermart Data Analysis

This repository contains Python code for analyzing Supermart data using Pandas, Matplotlib, and Seaborn for data visualization.

Overview

This project aims to analyze the Supermart data to gain insights into various aspects such as sales trends, customer behavior, and product performance. We will utilize Python programming language along with the Pandas, Matplotlib, and Seaborn libraries to create visualizations that will facilitate a better understanding of the data.

Dataset Features

The Supermart dataset includes the following features:

• Order ID
• Customer Name
• Category
• Sub Category
• City
• Order Date
• Region
• Sales
• Discount
• Profit
• State

Prerequisites

Make sure you have the following installed:

• Python
• Pandas
• Matplotlib
• Seaborn
• Jupyter Notebook (optional)

Installation

You can install the required libraries using pip:

pip install pandas matplotlib seaborn

Usage

You can use the provided Python scripts to perform data analysis and generate visualizations. Additionally, Jupyter Notebook can be used for an interactive analysis experience.

Files

• supermart_data_analysis.py: Python script for data analysis
• visualizations.ipynb: Jupyter Notebook for interactive visualizations

Getting Started

To get started, simply clone the repository and run the Python scripts or open the Jupyter Notebook to explore the data and visualizations.

Contributing

Feel free to contribute to this project by submitting pull requests. Your contributions are highly appreciated.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• Pandas: https://pandas.pydata.org/
• Matplotlib: https://matplotlib.org/
• Seaborn: https://seaborn.pydata.org/

l hope that this repository will be helpful for anyone interested in analyzing Supermart data using Python and visualizing the results using Pandas, Matplotlib, and Seaborn. Happy analyzing!