This repository contains Python code for analyzing Supermart data using Pandas, Matplotlib, and Seaborn for data visualization.
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.
The Supermart dataset includes the following features:
- Order ID
- Customer Name
- Category
- Sub Category
- City
- Order Date
- Region
- Sales
- Discount
- Profit
- State
Make sure you have the following installed:
- Python
- Pandas
- Matplotlib
- Seaborn
- Jupyter Notebook (optional)
You can install the required libraries using pip:
pip install pandas matplotlib seaborn
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.
supermart_data_analysis.py
: Python script for data analysisvisualizations.ipynb
: Jupyter Notebook for interactive visualizations
To get started, simply clone the repository and run the Python scripts or open the Jupyter Notebook to explore the data and visualizations.
Feel free to contribute to this project by submitting pull requests. Your contributions are highly appreciated.
This project is licensed under the MIT License - see the LICENSE file for details.
- 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!