Dataset Link - https://www.kaggle.com/datasets/aungpyaeap/supermarket-sales
This repository contains a data analysis project on the sales data of a supermarket. The data is provided in the form of a CSV file, and the analysis is performed using Python and various data analysis libraries such as Pandas, Matplotlib, and Seaborn.
The project aims to answer various business questions such as which products are the top-selling, which department generates the most revenue, what is the sales trend over time, etc. The project also includes data cleaning and preprocessing steps, exploratory data analysis, and visualizations to help understand the data better.
To run this project, you need to have Python 3.x installed on your system along with the following libraries:
- pandas
- matplotlib
- seaborn
You can install these libraries using pip, as follows:
pip install pandas matplotlib seaborn
Alternatively, you can use the requirements.txt file to install the dependencies by running the following command:
pip install -r requirements.txt
To run the project, you need to have the supermarket sales data file named "supermarket_sales.csv" in the same directory as the Jupyter notebook file named "Supermarket Sales Analysis.ipynb". You can then open the Jupyter notebook in a web browser and run the cells to execute the code and generate the visualizations.
This project is created by Aryadeep Chakraborty . The dataset used in this project is provided by AUNG PYAE on Kaggle.