Walmart Analysis

This Streamlit application analyzes and visualizes the Walmart sales dataset, providing insights into store performance, holiday impact, and potential areas for improvement. The app is built using Python and Streamlit.

Features

Overview of the Walmart dataset, its attributes, and objectives.

Data quality assessment, including checks for null values and duplicates.

Visualizations of data distributions, such as sales, unemployment, temperature, and more.

Store-specific analysis, including identifying top-performing stores and stores with the most varied sales.

Comparison of sales during holidays and non-holidays.

Recommendations and feedback for improving revenue.

Technologies Used

Python

Streamlit

Pandas

How to Run

To run this Streamlit app locally, follow these steps:

Clone this repository.

Install the required libraries using pip install -r requirements.txt.

Run the app using streamlit run app.py.

Dataset

The analysis is performed on the Walmart sales dataset covering the period from 2010 to 2012. The dataset contains information about multiple Walmart stores and various factors that can impact sales.