This project analyzes Walmart sales data to derive insights into total sales by city, revenue by branch, and sales and revenue trends over time. The analysis was conducted using Python in Jupyter Notebook, utilizing libraries such as Pandas, NumPy, and Matplotlib.
Walmart, as one of the largest retail chains globally, generates massive amounts of sales data across its branches. Understanding sales trends and performance metrics is crucial for strategic decision-making and optimizing business operations. This analysis aims to provide insights into Walmart sales data, focusing on key performance indicators (KPIs) such as total sales by city, revenue by branch, and sales and revenue trends over time.
Analyzed the distribution of sales across different cities to identify top-performing regions.
Examined the revenue generated by each Walmart branch to assess their individual performance.
Investigated the trends in sales and revenue over time, particularly focusing on monthly fluctuations.
Jupyter Notebook: Interactive development environment for data analysis and visualization. Python: Programming language used for data manipulation and analysis. Pandas: Python library for data manipulation and analysis. NumPy: Python library for numerical computing. Matplotlib: Python library for creating static, animated, and interactive visualizations.