Superstore Analysis Using Python

In this project, I used Python libraries such as Pandas, Seaborn, and NumPy to manipulate and analyze sales data from a superstore dataset. Through data cleaning, transformation, and statistical analysis, I uncovered key insights into sales performance, customer behavior, and product trends. I also created visualizations using Seaborn to clearly present patterns and correlations, enabling stakeholders to make informed business decisions based on data-driven insights