The aim of this project is to understand sales performance of a retail chain across different regions, product categories, and time periods. To accomplish this task, an exploratory data analysis on the company's sales data was performed to uncover insights that can drive business decisions. This involved importing the data, cleaning it, performing basic analyses and them creating visualisations to present the findings.
The dataset worked with is the Global Superstor Dataset, also available on Kaggle, and it contains information about sales, profits, product categories, customer segments, and geographical data.
Tools used are Python 3.13.12, Jupyter Notebook, Python Libraries: pandas, numpy, matplotlib, seaborn