Office Chair Online Sales Data

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I utilized Jupyter Notebook along with Pandas, Matplotlib, Seaborn, and NumPy to effectively clean, explore, and visualize data. By processing CSV data into Pandas DataFrames, I addressed duplicates, missing values, and formatting issues. This enabled me to illustrate the impact of payment methods on sales volume and revenue and identify top-selling products in each category using Bar Charts. Additionally, I visualized total revenue by product category and analyzed sales data by region and product type with Bar Charts and Choropleth Maps. These visualizations highlighted key trends, informing tactical decisions and global market strategies.

Chair Online Sales Data.ipynb

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