Clothes Cleaning

This dataset was cleaned and transformed in Power Query to make it structured and analysis-ready. The process included replacing values, changing data types, inserting new columns (such as Year), reordering and renaming columns for clarity, and merging queries to consolidate information. Additional transformations were applied, including creating conditional columns, adding custom calculations, and handling duplicates by removing them. Columns such as Day of Purchase, Time of Purchase, Age, Gender, City, Product, Category, Quantity, Unit Price, and Total Sales were standardized to ensure consistency. These steps improved data quality, corrected errors, and prepared the dataset for accurate reporting and visualization in Power BI.