Pandas Projects

Our Mission:

To simplify data for busy professionals by taking on the time-consuming, stressful tasks — turning complexity into clarity and freeing up our clients to focus on what they do best.

Cafe Sales - Data Cleaning:

This project showcases one of the most essential parts of the data process: data cleaning.

The dataset initially contained a significant amount of missing data. There were no reliable patterns in the transaction IDs, store locations, or dates, which made imputation for those fields unreliable. However, the sales values (Quantity, Price Per Unit, and Total Spent) had a consistent relationship that allowed for accurate imputation.

At the end of the cleaning process, two cleaned datasets were produced:

• One dataset with no missing values (but reduced in size due to dropped rows),

• Another dataset with missing values only in the non-critical fields: Transaction ID, Location, and Transaction Date.

The original file and both cleaned datasets are available for download below. You can also download a PDF report summarizing the cleaning process.