Title: Athletic Sales Analysis

This project consisted of analyzing sales data and gaining insights to determine the greatest total sales and highest sales.

Description: Preparing Data with Pandas

Putting into practice what we have learned during week 5 of our AI and ML class, this project focuses on how to combine data using concatenation, joins, and merging, and how to reshape data using groupby, pivot, pivot_table, resample, and melt functions. Such actions were completed via the following sections of the project:

1. Combine and Clean the Data
2. Determine which Region Sold the Most Products
3. Determine which Region had the Most Sales
4. Determine which Retailer had the Most Sales
5. Determine which Retailer Sold the Most Women's Athletic Footwear
6. Determine the Day with the Most Women's Athletic Footwear Sales
7. Determine the Week with the Most Women's Athletic Footwear Sales

Challenges

I ran into issues with sections 6 and 7, which consisted of determining both the day and week with the most women's footwear sales. Despite working on these problems for hours, reviewing class notes and activities, and trying various ways to rework the code through indexing, melting, resampling and binning, I was unable to arrive at the correct solution prior to the assignment due date.