This project analyzes purchase data for in-game items of a fictitious game.
The project was completed in Jupyter lab using the following languages and libraries:
- Python
- Pandas
The data used was provided by the University of Pennsylvania Data Analysis and Visualization bootcamp.
Sales data for in-game purchases for a fantasy video game was analyzed and displayed for different demographic breakdowns, including age and gender, and for the most purchased and most profitable items. A brief written analysis of three trends seen in the data is also provided in a separate file.
The analysis contained within the HeroesOfPymoli.ibynb file includes things like breakdowns of spending by age groups
and which items had the highest total purchase values.
