This project was to create pandas functions in order to drill for specific criteria in order to make the necessary As a first task, the company would like you to generate a report that breaks down the game's purchasing data into meaningful insights.
The report includes the following:
Player Count
- Total Number of Players Purchasing Analysis (Total)
- Number of Unique Items
- Average Purchase Price
- Total Number of Purchases
- Total Revenue Gender Demographics
- Percentage and Count of Male Players
- Percentage and Count of Female Players
- Percentage and Count of Other / Non-Disclosed Purchasing Analysis (Gender) The below each broken by gender
- Purchase Count
- Average Purchase Price
- Total Purchase Value
- Average Purchase Total per Person by Gender Age Demographics The below each broken into bins of 4 years (i.e. <10, 10-14, 15-19, etc.)
- Purchase Count
- Average Purchase Price
- Total Purchase Value
- Average Purchase Total per Person by Age Group
- Top Spenders Identify the the top 5 spenders in the game by total purchase value, then list (in a table):
- SN
- Purchase Count
- Average Purchase Price
- Total Purchase Value Most Popular Items Identify the 5 most popular items by purchase count, then list (in a table):
- Item ID
- Item Name
- Purchase Count
- Item Price
- Total Purchase Value Most Profitable Items Identify the 5 most profitable items by total purchase value, then list (in a table):
- Item ID
- Item Name
- Purchase Count
- Item Price
- Total Purchase Value