This project uses Python and in particular the Pandas Library to analyze csv data. The data is from a fictional video game company, regarding their sales and their customer demograpic.
Using the Pandas library, we are able to parse the data and uncover key customer insights.
1- Player Count
2- Total Number of Players
3- A look at all purchases on an aggregate level
4- Number of Unique Items
5- Average Purchase Price
6- Total Number of Purchases
7- Total Revenue
8 - Gender Demographics-----------------------------------------------------------------------------------------------------------------
A- Percentage and Count of Male Players B- Percentage and Count of Female Players C- Percentage and Count of Other / Non-Disclosed
9- Purchasing Analysis (Gender)----------------------------------------------------------------------------------------------------- The below each broken by gender
A- Purchase Count B- Average Purchase Price C- Total Purchase Value D- Average Purchase Total per Person by Gender
10 -Age Demographics---------------------------------------------------------------------------------------------------------------
The below each broken into bins of 4 years (i.e. <10, 10-14, 15-19, etc.)
A- Purchase Count B- Average Purchase Price C- Total Purchase Value D- Average Purchase Total per Person by Age Group
11- Top Spenders--------------------------------------------------------------------------------------------------------------------
Identify the the top 5 spenders in the game by total purchase value, then list (in a table):
A- SN B- Purchase Count C- Average Purchase Price D- Total Purchase Value
12- Most Popular Items-------------------------------------------------------------------------------------------------------------
Identify the 5 most popular items by purchase count, then list (in a table):
A- Item ID B- Item Name C- Purchase Count D- Item Price E- Total Purchase Value
13- Most Profitable Items------------------------------------------------------------------------------------------------------------
Identify the 5 most profitable items by total purchase value, then list (in a table):
A- Item ID B- Item Name C- Purchase Count D- Item Price E- Total Purchase Value