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Analysis of fantasy game player purchasing data using Python and Pandas

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Pandas-challenge

By: Jack Cohen

Heroes of Pymoli

Background

Congratulations! After a lot of hard work in the data wrangling mines, you've landed a job as Lead Analyst for an independent gaming company. You've been assigned the task of analyzing the data for their most recent fantasy game Heroes of Pymoli.

Like many others in its genre, the game is free-to-play, but players are encouraged to purchase optional items that enhance their playing experience. As a first task, the company would like you to generate a report that breaks down the game's purchasing data into meaningful insights.

Outputs

The final report includes each of 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

Analysis

Observable trends based on the data:

  1. The vast majority of in-game extras purchasers are male (84% Male, 14% Female). The male purchase value totaled $1,967.64 while female purchase value totaled only $361.94. However, on average each female player spent $4.47 while the average male player spent $4.07.
  2. Age range with the majority of purchases is ages 20-24, which comprised of 44.79% of all purchases. The next closes age ranges are ages 15-19 with 19.58% of purchases and ages 25-29 with 13.37% of purchases.
  3. The item that was purchased the most, and also brought in the most revenue, was the 'Final Critic' (Item ID: 92), which was purchased 13 times and generated $59.99 in revenue, suggesting the majority of revenue comes from the variety of items and not one particular item.