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fantasy-game-with-pandas's Introduction

Data dive with Pandas

Heroes of Pymoli

Fantasy

This project analyzes the data for most recent fantasy game "Heroes of Pymoli".

Findings from Data Analysis

  • Of the 1163 active players, the vast majority are male (84%). There also exists, a smaller, but notable proportion of female players (14%).
  • Our peak age demographic falls between 20-24 (44.8%) with secondary groups falling between 15-19 (18.60%) and 25-29 (13.4%).

Jupyter Notebook contains 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

Libraries used:

  • Pandas
  • Numpy

fantasy-game-with-pandas's People

Contributors

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Watchers

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