gabbyolivares / pandas-challenge

4.Data Visualization-Pandas

pandas-challenge

Homework 4. Using Pandas **IMPORTANT NOTES The complete and pulished delivery file corresponds to the version HeroesOfPymoli_final.ipynb file Please be advised that the file code was uploaded but not runned, for avoiding weird characters within the delivery

The 2 draft.ipynb files correspond to tryout versions of the homework. Both of them contain mistakes! =), but wanted to share in case you were interested on seeing the complete coding process

The starter.ipynb was kept in blank in case I needed to start from scratch

Pandas Homework - Pandas, Pandas, Pandas

Background The data dive continues! Now, it's time to take what you've learned about Python Pandas and apply it to new situations. For this assignment, you'll need to complete one of two (not both) Data Challenges. Once again, which challenge you take on is your choice. Just be sure to give it your all -- as the skills you hone will become powerful tools in your data analytics tool belt.

INSTRUCTIONS Before You Begin

Create a new repository for this project called pandas-challenge. Do not add this homework to an existing repository.

Clone the new repository to your computer.

Inside your local git repository, create a directory for the Pandas Challenge you choose. Use folder names corresponding to the challenges: HeroesOfPymoli or PyCitySchools.

Add your Jupyter notebook to this folder. This will be the main script to run for analysis.

Push the above changes to GitHub or GitLab.

Option 1: Heroes of Pymoli

Congratulations! After a lot of hard work in the data munging 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. Your final report should include 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

As final considerations:

You must use the Pandas Library and the Jupyter Notebook. You must submit a link to your Jupyter Notebook with the viewable Data Frames. You must include a written description of three observable trends based on the data. See Example Solution for a reference on expected format.