Data Wrangling with Pandas in Jupyter Lab

Purchasing Dataset for Recently launched Mobile Game App

This dataset is from an independent gaming company. I analyzed the purchase data for their most recent fantasy game Heroes of Pymoli.

My final report breaks down the game's purchasing data into meaningful insights.

This includes each of the following:

1. Player Count

Total Number of Players

2. Purchasing Analysis (Total)

Number of Unique Items
Average Purchase Price
Total Number of Purchases
Total Revenue

3. Gender Demographics

Percentage and Count of Male Players
Percentage and Count of Female Players
Percentage and Count of Other / Non-Disclosed

4. Purchasing Analysis (Gender)

The below each broken by gender
- Purchase Count
- Average Purchase Price
- Total Purchase Value
- Average Purchase Total per Person by Gender

5. Age Demographics

The below are each grouped into bins by age (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

Identified the top 5 spenders in the game by total purchase value, then listed (in a table):
- SN
- Purchase Count
- Average Purchase Price
- Total Purchase Value

Most Profitable Items

Identifed the 5 most profitable items by total purchase value, then listed (in a table):
- Item ID
- Item Name
- Purchase Count
- Item Price
- Total Purchase Value

Analyzing data for a city's school district

This dataset consists of the district-wide standardized test results (every student's math and reading scores). It also contains various information on the schools they attend.

My final report aggregates the data and showcases obvious trends in school performance.

Each of the following are included:

District Summary

High level snapshot (in table form) of the district's key metrics, this includes:
- Total Schools
- Total Students
- Total Budget
- Average Math Score
- Average Reading Score
- % Passing Math (The percentage of students that passed math.)
- % Passing Reading (The percentage of students that passed reading.)
- % Overall Passing (The percentage of students that passed math and reading.)

School Summary

An overview table that summarizes key metrics about each school, this includes:
- School Name
- School Type
- Total Students
- Total School Budget
- Per Student Budget
- Average Math Score
- Average Reading Score
- % Passing Math (The percentage of students that passed math.)
- % Passing Reading (The percentage of students that passed reading.)
- % Overall Passing (The percentage of students that passed math and reading.)

Top Performing Schools (By % Overall Passing)

A table that highlights the top 5 performing schools based on % Overall Passing. This includes:
- School Name
- School Type
- Total Students
- Total School Budget
- Per Student Budget
- Average Math Score
- Average Reading Score
- % Passing Math (The percentage of students that passed math.)
- % Passing Reading (The percentage of students that passed reading.)
- % Overall Passing (The percentage of students that passed math and reading.)

Bottom Performing Schools (By % Overall Passing)

A table that highlights the bottom 5 performing schools based on % Overall Passing. Included are all of the same metrics as above.

Math Scores by Grade**

A table that lists the average Math Score for students of each grade level (9th, 10th, 11th, 12th) at each school.

Reading Scores by Grade

A table that lists the average Reading Score for students of each grade level (9th, 10th, 11th, 12th) at each school.

Scores by School Spending

A table that breaks down school performances based on average Spending Ranges (Per Student). Used 4 bins to group school spending. Included in the table is each of the following:
- Average Math Score
- Average Reading Score
- % Passing Math (The percentage of students that passed math.)
- % Passing Reading (The percentage of students that passed reading.)
- % Overall Passing (The percentage of students that passed math and reading.)

Scores by School Size

Repeated the above breakdown, but this time grouped schools based on a reasonable approximation of school size (Small, Medium, Large).

Scores by School Type

Repeated the above breakdown, but this time grouped schools based on the school type (Charter vs. District).

Dataset References

Mockaroo, LLC. (2021). Realistic Data Generator. https://www.mockaroo.com/

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