For this project, I created and manipulated Pandas DataFrames to analyze school and standardized test data to help the school board and mayor make strategic decisions regarding future school budgets and priorities.
The first task was to analyze district-wide standardized test results. With access to every student's math and reading scores, as well as various information on the schools they attend, I aggregated the data to showcase obvious trends in school performance.
District Summary
I created a high-level snapshot of the district's key metrics in a DataFrame which included the following metrics:
Total number of unique schools
Total students
Total budget
Average math score
Average reading score
% passing math (the percentage of students who passed math)
% passing reading (the percentage of students who passed reading)
% overall passing (the percentage of students who passed math AND reading)
School Summary
I created a DataFrame that summarizes key metrics about each school which included the following data:
School name
School type
Total students
Total school budget
Per student budget
Average math score
Average reading score
% passing math (the percentage of students who passed math)
% passing reading (the percentage of students who passed reading)
% overall passing (the percentage of students who passed math AND reading)
Highest-Performing Schools (by % Overall Passing)
Lowest-Performing Schools (by % Overall Passing)
Math Scores by Grade - DataFrame that lists the average math score for students of each grade level (9th, 10th, 11th, 12th) at each school.
Reading Scores by Grade - DataFrame that lists the average reading score for students of each grade level (9th, 10th, 11th, 12th) at each school.
Scores by School Spending - school performance based on average spending ranges (per student).
Scores by School Size - DataFrame called size_summary that breaks down school performance based on school size (small, medium, or large).
Scores by School Type - DataFrame that shows school performance based on the "School Type".