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This project analyzes school district data. Demonstrates use of Python and Pandas library, reading csv and converting to dataframes, merging dataframes, aggregate functions, bins, and cleaning and organizing data.

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ajcascella/School-District-Analysis

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Background

In this project I analyzed district-wide standardized test results including 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.

Step by Step

The final report includes the following:

District Summary

  • District's key metrics, including:
    • Total Schools
    • Total Students
    • Total Budget
    • Average Math Score
    • Average Reading Score
    • % Passing Math
    • % Passing Reading
    • Overall Passing Rate (Average of the above two)

School Summary

  • Table that summarizes key metrics about each school, including:
    • School Name
    • School Type
    • Total Students
    • Total School Budget
    • Per Student Budget
    • Average Math Score
    • Average Reading Score
    • % Passing Math
    • % Passing Reading
    • Overall Passing Rate (Average of the above two)

Top Performing Schools (By Passing Rate)

  • Table that highlights the top 5 performing schools based on Overall Passing Rate. Includes:
    • School Name
    • School Type
    • Total Students
    • Total School Budget
    • Per Student Budget
    • Average Math Score
    • Average Reading Score
    • % Passing Math
    • % Passing Reading
    • Overall Passing Rate (Average of the above two)

Bottom Performing Schools (By Passing Rate)

  • Table that highlights the bottom 5 performing schools based on Overall Passing Rate. Includes all of the same metrics as above.

Math Scores by Grade

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

Reading Scores by Grade

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

Scores by School Spending

  • Table that breaks down school performances based on average Spending Ranges (Per Student). Include in the table each of the following:
    • Average Math Score
    • Average Reading Score
    • % Passing Math
    • % Passing Reading
    • Overall Passing Rate (Average of the above two)

Scores by School Size

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

Scores by School Type

  • Repeats the above breakdown, but this time group schools based on school type (Charter vs. District).

About

This project analyzes school district data. Demonstrates use of Python and Pandas library, reading csv and converting to dataframes, merging dataframes, aggregate functions, bins, and cleaning and organizing data.

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