pycity_schools_analysis

Overview

In this project, I analyzed school data and district-wide standardized test results to showcase obvious trends in school performance.

Data Included

District Summary

• DataFrame that summarizes district's key 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

• DataFrame that summarizes key metrics about each school:
  • School name
  • School type
  • Total students
  • Total school budget
  • Per student budget
  • Average math score
  • Average reading score
  • % passing math
  • % passing reading
  • % overall passing

Highest-Performing and Lowest-Performing Schools

• Lists of schools ranked by % overall passing

Math Scores by Grade

• Analysis of math scores by grade level

Reading Scores by Grade

• Analysis of reading scores by grade level

Scores by School Spending

• Analysis of scores based on school spending

Scores by School Size

• Analysis of scores based on school size

Scores by School Type

• Analysis of scores based on school type

Requirements

• Python
• Pandas
• Jupyter Notebook