pandas-challenge

Andrew Lounsbury

Module 4 Pandas challenge for the Vanderbilt Data Analytics Bootcamp

Code from Stack Overflow

The cell

# Use `pd.cut` to categorize spending based on the bins.
# https://stackoverflow.com/questions/75808415/why-am-i-getting-typeerror-not-supported-between-instances-of-int-and-st
# We're trying to compare the integer bins to the budgets, which have dollar signs in them, making them strings. To avoid this, we take just the numbers in the string with .str[1:], and convert just that portion to a float. Then the comparison works. 
school_spending_df["Spending Ranges (Per Student)"] = pd.cut(school_spending_df["Per Student Budget"].str[1:].astype(float), bins=spending_bins, labels=labels)
school_spending_df

contains some code taken from this page.

Charts

The Initial Data Set

District Summary

School Summary

Highest Performing Schools

Bottom Performing Schools

Math Scores by Grade

Reading Scores by Grade

Scores by School Spending

Scores by School Size

Scores by School Type

Report

• Overall, Charter schools greatly outperformed District schoools with Charter schools having an overall passing percentage of 90.43% and District schools having an overall passing percentage of 53.67%.
• The school with the lowest number of students, Holden High School, had a high percent passing math (92.51%), an even higher percent passing reading (96.25%), and a relativley high percent overall passing (89.23%) despite its low spending rate per student (<585).
• The school with the highest number of students had a low overall passing percentage (54.64%) despite having a higher spending range per student ($585-630) than Holden High School.