Photo by Jannis Lucas on Unsplash.
Every year, American high school students take SATs, which are standardized tests intended to measure literacy, numeracy, and writing skills. There are three sections - reading, math, and writing, each with a maximum score of 800 points. These tests are extremely important for students and colleges, as they play a pivotal role in the admissions process.
Analyzing the performance of schools is important for a variety of stakeholders, including policy and education professionals, researchers, government, and even parents considering which school their children should attend.
You have been provided with a dataset called schools.csv, which is previewed below.
You have been tasked with answering three key questions about New York City (NYC) public school SAT performance.
# Re-run this cell
import pandas as pd
# Read in the data
schools = pd.read_csv("schools.csv")
# Preview the data
schools.head()
# Start coding here...
# Add as many cells as you like...best_math_schools = schools[schools['average_math']>= (800*0.8)][['school_name','average_math']]best_math_schools = best_math_schools.sort_values(by='average_math',ascending=False)
print(best_math_schools.head())columns_to_sum = ['average_math','average_reading','average_writing']
schools['total_SAT'] = schools[columns_to_sum].sum(axis=1)
top_10_schools = schools[['school_name','total_SAT']].nlargest(10,'total_SAT')
largest_std_dev = schools.groupby('borough')['total_SAT'].agg(['count','mean','std']).max().round(2)
largest_std_dev = pd.DataFrame(largest_std_dev).T
largest_std_dev.rename(columns={'count':'num_schools','mean':'average_SAT','std':'std_SAT'})
largest_std_dev.reset_index(inplace=True)largest_std_dev.head()
# Which NYC borough has the highest standard deviation for total_SAT?
boroughs = schools.groupby("borough")["total_SAT"].agg(["count", "mean", "std"]).round(2)
# Filter for max std and make borough a column
largest_std_dev = boroughs[boroughs["std"] == boroughs["std"].max()]
# Rename the columns for clarity
largest_std_dev = largest_std_dev.rename(columns={"count": "num_schools", "mean": "average_SAT", "std": "std_SAT"})
# Optional: Move borough from index to column
largest_std_dev.reset_index(inplace=True)