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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

# Start coding here...
# Add as many cells as you like...
best_math_schools = schools[['school_name', 'average_math']]
best_math_schools = best_math_schools[best_math_schools['average_math'] > 640].sort_values('average_math',ascending=False)
best_math_schools
schools['total_SAT'] = schools[['average_math','average_reading','average_writing']].sum(axis=1)
# schools
top_10_schools = schools[['school_name','total_SAT']].sort_values('total_SAT',ascending=False).head(10)
top_10_schools
# boroughs = schools.groupby('borough')['total_SAT'].agg(['count','mean','median'])
boroughs = schools.groupby('borough')['total_SAT'].agg(
    num_schools='count', 
    average_SAT='mean', 
    std_SAT='std'
)
boroughs = boroughs.round(2)
boroughs
largest_std_dev = boroughs[boroughs['std_SAT'] == boroughs['std_SAT'].max()]
largest_std_dev