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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.head()

# Initialize an empty data frame: best_math_schools
best_math_schools = pd.DataFrame()

# Define a threshold which is 80% of the maximum score of 800
threshold = 0.8 * 800

# Finding schools with the best math scores of at least 80% of average_math
best_math_schools = schools[schools['average_math'] > threshold]

# Sorting the reults from largest to smallest based on 'average_math'
best_math_schools = best_math_schools.sort_values(by='average_math', ascending=False)

best_math_schools = best_math_schools[['school_name', 'average_math']]

# Identifying the top 10 performing schools by "total_SAT" 
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']

# Sorting the values by "total_SAT" in descending order
schools = schools.sort_values(by='total_SAT', ascending=False)

# Subsetting and limiting the results to 10 rows: top_10_schools
top_10_schools = schools[['school_name', 'total_SAT']].head(10)

# Locating the NYC borough with the largest standard deviation in SAT performance
borough_stat = schools.groupby('borough').agg(
                                            num_schools=('school_name', 'count'),
                                            average_SAT=('total_SAT', 'mean'),
                                            std_SAT=('total_SAT', 'std')).round(2)

# Filtering for the largest standard deviation
largest_std_dev = borough_stat[borough_stat['std_SAT'] == borough_stat['std_SAT'].max()]