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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()

# Start coding here...
# Add as many cells as you like...
quick_math = schools[schools["average_math"] >= 800 * 0.8]
best_math_schools = quick_math.sort_values("average_math", ascending=False)[["school_name", "average_math"]]
print(best_math_schools)


schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']
#top_10_schools = schools.nlargest(10, 'total_SAT')
top_10_schools = schools.nlargest(10, 'total_SAT')[['school_name', 'total_SAT']]
print(top_10_schools)

#print(top_10_schools[['school_name', 'total_SAT']]) #add two square brackets to select two columns
borough_stats = schools.groupby('borough')['total_SAT'].agg(['size', 'mean', 'std']) #calculating multiple variables in the one column total_SAT, and grouped by borough
max_std_borough = borough_stats['std'].idxmax()
max_std_borough_data = borough_stats.loc[max_std_borough]
largest_std_dev = pd.DataFrame({
    'borough': [max_std_borough],
    'num_schools': [max_std_borough_data['size']],
    'average_SAT': [round(max_std_borough_data['mean'], 2)],
    'std_SAT': [round(max_std_borough_data['std'], 2)]
})
print(largest_std_dev)