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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...
math_threshold = 0.8 * 800
best_math_schools = schools[schools['average_math'] >= math_threshold][['school_name', 'average_math']]
best_math_schools = best_math_schools.sort_values('average_math', ascending=False)
print(best_math_schools)
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']
top_10_schools = schools[['school_name', 'total_SAT']].sort_values('total_SAT', ascending=False).head(10)
print(top_10_schools)
borough_stats = schools.groupby('borough')['total_SAT'].agg(['std', 'mean', 'count']).reset_index()
largest_std_dev = borough_stats.loc[borough_stats['std'].idxmax()]
largest_std_dev = pd.DataFrame({
'borough': [largest_std_dev['borough']],
'num_schools': [largest_std_dev['count']],
'average_SAT': [round(largest_std_dev['mean'], 2)],
'std_SAT': [round(largest_std_dev['std'], 2)]
})
print(largest_std_dev)
# Add as many cells as you like...