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 = pd.DataFrame({
'school_name': schools['school_name'],
'average_math': schools[schools['average_math'] > 800 * 0.8]['average_math']
}).sort_values('average_math', ascending = False).dropna()
print(best_math_schools)
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']
top_10_schools = pd.DataFrame({
'school_name': schools['school_name'],
'total_SAT': schools['total_SAT']
}).sort_values('total_SAT', ascending = False).head(10)
print(top_10_schools)
deviation = schools.groupby('borough')['total_SAT'].std().idxmax()
filtered = schools[schools['borough'] == deviation]
largest_std_dev = pd.DataFrame({
'borough': [deviation],
'num_schools': [filtered.shape[0]],
'average_SAT': [round(filtered['total_SAT'].mean(),2)],
'std_SAT': [round(filtered['total_SAT'].std(),2)]
})
print(largest_std_dev)