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 = schools.loc[schools['average_math'] > 639, ['school_name', 'average_math']].sort_values('average_math', ascending=False)
print(best_math_schools)
all_schools = schools.loc[:, :]
all_schools['total_SAT'] = all_schools[['average_math', 'average_reading', 'average_writing']].sum(axis = 1)
top_10_schools = all_schools.loc[:, ['school_name', 'total_SAT']].sort_values('total_SAT', ascending = False).head(10)
print(top_10_schools)new_school = all_schools.groupby('borough').agg({'total_SAT': ['count', 'mean', 'std']})
new_school.columns = ['num_schools', 'average_SAT', 'std_SAT']
largest_std_dev = new_school.sort_values('std_SAT', ascending=False).head(1).round(2)
print(largest_std_dev)