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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...
# Add as many cells as you like...more_or_even_80 = schools['average_math'] >= 800*0.8best_math_schools_general= schools[more_or_even_80].sort_values(by='average_math', ascending=False)
best_math_schools = best_math_schools_general[['school_name','average_math']]
print(best_math_schools.head())top_10_schools_general = schools.copy()
top_10_schools_general['total_SAT'] = top_10_schools_general[['average_math', 'average_reading', 'average_writing']].sum(axis=1)
top_10_schools = top_10_schools_general[['school_name', 'total_SAT']].sort_values(by='total_SAT', ascending=False).head(10)
print(top_10_schools)largest_std_dev_general = schools.copy()
largest_std_dev_general['total_SAT'] = largest_std_dev_general[['average_math', 'average_reading', 'average_writing']].sum(axis=1)
largest_std_dev_general['num_schools'] = largest_std_dev_general.groupby('borough')['school_name'].transform('count')
# Calculate the mean and standard deviation of total_SAT for each borough
largest_std_dev_general['average_SAT'] = largest_std_dev_general.groupby('borough')['total_SAT'].transform('mean')
largest_std_dev_general['std_SAT'] = largest_std_dev_general.groupby('borough')['total_SAT'].transform('std')
# Round the calculated values to 2 decimal places
largest_std_dev_general['average_SAT'] = round(largest_std_dev_general['average_SAT'],ndigits=2)
largest_std_dev_general['std_SAT'] = round(largest_std_dev_general['std_SAT'],ndigits=2)largest_std_dev = largest_std_dev_general[['borough','num_schools','average_SAT','std_SAT']].sort_values(by='std_SAT',ascending=False).head(1)
print(largest_std_dev.head())