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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...# Which NYC schools have the best math results?
schools_sorted = schools.sort_values('average_math', ascending=False)
best_math_schools = schools_sorted[schools_sorted['average_math'] >= 800 * 0.8]
best_math_schools = best_math_schools[['school_name', 'average_math']]
best_math_schools# What are the top 10 performing schools based on the combined SAT scores?
top_10_schools = schools[['school_name','average_math', 'average_reading', 'average_writing']]
top_10_schools['total_SAT'] = top_10_schools['average_math']+top_10_schools['average_reading']+top_10_schools['average_writing']
top_10_schools = top_10_schools.sort_values('total_SAT', ascending = False).drop(columns=['average_math', 'average_reading', 'average_writing']).head(10)
top_10_schools# Which single borough has the largest standard deviation in the combined SAT score?
# Calculate the total SAT score for each school
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']
# Group by borough and calculate the standard deviation, mean, and count of the total SAT score
borough_stats = schools.groupby('borough')['total_SAT'].agg(['std', 'mean', 'count'])
# Find the borough with the largest standard deviation
largest_std_borough = borough_stats.loc[borough_stats['std'].idxmax()]
# Create the DataFrame with the required information and round numeric values to two decimal places
largest_std_dev = pd.DataFrame([[largest_std_borough.name, round(largest_std_borough['count'], 2), round(largest_std_borough['mean'], 2), round(largest_std_borough['std'], 2)]],
columns=['borough', 'num_schools', 'average_SAT', 'std_SAT'])
largest_std_dev