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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...maxMathScore = schools.average_math.max()
maxMathScoremaximumPossibleScore = maxMathScore*0.85
maximumPossibleScorebest_math_schools = schools[schools.average_math>=(0.85*maxMathScore)]
best_math_schools = best_math_schools.sort_values('average_math',ascending = False)
best_math_schools = best_math_schools[['school_name','average_math']]
best_math_schoolsschools['total_SAT'] = schools['average_math']+schools['average_reading']+schools['average_writing']
top_10_schools = schools[['school_name','total_SAT']].nlargest(10,'total_SAT')
top_10_schoolsschool_info = schools.groupby("borough")["total_SAT"].agg(['count','mean','std']).round(2)
school_infomaxStd = school_info['std'].max()largest_std_dev = school_info[school_info['std']==maxStd]
largest_std_devlargest_std_dev.rename(columns={"count":"num_schools","mean":"average_SAT","std":"std_SAT"},inplace=True)
largest_std_dev