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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(n=10)
best_math_schools = schools[schools['average_math']>= 640][['school_name','average_math']].sort_values('average_math', ascending=False)
#Total Sat
schools['total_SAT'] = schools['average_math'] + schools['average_reading']+ schools['average_writing']
#Top ten schools
top_10_schools = schools.groupby('school_name',as_index=False)['total_SAT'].mean().sort_values('total_SAT', ascending=False).head(n=10)
#Which NYC borough has the longest deviation
borough = schools.groupby('borough')['total_SAT'].agg(['count','mean','std']).round(2)
print(bourough)
#The max std
largest_std_dev = borough[borough["std"] == borough["std"].max()]
print(largest_std_dev)
#Rename the columns
largest_std_dev = largest_std_dev.rename(columns={'count':'num_schools',
'mean':'average_SAT',
'std':'std_SAT'})
print(largest_std_dev)