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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...

Which NYC schools have the best math results?

best_math_schools = schools[schools['average_math'] >= (800 *(80/100))][['school_name', 'average_math']].sort_values('average_math', ascending = False)

best_math_schools

What are the top 10 performing schools based on the combined SAT scores?

schools['total_SAT']= schools[['average_reading', 'average_math','average_writing']].sum(axis = 1)

schools_sorted = schools.sort_values('total_SAT', ascending = False)

top_10_schools = schools_sorted[['school_name', 'total_SAT']][:10]

top_10_schools

Which single borough has the largest standard deviation in the combined SAT score?

import numpy as np
boroughs = schools.groupby('borough')['total_SAT'].agg(['count', 'mean', 'std']).round(2)
boroughs
largest_std = boroughs['std'].idxmax()

largest_std_dev = boroughs.loc[[largest_std]]

largest_std_dev.rename(columns = {'count': 'num_schools', 'mean' : 'average_SAT', 'std' : 'std_SAT'}, inplace = True)

largest_std_dev