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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
import numpy as np

# Read in the data
schools = pd.read_csv("schools.csv")

# Preview the data
schools.head()

# Number of observations per borough
schools['borough'].value_counts()
# Which NYC schools have the best math results?

best_math_schools = (
    schools
    [schools['average_math'] >= 0.8*800]
    [['school_name', 'average_math']]
    .sort_values('average_math', ascending= False)
)

best_math_schools

schools['math_80_perc'] = np.where(
    schools['average_math'] >= 0.8 * 800,
    'High',
    'Low'
    )

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

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

top_10_schools = (
    schools[['school_name','total_SAT']]
    .sort_values('total_SAT', ascending= False)
    .head(10)
)

top_10_schools
# Which single borough has the largest standard deviation in the combined SAT score

(
    schools
    .groupby(['borough'], as_index= True)
    .agg(total_SAT_stddev = ('total_SAT', 'std'))
    .sort_values('total_SAT_stddev', ascending= False)
    .head(1)
    .pipe(
        lambda x: round(x, 2)
    )
)
largest_std_dev = (   
    schools
    .groupby('borough')
    .agg(
        num_schools = ('school_name', 'nunique'),
        average_SAT = ('total_SAT', 'mean'),
        std_SAT = ('total_SAT', 'std')
    )
    .pipe(
        lambda x: round(x, 2)
    )
    .sort_values('std_SAT', ascending= False)
    .head(1)
)

largest_std_dev