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

#best_math_schools.head()
schools['total_SAT']=schools.iloc[:, -4:-1].sum(axis=1)
top_10_schools=schools[['school_name','total_SAT']].sort_values(by='total_SAT',ascending=False).head(10)
#top_10_schools
ll = schools.groupby('borough')['total_SAT'].std().sort_values(ascending=False).nlargest(1)
list(ll.index)

primary = schools[schools['borough'].isin(list(ll.index))]
#primary.groupby('borough')['school_name'].count()
largest_std_dev = primary.groupby('borough').agg(
    num_schools=('school_name', 'count'),
    average_SAT=('total_SAT', 'mean'),
    std_SAT=('total_SAT','std')
).round(2)
#largest_std_dev