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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...best_math=schools[schools['average_math']>=80/100*800]
best_math_schools=best_math[['school_name','average_math']]
best_math_schools=best_math_schools.sort_values('average_math', ascending=False)
print(best_math_schools)schools['total_SAT']=schools[['average_math','average_writing','average_reading']].sum(axis=1)
top_10_schools=schools[['school_name','total_SAT']]
top_10_schools=top_10_schools.sort_values('total_SAT', ascending=False).head(10)
print(top_10_schools)borough_stats = schools.groupby("borough").agg(num_schools=("school_name", "size"), average_SAT=("total_SAT", "mean"),std_SAT=("total_SAT", "std")).reset_index()
borough_stats=borough_stats.round(2)
largest_std_dev=borough_stats.loc[borough_stats['std_SAT'].idxmax()]
largest_std_dev = pd.DataFrame(largest_std_dev).transpose()
print(borough_stats)
print(largest_std_dev)