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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...
# max_score = schools["average_math"].max()
best_math_schools = schools[schools["average_math"] >= 640]best_math_schools = best_math_schools.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[["average_math", "average_reading", "average_writing",]].sum(axis=1)
schools.head()# top_10_schools = schools["total_SAT"].sort_values(ascending = False).head(10)
# top_10_schools = schools[['school_name', 'total_SAT']]
# top_10_schools.head()
top_10_schools = schools.groupby("school_name")["total_SAT"].mean().reset_index().sort_values("total_SAT", ascending=False).head(10)borough_stats = schools.groupby('borough')['total_SAT'].agg(['count', 'mean', 'std']).round(2)
largest_std_dev = borough_stats[borough_stats['std'] == borough_stats['std'].max()]
largest_std_dev.columns = ['num_schools', 'average_SAT', 'std_SAT']
largest_std_dev.head()