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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...math_threshold = 0.8 * 800 best_math_schools = schools[schools["average_math"] >= math_threshold][["school_name", "average_math"]]best_math_schools = best_math_schools.sort_values("average_math", ascending=False).reset_index(drop=True)
print(best_math_schools)schools["total_SAT"] = schools[["average_math","average_writing","average_reading"]].sum(axis=1)top_10_schools = schools.nlargest(10, "total_SAT")[["school_name", "total_SAT"]]print(top_10_schools)borough_stats = schools.groupby("borough")["total_SAT"].agg(["count", "mean", "std"]).reset_index()
borough_stats.columns = ["borough", "num_schools", "average_SAT", "std_SAT"]borough_stats = borough_stats.round(2)largest_std_dev = borough_stats.nlargest(1, "std_SAT")print(largest_std_dev)