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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[schools["average_math"] >= 800*0.8][["school_name","average_math"]]
best_math_schools = best_math_schools.sort_values("average_math", ascending=False)
best_math_schools.head()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)[:10]largest_std_dev = pd.DataFrame()
largest_std_dev["std_SAT"] = pd.DataFrame(schools.groupby("borough")["total_SAT"].std())largest_std_dev["num_schools"] = schools.groupby("borough")["school_name"].count()
largest_std_dev["average_SAT"] = schools.groupby("borough")["total_SAT"].mean()largest_std_dev = largest_std_dev.sort_values("std_SAT", ascending=False)[:1]largest_std_dev = round(largest_std_dev.sort_values("std_SAT", ascending=False)[:1],2)
largest_std_dev