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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...schools.loc[schools["average_math"] >= 640, ["school_name", "average_math"]]best_math_schools = schools.loc[schools["average_math"] >= 640, ["school_name", "average_math"]].sort_values(by="average_math", ascending=False)
best_math_schools.head()schools["total_SAT"] = schools["average_math"] + schools["average_reading"] + schools["average_writing"]
top_10_schools = schools[["school_name", "total_SAT"]].sort_values(by="total_SAT", ascending=False).head(10)
top_10_schoolslargest_std_dev = schools.groupby("borough")["total_SAT"].agg(['count', 'mean', 'std']).round(2)
largest_std_dev.rename(columns={"count":"num_schools", "mean":"average_SAT", "std":"std_SAT"}, inplace=True)
largest_std_dev = largest_std_dev[largest_std_dev["std_SAT"] == largest_std_dev["std_SAT"].max()]
largest_std_dev