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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...treshold = 800 * 0.8
tresholdbest_math_schools = schools[schools["average_math"] >= treshold][["school_name", "average_math"]].sort_values("average_math", ascending=False)schools['total_SAT'] = schools[['average_math', 'average_reading', 'average_writing']].sum(axis=1)
top_10_schools = schools.groupby("school_name", as_index=False)["total_SAT"].mean().sort_values("total_SAT", ascending=False).head(10)
top_10_schoolsby_brough = schools.groupby('borough')["total_SAT"].agg([("num_schools", 'count'), ("average_SAT", 'mean'), ("std_SAT", 'std')]).round(2)
largest_std_dev = by_brough[by_brough['std_SAT'] == by_brough['std_SAT'].max()]
largest_std_dev