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Photo by Jannis Lucas on Unsplash.

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.head(15)

The best math results are at least 80% of the maximum possible score of 800 for math.

best_math_schools = schools[(schools["average_math"] == 640) | (schools["average_math"] > 640)][["school_name", "average_math"]].sort_values(by="average_math", ascending=False)
print(best_math_schools.head())

What are the top 10 performing schools based on the combined SAT scores?

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).reset_index(drop=True)

Which single borough has the largest standard deviation in the combined SAT score?

import numpy as np

grouping_data= schools.groupby('borough').agg(
      num_schools=("total_SAT", "count"),
      average_SAT=("total_SAT", "mean"),
      std_SAT=('total_SAT', "std")
).round(2)
largest_std_dev= grouping_data.loc[[grouping_data["std_SAT"].idxmax()]].reset_index()
print(largest_std_dev)