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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...
best_math_schools = schools[schools["average_math"] >= 640]
best_math_schools = best_math_schools.sort_values("average_math", ascending=False)
best_math_schools = best_math_schools[["school_name", "average_math"]]
best_math_schools
schools["total_SAT"] = schools["average_math"]+schools["average_reading"]+schools["average_writing"]
schools=schools.sort_values("total_SAT",ascending=False)
top_10_schools=schools.head(10)
top_10_schools=top_10_schools[["school_name","total_SAT"]]
top_10_schools
std_dev = schools.groupby("borough").std()
largest_std_dev_borough = std_dev[std_dev["total_SAT"] == std_dev["total_SAT"].max()].index[0]
largest_std_dev = pd.DataFrame({"borough": [largest_std_dev_borough]})
largest_std_dev["num_schools"] = schools.groupby("borough").size().loc[largest_std_dev_borough]
largest_std_dev["average_SAT"] = schools.groupby("borough")["total_SAT"].mean().loc[largest_std_dev_borough].round(2)
largest_std_dev["std_SAT"] = std_dev.loc[largest_std_dev_borough, "total_SAT"].round(2)
largest_std_dev