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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()

1 - Which NYC schools have the best math results?

# Get the average_math values equal or higher than 800*0.8 and sort descending by average_math
best_math_scores = schools[schools["average_math"] >= 800*0.8].sort_values(by="average_math", ascending=False)

# store school_name and average in a DataFrame
best_math = best_math_scores[["school_name", "average_math"]]
best_math_schools = pd.DataFrame(best_math)

# print the best_math_schools DataFrame
print(best_math_schools)

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

# Calculate total SAT score for each school
schools["total_SAT"] = schools["average_math"] + schools["average_reading"] + schools["average_writing"]

# Select top 10 schools based on total SAT score
top_10_schools = schools[["school_name", "total_SAT"]].sort_values(by="total_SAT", ascending=False).head(10)

print(top_10_schools)

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


# Group data by borough and calculate statistics
grouped = schools.groupby("borough").agg(
    num_schools=("school_name", "count"),
    average_SAT=("total_SAT", "mean"),
    std_SAT=("total_SAT", "std")
).reset_index()

# Find the borough with the largest standard deviation
largest_std_dev = grouped[grouped["std_SAT"] == grouped["std_SAT"].max()]

# Round numeric values to two decimal places
largest_std_dev = largest_std_dev.round(2)

print(largest_std_dev)