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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...
# Which NYC schools have the best math results?
schools["percent_math"] = (schools["average_math"] / 800 * 100).round(2)
print(schools)
best_math_schools = schools[schools["percent_math"] >= 80][["school_name","average_math"]].sort_values('average_math', ascending = False)
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("total_SAT", ascending = False).head(10)
top_10_schools
# Which single borough has the largest standard deviation in the combined SAT score?
borough_stats = (schools.groupby("borough")["total_SAT"].agg(num_schools = "count", average_SAT="mean", std_SAT="std").round(2))
# Get the borough with the largest standard deviation
largest_std_dev = borough_stats[borough_stats["std_SAT"] == borough_stats["std_SAT"].max()]
# Display the resulting single-row DataFrame
print(largest_std_dev)