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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...
schools["math result"] = (schools["average_math"] / 800) * 100
best_math_result = schools[schools["math result"] > 80]
sort_avg_math = best_math_result.sort_values("average_math", ascending=False)
best_math_schools = sort_avg_math[["school_name","average_math"]]
print("The best math schools are the following:")
print(best_math_schools.head())
schools["total_SAT"] = (schools["average_math"]+ schools["average_reading"] + schools["average_writing"])
sort_schools = schools.sort_values("total_SAT", ascending=False)
new_results = sort_schools.head(10).copy()
top_10_schools = new_results[["school_name","total_SAT"]]
print("The top 10 performing schools based on the combined SAT scores")
print(top_10_schools)
grouped_sat = schools.groupby("borough")["total_SAT"].agg(num_schools="count",average_SAT="mean",std_SAT="std")
grouped_sat = grouped_sat.reset_index()
largest_std_dev_row = grouped_sat.loc[grouped_sat['std_SAT'].idxmax()]
largest_std_dev = pd.DataFrame([largest_std_dev_row])
numeric_cols = ["num_schools","average_SAT","std_SAT"]
largest_std_dev[numeric_cols] = largest_std_dev[numeric_cols].round(2)
larges_std_dev = largest_std_dev[["borough","num_schools","average_SAT","std_SAT"]]
print(f"The borough that has the largest standard deviation in the combined SAT score is: \n {largest_std_dev}")