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.
import pandas as pd
schools = pd.read_csv("schools.csv")
print(schools)
#best math result schools
best_math = schools[schools["average_math"] >= 640]
best_math_schools = best_math[["school_name","average_math"]].sort_values("average_math",ascending =False)
print(best_math_schools)
#top 10 performing schools based on the combine SAT scores
schools["total_SAT"] = schools["average_math"] + schools["average_writing"] + schools["average_reading"]
top_10_schools = schools[["school_name","total_SAT"]].sort_values("total_SAT",ascending=False).head(10)
print(top_10_schools)
# school borough with the largest std in combine sat scores
school_borough = schools.groupby("borough")["total_SAT"].agg(["count","mean","std"]).round(2)
school_borough =school_borough.rename(columns ={"count":"num_schools","mean" :"average_SAT","std":"std_SAT"})
print(school_borough.sort_values("std_SAT", ascending = False))
largest_std_dev = school_borough[school_borough["std_SAT"] ==school_borough["std_SAT"].max()]
print(largest_std_dev)