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...
#For NYC schools that are best in math results
best_math_schools=schools[schools["average_math"]>=(800/100)*80]
best_math_schools=best_math_schools[["school_name", "average_math"]]
best_math_schools.sort_values("average_math", ascending=False, inplace=True)
best_math_schools
# For 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.sort_values("total_SAT", ascending=False)[["school_name", "total_SAT"]].head(10)
#For largest standard deviation in the combined SAT score
data=schools.groupby("borough")["total_SAT"].agg(["std", "mean"]).round(2)
data["num_schools"]=schools.groupby("borough")["school_name"].count()
largest_std_dev=data[data["std"]==data["std"].max()]
largest_std_dev.columns=["std_SAT", "average_SAT", "num_schools"]
largest_std_dev