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()
cutoff = 0.8 * 800
best_math_schools = schools[schools["average_math"] >= cutoff][["school_name", "average_math"]].sort_values(by = "average_math", ascending = False)
schools["total_SAT"] = schools[["average_math", "average_reading", "average_writing"]].sum(axis=1)
top_10_schools = schools[["school_name", "total_SAT"]].sort_values(by = "total_SAT", ascending= False).head(10)
stats = schools.groupby("borough")["total_SAT"].agg(num_schools="count",
average_SAT="mean",
std_SAT="std")
largest_borough = stats["std_SAT"].idxmax()
row = stats.loc[largest_borough]
largest_std_dev= pd.DataFrame({"borough": [largest_borough],
"num_schools": [row["num_schools"]],
"average_SAT": [row["average_SAT"]],
"std_SAT": [row["std_SAT"]]})
largest_std_dev = largest_std_dev.round(2)