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...
filtered_schools = schools[schools["average_math"] >= .8*800]
sorted_schools = filtered_schools.sort_values("average_math", ascending = False)
best_math_schools = sorted_schools[["school_name", "average_math"]]
print(best_math_schools)
schools["total_SAT"] = schools["average_math"] + schools["average_reading"] + schools["average_writing"]
w_SAT = schools.groupby("school_name")["total_SAT"].mean().reset_index()
top_10_schools = w_SAT.sort_values("total_SAT", ascending = False).head(10).reset_index(drop=True)
print(top_10_schools)
final_table = schools.groupby('borough').agg(
num_schools=('school_name', 'count'),
average_SAT=('total_SAT', 'mean'),
std_SAT=('total_SAT', 'std')
).round(2).reset_index()
largest_std_dev = final_table.sort_values("std_SAT", ascending = False)
print(largest_std_dev.head(1))