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...
# Add as many cells as you like...
qua = 800*0.8
best_math_schools = schools[ schools['average_math'] > qua].sort_values(by = "average_math", ascending=False)
best_math_schools = best_math_schools[["school_name", "average_math"]]
best_math_schools
schools["total_SAT"] = schools["average_math"] + schools["average_reading"] + schools["average_writing"]
top_10_schools = schools.sort_values(by="total_SAT", ascending=False)
top_10_schools = top_10_schools[["school_name", "total_SAT"]].head(10)
top_10_schools
# Group by borough and calculate required statistics
borough_stats = schools.groupby("borough").agg(
num_schools=("school_name", "count"),
average_SAT=("total_SAT", "mean"),
std_SAT=("total_SAT", "std")
).reset_index()
borough_stats = borough_stats.round(2)
largest_std_dev = borough_stats.sort_values("std_SAT", ascending=False).head(1)
largest_std_dev