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
print(schools["average_math"].head())
print(schools.columns)
print(schools.info())
print(schools.shape)
# To get School with best maths results
best_math_schools = schools[schools["average_math"] >= 640][["school_name", "average_math"]]
best_math_schools = best_math_schools.sort_values("average_math", ascending=False)
print(best_math_schools)
#Top 10 schools based on SAT
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)
print(top_10_schools)
# Single Borough with largest Std Dev
# Option 1
boroughs = schools.groupby("borough")["total_SAT"].agg(["count", "mean", "std"]).round(2)
print(boroughs)
largest_std_dev = boroughs[boroughs["std"] == boroughs["std"].max()]
print(largest_std_dev)
largest_std_dev = largest_std_dev.rename(columns = {"count" : "num_schools", "mean" : "average_SAT", "std" : "std_SAT"})
print(largest_std_dev)