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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
import numpy as np
import matplotlib.pyplot as plt
# Read in the data
schools = pd.read_csv("schools.csv")
# Preview the data
schools.head()
# Start coding here...
# Which school is best for math?
best_math_schools = schools[schools["average_math"]>=640][["school_name","average_math"]].sort_values("average_math", ascending=False)
print("Best math schools:")
print(best_math_schools.head(10))
# Fixing the error in the following block
best_math_schools_by_borough = schools[schools["average_math"]>=640].groupby("borough")[["school_name", "average_math"]].apply(lambda x: x.sort_values("average_math", ascending=False))
print("Best math schools by borough:")
print(best_math_schools_by_borough.head(10))
# top 10 performing schools
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 performing schools are:")
print(top_10_schools)
# Borough wise stats
borough_stats = schools.groupby("borough")["total_SAT"].agg(["count","mean", "std"]).round(2)
print("Borough wise stats:")
print(borough_stats)
borough_stats.plot(kind="bar", title="Borough wise stats",rot=45)
plt.show()
# which single borough has the largest standard deviation
largest_std_dev = borough_stats[borough_stats["std"] == borough_stats["std"].max()]
# Rename the columns
largest_std_dev = largest_std_dev.rename(columns={"count":"num_schools","mean":"average_SAT","std":"std_SAT"})
print("The borough with the largest standard deviation is:")
print(largest_std_dev)The NYC school analysis tells us that the borough with best scores are Queens and Staten Island and the largest variance is Manhattan.