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Project: Exploring NYC Public School Test Result Scores

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.

import pandas as pd

# Read in the data
schools = pd.read_csv("schools.csv")

# Adding a new column total_SAT to schools
schools["total_SAT"] = schools["average_math"] + schools["average_writing"] + schools["average_reading"]

print('/n', schools)

# Creating DataFrame best_math_schools
best_math_schools = schools[schools["average_math"] >= 640] # filters the data

best_math_schools = best_math_schools.sort_values("average_math", ascending=False)[["school_name", "average_math"]] # sorts the data by the average_math column in descending order

print('/n', best_math_schools)

# Creating DataFrame top_10_schools
top_10_schools = schools.sort_values(["average_math", "average_writing", "average_reading"], ascending=[False, False, False])

# Ordering the data by the total_SAT column in descending order
top_10_schools = top_10_schools[["school_name", "total_SAT"]].sort_values("total_SAT", ascending = False).head(10)

print('/n', top_10_schools)

# Locating the NYC borough with the largest standard deviation
borough_stats = schools.groupby("borough")["total_SAT"].agg(['count', 'mean', 'std']).round(2)
largest_std_dev_borough = borough_stats['std'].idxmax()
largest_std_dev = borough_stats.loc[largest_std_dev_borough].to_frame().T
largest_std_dev.index = [largest_std_dev_borough]  # Set the index to the borough name
largest_std_dev.columns = ['num_schools', 'average_SAT', 'std_SAT']

print("\n", largest_std_dev)