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
import numpy as np
# Read in the data
schools = pd.read_csv("schools.csv")
# Preview the data
schools.head()
#NYC schools that have the best math results
max_score = 800
best_result = 0.8 * max_score
best_math_schools = schools[schools['average_math'] >= best_result][['school_name', 'average_math']]\
.sort_values(by='average_math', ascending = False)
print(best_math_schools)
#The top 10 performing schools based on the combined SAT scores
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']
top_10_schools = schools[['school_name', 'total_SAT']].sort_values(by= 'total_SAT', ascending = False).head(10)
print(top_10_schools)
#Borough with the largest standard deviation in the combined SAT score
grouped_schools = 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 = grouped_schools.sort_values(by='std_SAT', ascending = False).head(1)
print(largest_std_dev)