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()
# Find schools above 640 in math
best_math_schools = schools[schools['average_math'] >= 640][['school_name', 'average_math']].sort_values(by='average_math', ascending=False)
#create total scores column
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']
print(schools.head())
# top ten schools
top_10_schools = schools[['school_name', 'total_SAT']].sort_values(by='total_SAT', ascending=False).head(10)
print(top_10_schools)
# Group by borough and calculate required statistics
borough_stats = schools.groupby('borough').agg(
num_schools=('total_SAT', 'count'),
average_SAT=('total_SAT', 'mean'),
std_SAT=('total_SAT', 'std')
).round(2)
borough_stats.head(5)
# Find the borough with the largest standard deviation in total_SAT
largest_std_dev = borough_stats.nlargest(1, 'std_SAT').reset_index()
print(large_std_dev)