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()
# Start coding here...
# Add as many cells as you like...MATH_THRESHOLD = 800 * .8
best_math_schools = (schools
.query('average_math >= @MATH_THRESHOLD')
[['school_name', 'average_math']]
.sort_values('average_math', ascending=False))
best_math_schoolstotal_SAT = sum(schools[f'average_{s}'] for s in ('math', 'reading', 'writing'))
top_10_schools = (schools
.assign(total_SAT=total_SAT)
[['school_name', 'total_SAT']]
.sort_values('total_SAT', ascending=False)
.head(10))
top_10_schoolslargest_std_dev = (schools
.assign(total_SAT=total_SAT)
.groupby('borough')
.total_SAT.agg(
num_schools='count',
average_SAT='mean',
std_SAT='std')
.applymap(lambda v: round(v, 2) if isinstance(v, float) else v)
.reset_index()
.sort_values('std_SAT', ascending=False)
.head(1))
largest_std_dev