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...
after_threshold = schools[
schools['average_math'] > 800*0.8
]
#1
best_math_schools = after_threshold.sort_values(by='average_math', ascending=False)[['school_name', 'average_math']]
print(best_math_schools)
#2
schools['total_SAT']= (
schools['average_math'] +
schools['average_reading'] +
schools['average_writing']
)
sorted_schools = schools.sort_values('total_SAT', ascending=False)
top_10_schools = sorted_schools[['school_name', 'total_SAT']].head(10)
print(top_10_schools)
#3
borough_stats = schools.groupby('borough').agg(
num_schools = ('school_name', 'count'),
average_SAT = ('total_SAT', 'mean'),
std_SAT = ('total_SAT', 'std')
).reset_index()
borough_stats = borough_stats.round(2)
largest_std_dev = borough_stats.sort_values('std_SAT', ascending=False).head(1)
print(largest_std_dev)