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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...

1. Which NYC schools have the best math results?

1.Solution

  • Sort first the values in "average_math" in descending order using .sort_values(ascending=False).
sorted_math = schools.sort_values('average_math', ascending=False)
sorted_math.head()
  • To get the best math results, get first the 80% of 800 (maximum possible score) and the result is 640. Use this to filter the results.
per_80 = 800 * 0.8

atleast_80 = sorted_math[sorted_math['average_math'] >= per_80]

# Get the column ["school_name", "average_math"] of the results, then store it to "best_math_schools"
best_math_schools = atleast_80[["school_name", "average_math"]]
best_math_schools

2. What are the top 10 performing schools based on the combined SAT scores?

2. Solution

  • Get the sum of average_math, average_reading, average_writing, then store the result to a variable named total_SAT
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']
schools.head()
  • Sort the values of total_SAT in descending orders (ascending=False), store them in a new column named "total_SAT" and store the results as a pandas DataFrame called top_10_schools
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