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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...# Best Math Schools (Top-10)
best_math_schools = schools[schools["average_math"] >= 640][["school_name", "average_math"]].sort_values("average_math", ascending = False)
print(best_math_schools)Top-10 schools based on combined SAT scores (Math + Reading + Writing)
Create a new column named "total_SAT"
schools["total_SAT"] = schools["average_math"] + schools["average_reading"] + schools["average_writing"]
print(schools[["total_SAT"]]) top_10_schools = schools[schools["total_SAT"] > 1881][["school_name", "total_SAT"]].sort_values("total_SAT", ascending = False)
print(top_10_schools)Which borough (only One) has the Largest Std in the combined /total SAT score (Math + Reading + Writing)
borough = schools.groupby("borough")["total_SAT"].agg(["mean", "std", "count"]).round(2)
print(borough)largest_std_dev = borough[borough["std"] == borough["std"].max()]
print(largest_std_dev)largest_std_dev = largest_std_dev.rename(columns={"count": "num_schools", "mean": "average_SAT", "std": "std_SAT"})
print(largest_std_dev)largest_std_dev.reset_index(inplace=True)
print(largest_std_dev)