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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...
# Which NYC schools have the best math results?
math = schools[["school_name", "average_math"]]
math_sorted = math.sort_values("average_math", ascending = False)
best_math_schools = math_sorted[math_sorted["average_math"] >= 0.8 * 800]
print(best_math_schools)
school_SAT = schools
school_SAT["total_SAT"] = school_SAT["average_math"] + school_SAT["average_reading"] + school_SAT["average_writing"]

school_SAT_sorted = school_SAT.sort_values("total_SAT", ascending = False)
school_SAT_sorted_filtered = school_SAT_sorted[["school_name", "total_SAT"]]
top_10_schools = school_SAT_sorted_filtered.iloc[0:10]
print(top_10_schools)
borough_sorted = (
    school_SAT
    .groupby("borough")["total_SAT"]
    .std()
    .sort_values(ascending = False)
    .to_frame()
    .reset_index()
)
highest_dev_borough = borough_sorted.iloc[0,0]

highest_dev_df = school_SAT[school_SAT["borough"] == highest_dev_borough]
num_schools = (
    highest_dev_df
    .groupby("borough")["school_name"]
    .count()
    .to_frame()
    .reset_index()
    .iloc[0,1]
    .round(2)
)

average_SAT = (
    highest_dev_df
    .groupby("borough")["total_SAT"]
    .mean()
    .to_frame()
    .reset_index()
    .iloc[0,1]
    .round(2)
)

std_SAT = (
    highest_dev_df
    .groupby("borough")["total_SAT"]
    .std()
    .to_frame()
    .reset_index()
    .iloc[0,1]
    .round(2)
)

prep = {
    "borough" : highest_dev_borough,
    "num_schools" : num_schools,
    "average_SAT" : average_SAT,
    "std_SAT" : std_SAT
}

largest_std_dev = pd.DataFrame([prep])
print(largest_std_dev.head())