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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...
high_math = schools[schools["average_math"] >= 640]
high_math
best_math = high_math.sort_values("average_math", ascending = False).head(10)
best_math_schools = best_math[["school_name","average_math"]]
best_math_schools
import matplotlib.pyplot as plt
best_math_schools.plot(x="school_name", y="average_math", kind="bar", legend=False)
plt.title('Top 10 Schools by Average Math Score')
plt.grid(True)
plt.show()
schools.head()
schools["total_SAT"] = schools["average_math"] + schools["average_reading"] + schools["average_writing"]
schools.head()
top_10 = schools.sort_values("total_SAT", ascending = False).head(10)
top_10_schools = top_10[["school_name","total_SAT"]]
top_10_schools
top_10_schools.plot(x="school_name", y="total_SAT", kind="bar", legend=False)
plt.title('Top 10 Schools by SAT Score')
plt.grid(True)
plt.show()
schools.head()
school_groupby =schools.grouped = schools.groupby("borough")["total_SAT"].agg([
    ("num_schools", "count"),
    ("average_SAT", "mean"),
    ("std_SAT", "std")
])

school_groupby
school_groupby["average_SAT"] = school_groupby["average_SAT"].round(2)
school_groupby["std_SAT"] = school_groupby["std_SAT"].round(2)
school_groupby
largest_std_dev = school_groupby[school_groupby["std_SAT"] == school_groupby["std_SAT"].max()]

largest_std_dev = largest_std_dev.reset_index()

largest_std_dev