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Project: Exploring NYC Public School Test Result Scores
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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
    # Start coding here...
    # Add as many cells as you like...
    best_math_schools = schools[["school_name", "average_math"]][schools["average_math"]>= (800*0.8)]
    best_math_schools = best_math_schools.sort_values("average_math", ascending = False)
    schools["total_SAT"] = schools["average_math"]+schools["average_reading"]+ schools["average_writing"]
    schools = schools.sort_values("total_SAT", ascending = False)
    top_10_schools = schools[["school_name", "total_SAT"]][0:10]
    borough_schools = pd.DataFrame(columns = ["num_schools","average_SAT","std_SAT"])
    largest_std_dev = borough_schools[borough_schools["std_SAT"].max() == borough_schools["std_SAT"]]
    largest_std_dev["average_SAT"] = schools["total_SAT"][schools["borough"] == largest_std_dev.index[0]].mean()
    largest_std_dev["num_schools"] = len(schools[schools["borough"] == largest_std_dev.index[0]])