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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
    import numpy as np
    
    # Read in the data
    schools = pd.read_csv("schools.csv")
    
    # Preview the data
    schools.head()
    
    # Start coding here...
    threshold = 640
    best_math_schools = schools[schools["average_math"]>= threshold][["school_name","average_math"]]
    best_math_schools = best_math_schools.sort_values(by="average_math",ascending=False)
    
    schools["total_SAT"] = schools["average_math"] + schools["average_reading"] + schools["average_writing"]
    top_10_schools = schools.sort_values(by="total_SAT", ascending=False)[:10]
    top_10_schools = top_10_schools[["school_name","total_SAT"]]
    
    borough_counts = schools["borough"].value_counts().reset_index()
    borough_counts.columns = ["borough","num_schools"]
    
    borough_stats = schools.groupby("borough")["total_SAT"].agg([np.mean,np.std])
    borough_stats.columns = ["average_SAT", "std_SAT"]
    borough_stats["average_SAT"] = round(borough_stats["average_SAT"],2)
    borough_stats["std_SAT"] = round(borough_stats["std_SAT"],2)
    borough_stats_all = borough_stats.merge(borough_counts,left_on="borough", right_on="borough")
    borough_stats_all = borough_stats_all.set_index("borough").sort_values(by="std_SAT",ascending=False)
    largest_std_dev = borough_stats_all[["num_schools","average_SAT","std_SAT"]].head(1)