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()
# Menentukan nilai ambang batas 80% dari nilai tertinggi pada kolom "average_math"
best_math_results = 640
# Memfilter sekolah yang memiliki rata-rata matematika >= 80% dari nilai maksimum
best_math_schools = schools[schools["average_math"] >= best_math_results][["school_name", "average_math"]]
best_math_schools = best_math_schools.sort_values("average_math", ascending= False)
# Menampilkan hasil
print(best_math_schools)
# Menambahkan kolom total SAT sebagai jumlah dari nilai rata-rata math, reading, dan writing
schools["total_SAT"] = schools["average_math"] + schools["average_reading"] + schools["average_writing"]
# Mengurutkan sekolah berdasarkan total SAT, dari yang tertinggi ke terendah, dan memilih 10 teratas
top_10_schools = schools.sort_values(by="total_SAT", ascending=False)[["school_name", "total_SAT"]].head(10)
# Menampilkan hasil
print(top_10_schools)
import pandas as pd
# Menghitung statistik untuk setiap borough
borough_stats = schools.groupby("borough")["total_SAT"].agg(
num_schools="count", # Jumlah sekolah dalam borough
average_SAT="mean", # Rata-rata skor SAT
std_SAT="std" # Standar deviasi skor SAT
).reset_index()
# Menemukan borough dengan standar deviasi SAT terbesar
max_std = borough_stats["std_SAT"].max()
largest_std_dev = borough_stats[borough_stats["std_SAT"] == max_std]
# Membulatkan semua nilai numerik ke 2 desimal
largest_std_dev = largest_std_dev.round(2)
# Menampilkan hasil
print(largest_std_dev)