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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...Identificar las escuelas con los mejores resultados en matemáticas
import pandas as pd
# Read in the data
schools = pd.read_csv("schools.csv")
# Filtrar las escuelas con puntajes de matemáticas >= 640
best_math_schools = schools[schools['average_math'] >= 640][['school_name', 'average_math']]
# Ordenar los resultados por average_math en orden descendente
best_math_schools = best_math_schools.sort_values(by='average_math', ascending=False).reset_index(drop=True)
# Mostrar los mejores resultados en matemáticas
print(best_math_schools)
Identificar las 10 mejores escuelas basadas en los puntajes combinados del SAT
# Calcular el puntaje total del SAT
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']
# Ordenar los resultados por total_SAT en orden descendente y seleccionar las 10 mejores escuelas
top_10_schools = schools[['school_name', 'total_SAT']].sort_values(by='total_SAT', ascending=False).head(10).reset_index(drop=True)
# Mostrar las 10 mejores escuelas
print(top_10_schools)
Encontrar el distrito con la mayor desviación estándar en el puntaje combinado del SAT
# Agrupar por distrito y calcular la desviación estándar y media del puntaje total del SAT
borough_stats = schools.groupby('borough').agg(
num_schools=('school_name', 'count'),
average_SAT=('total_SAT', 'mean'),
std_SAT=('total_SAT', 'std')
).reset_index()
# Redondear los valores numéricos a dos decimales
borough_stats['average_SAT'] = borough_stats['average_SAT'].round(2)
borough_stats['std_SAT'] = borough_stats['std_SAT'].round(2)
# Encontrar el distrito con la mayor desviación estándar
largest_std_dev = borough_stats.loc[borough_stats['std_SAT'].idxmax()].to_frame().T
# Mostrar el distrito con la mayor desviación estándar
print(largest_std_dev)