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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...
schools.info()
schools.isna().sum()
schools[schools['percent_tested'].isna()]
schools_work = schools.copy()
schools_work.head()

Eliminar valores NaN

schools_work = schools_work.fillna(0)
schools_work.isna().sum()
best_math_schools = schools_work[schools_work['average_math'] >= (800 * 0.80)][['school_name','average_math']].sort_values(by='average_math', ascending=False)
best_math_schools

10 escuelas con mejor desempeño

schools_work['total_SAT'] = schools_work['average_math'] + schools_work['average_reading'] + schools_work['average_writing']
top_10_schools = schools_work[['school_name','total_SAT']].sort_values(by='total_SAT', ascending=False).head(10)
top_10_schools

Distrito con desviacion estandar mas grande

largest_std_dev = schools_work.groupby('borough')['total_SAT'].agg(num_schools='size', average_SAT='mean', std_SAT='std').round(2).sort_values(by='std_SAT', ascending=False).head(1)
largest_std_dev