school = 'Platzi' print(____) # Incluir la variable declarada anteriormente.

import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns # agrega librerías que necesites

url_wine_red = 'https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv' url_wine_white = 'https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv'

red = pd.read_csv(____, delimiter="____") white = pd.read_csv(____, delimiter="____")

red['____']='red' white['____']='white'

total_wine=red.____(____, ignore_index=True)

quality = total_wine['____'] ____

total_wine['quality_category'] = total_wine['quality'].apply(lambda x: ____) total_wine.tail()

total_wine.quality_category = ____ total_wine.info()

3. Elimina los outliers de ser necesario en la siguiente celda.

total_wine.____()[['____']].sort_values(by='____', ascending = False)