# n: number of rows to be extracted randomly
# random_state fixed for reproducibility
# replace = True for extraction with replacement
df.sample(n=3, random_state=42, replace=False)
import numpy as np
import pandas as pd
df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))