Numpy Sampling with Replacement
To generate a sample with replacement with numpy from a given array, use random.choice which takes as arguments
- $a$: array to sample from
- $size$: the size of the samples array/output
- $replace$: Sample with or without replacement
- $p$: probabilities associated with each entry. If not provided, the uniform probability is assumed
In the example below, I generate a sample of 21 events from a list ['A', 'B', 'C', 'D', 'E'] with replacement.
import numpy as np
a = ['A', 'B', 'C', 'D', 'E']
# generate samples
sample = np.random.choice( a=a, size=21, replace=True )
sample