Since Python 3.6 there is a method `choices`

from the `random`

module.

```
In [1]: import random
In [2]: random.choices(
...: population=[['a','b'], ['b','a'], ['c','b']],
...: weights=[0.2, 0.2, 0.6],
...: k=10
...: )
Out[2]:
[['c', 'b'],
['c', 'b'],
['b', 'a'],
['c', 'b'],
['c', 'b'],
['b', 'a'],
['c', 'b'],
['b', 'a'],
['c', 'b'],
['c', 'b']]
```

Note that `random.choices`

will sample *with replacement*, per the docs:

Return a

`k`

sized list of elements chosen from the population with replacement.

Note for completeness of answer:

When a sampling unit is drawn from a finite population and is returned

to that population, after its characteristic(s) have been recorded,

before the next unit is drawn, the sampling is said to be “with

replacement”. It basically means each element may be chosen more than

once.

If you need to sample without replacement, then as @ronan-paixão’s brilliant answer states, you can use `numpy.choice`

, whose `replace`

argument controls such behaviour.