# Choosing more than 1 element from the list

## Question:

I am trying to make a choice for each element in `elements`

, and then I am pairing up the element in `elements`

list with its preferential choice(one,two or three). The choice is mostly done regarding the probabilities (`weights`

) of the elements. The code until here:

```
from numpy.random import choice
elements = ['one', 'two', 'three']
weights = [0.2, 0.3, 0.5]
chosenones= []
for el in elements:
chosenones.append(choice(elements,p=weights))
tuples = list(zip(elements,chosenones))
```

Yields:

```
[('one', 'two'), ('two', 'two'), ('three', 'two')]
```

What I need is, for each element to make **two** choices instead of one.

The expected output should look like:

```
[('one', 'two'), ('one', 'one'), ('two', 'two'),('two', 'three'), ('three', 'two'), ('three', 'one')]
```

Do you know how to do have this output?

## Answers:

If you accept duplicates, `random.choices`

will do the job:

random.choices(population, weights=None, *, cum_weights=None, k=1)

Return a k sized list of elements chosen from the population with replacement. If the population is empty, raises IndexError.

If a weights sequence is specified, selections are made according to the relative weights.

```
>>> random.choices(['one', 'two', 'three'], weights=[0.2, 0.3, 0.5], k=2)
['one', 'three']
```

If you need two, just tell `numpy.random.choice()`

to pick two values; include the `el`

value as a tuple as you loop (no need to use `zip()`

):

```
tuples = []
for el in elements:
for chosen in choice(elements, size=2, replace=False, p=weights):
tuples.append((el, chosen))
```

or by using a list comprehension:

```
tuples = [(el, chosen) for el in elements
for chosen in choice(elements, size=2, replace=False, p=weights)]
```

By setting `replace=False`

, you get unique values; remove it or set it to `True`

explicitly to allow for repetition. See the `numpy.random.choice()`

documentation:

size:int or tuple of ints, optional

Output shape. If the given shape is, e.g.,`(m, n, k)`

, then`m * n * k`

samples are drawn. Default is`None`

, in which case a single value is returned.

replace:boolean, optional

Whether the sample is with or without replacement

Demo:

```
>>> from numpy.random import choice
>>> elements = ['one', 'two', 'three']
>>> weights = [0.2, 0.3, 0.5]
>>> tuples = []
>>> for el in elements:
... for chosen in choice(elements, size=2, replace=False, p=weights):
... tuples.append((el, chosen))
...
>>> tuples
[('one', 'three'), ('one', 'one'), ('two', 'three'), ('two', 'two'), ('three', 'three'), ('three', 'two')]
>>> [(el, chosen) for el in elements for chosen in choice(elements, size=2, replace=False, p=weights)]
[('one', 'one'), ('one', 'three'), ('two', 'one'), ('two', 'three'), ('three', 'two'), ('three', 'three')]
```