# randomgen.mtrand.RandomState.choice¶

- RandomState.choice(
*a*,*size=None*,*replace=True*,*p=None*)¶ Generates a random sample from a given array

New in version 1.7.0.

- Parameters
**a**1-D array-like or intIf an ndarray, a random sample is generated from its elements. If an int, the random sample is generated as if a were np.arange(a)

**size**int or tuple of ints, optionalOutput 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, optionalWhether the sample is with or without replacement. Default is True, meaning that a value of

`a`

can be selected multiple times.**p**1-D array-like, optionalThe probabilities associated with each entry in a. If not given, the sample assumes a uniform distribution over all entries in

`a`

.

- Returns
**samples**single item or ndarrayThe generated random samples

- Raises
- ValueError
If a is an int and less than zero, if a or p are not 1-dimensional, if a is an array-like of size 0, if p is not a vector of probabilities, if a and p have different lengths, or if replace=False and the sample size is greater than the population size

See also

Examples

Generate a uniform random sample from np.arange(5) of size 3:

>>> np.random.choice(5, 3) array([0, 3, 4]) # random >>> #This is equivalent to np.random.randint(0,5,3)

Generate a non-uniform random sample from np.arange(5) of size 3:

>>> np.random.choice(5, 3, p=[0.1, 0, 0.3, 0.6, 0]) array([3, 3, 0]) # random

Generate a uniform random sample from np.arange(5) of size 3 without replacement:

>>> np.random.choice(5, 3, replace=False) array([3,1,0]) # random >>> #This is equivalent to np.random.permutation(np.arange(5))[:3]

Generate a non-uniform random sample from np.arange(5) of size 3 without replacement:

>>> np.random.choice(5, 3, replace=False, p=[0.1, 0, 0.3, 0.6, 0]) array([2, 3, 0]) # random

Any of the above can be repeated with an arbitrary array-like instead of just integers. For instance:

>>> aa_milne_arr = ['pooh', 'rabbit', 'piglet', 'Christopher'] >>> np.random.choice(aa_milne_arr, 5, p=[0.5, 0.1, 0.1, 0.3]) array(['pooh', 'pooh', 'pooh', 'Christopher', 'piglet'], # random dtype='<U11')