# randomgen.mtrand.RandomState.geometric¶

- RandomState.geometric(
*p*,*size=None*)¶ Draw samples from the geometric distribution.

Bernoulli trials are experiments with one of two outcomes: success or failure (an example of such an experiment is flipping a coin). The geometric distribution models the number of trials that must be run in order to achieve success. It is therefore supported on the positive integers,

`k = 1, 2, ...`

.The probability mass function of the geometric distribution is

\[f(k) = (1 - p)^{k - 1} p\]where p is the probability of success of an individual trial.

- Parameters
**p**float or array_like of floatsThe probability of success of an individual trial.

**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. If size is`None`

(default), a single value is returned if`p`

is a scalar. Otherwise,`np.array(p).size`

samples are drawn.

- Returns
**out**ndarray or scalarDrawn samples from the parameterized geometric distribution.

Examples

Draw ten thousand values from the geometric distribution, with the probability of an individual success equal to 0.35:

>>> z = np.random.geometric(p=0.35, size=10000)

How many trials succeeded after a single run?

>>> (z == 1).sum() / 10000. 0.34889999999999999 # random