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# numpy.random.geometric¶

`numpy.random.``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

where p is the probability of success of an individual trial.

Note

New code should use the `geometric` method of a `default_rng()` instance instead; see random-quick-start.

Parameters
pfloat or array_like of floats

The probability of success of an individual trial.

sizeint or tuple of ints, optional

Output 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
outndarray or scalar

Drawn samples from the parameterized geometric distribution.

`Generator.geometric`

which should be used for new code.

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
```