# numpy.random.Generator.geometric

method

random.Generator.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 floats

      The probability of success of an individual trial.

    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. 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 scalar

      Drawn 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.default_rng().geometric(p=0.35, size=10000)

  How many trials succeeded after a single run?

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

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