### Navigation

- index
- modules |
- next |
- previous |
- NumPy v1.3 Manual (DRAFT) »
- NumPy Reference »
- Routines »
- Random sampling (`numpy.random`) »

# 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.

  Parameters: | p : float The probability of success of an individual trial. size : tuple of ints Number of values to draw from the distribution. The output is shaped according to size.
  Returns: | out : ndarray Samples from the geometric distribution, shaped according to size.

  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

### Navigation

- index
- modules |
- next |
- previous |
- NumPy v1.3 Manual (DRAFT) »
- NumPy Reference »
- Routines »
- Random sampling (`numpy.random`) »