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 adefault_rng()
instance instead; see randomquickstart. 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)
, thenm * n * k
samples are drawn. If size isNone
(default), a single value is returned ifp
is a scalar. Otherwise,np.array(p).size
samples are drawn.
 Returns
 outndarray or scalar
Drawn samples from the parameterized geometric distribution.
See also
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