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# numpy.random.poisson

`numpy.random.``poisson`(lam=1.0, size=None)

  Draw samples from a Poisson distribution.

  The Poisson distribution is the limit of the Binomial distribution for large N.

  Parameters: | lam : float or sequence of float Expectation of interval, should be >= 0. A sequence of expectation intervals must be broadcastable over the requested size. 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. Default is None, in which case a single value is returned.

  Notes

  The Poisson distribution

  For events with an expected separation the Poisson distribution describes the probability of events occurring within the observed interval .

  Because the output is limited to the range of the C long type, a ValueError is raised when lam is within 10 sigma of the maximum representable value.

  References

  [R222] | Weisstein, Eric W. “Poisson Distribution.” From MathWorld–A Wolfram Web Resource. http://mathworld.wolfram.com/PoissonDistribution.html

  [R223] | Wikipedia, “Poisson distribution”, http://en.wikipedia.org/wiki/Poisson_distribution

  Examples

  Draw samples from the distribution:

      >>> import numpy as np
      >>> s = np.random.poisson(5, 10000)

  Display histogram of the sample:

      >>> import matplotlib.pyplot as plt
      >>> count, bins, ignored = plt.hist(s, 14, normed=True)
      >>> plt.show()

  (Source code, png, pdf)

  Draw each 100 values for lambda 100 and 500:

      >>> s = np.random.poisson(lam=(100., 500.), size=(100, 2))

  ()