numpy.random.exponential(scale=1.0, size=None)

Exponential distribution.

Its probability density function is

f(x; \lambda) = \lambda \exp(-\lambda x),

for x > 0 and 0 elsewhere. lambda is known as the rate parameter.

The exponential distribution is a continuous analogue of the geometric distribution. It describes many common situations, such as the size of raindrops measured over many rainstorms [61], or the time between page requests to Wikipedia [62].


scale : float

The rate parameter, \lambda.

size : tuple of ints

Number of samples to draw. The output is shaped according to size.


[61]Peyton Z. Peebles Jr., “Probability, Random Variables and Random Signal Principles”, 4th ed, 2001, p. 57.
[62]“Poisson Process”, Wikipedia,

Previous topic


Next topic


This Page

Quick search