Though this article tackles **Poisson distribution**, a type of discrete probability distribution, it is rather focused on practical questions how to use matplotlib to construct graphs of that distribution.

Numpy offers three parameters that effect graphical appearance:

parameter |
meaning |
usage |

mu |
shape parameter |
essential, to construct a probability distribution |

loc |
origin |
optional, the origin of the probability distribution default = 0 |

size |
vector length |
optional, size of the one dimensional array of random variables default=0 => no array but a single random variable is returned |

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The probability mass function can be written:

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The cumulative probability function can be described by the equation:

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The function of the Numpy parameters can be tested by the following sage cell.

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