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 
[Error: Macro 'mathplot' error: mathplot() got an unexpected keyword argument 'title']
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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