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.    
Parameters:

p : float The probability of success of an individual trial. 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.   
Returns:

out : ndarray Samples from the geometric distribution, shaped according to size.    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
 


    
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