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Diffstat (limited to 'numpy/random/mtrand.pyx')
| -rw-r--r-- | numpy/random/mtrand.pyx | 18 |
1 files changed, 17 insertions, 1 deletions
diff --git a/numpy/random/mtrand.pyx b/numpy/random/mtrand.pyx index edf812a4d..dfa553ee4 100644 --- a/numpy/random/mtrand.pyx +++ b/numpy/random/mtrand.pyx @@ -537,6 +537,22 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized exponential distribution. + Examples + -------- + A real world example: Assume a company has 10000 customer support + agents and the average time between customer calls is 4 minutes. + + >>> n = 10000 + >>> time_between_calls = np.random.default_rng().exponential(scale=4, size=n) + + What is the probability that a customer will call in the next + 4 to 5 minutes? + + >>> x = ((time_between_calls < 5).sum())/n + >>> y = ((time_between_calls < 4).sum())/n + >>> x-y + 0.08 # may vary + See Also -------- random.Generator.exponential: which should be used for new code. @@ -3050,7 +3066,7 @@ cdef class RandomState: >>> b = [] >>> for i in range(1000): ... a = 10. + np.random.standard_normal(100) - ... b.append(np.product(a)) + ... b.append(np.prod(a)) >>> b = np.array(b) / np.min(b) # scale values to be positive >>> count, bins, ignored = plt.hist(b, 100, density=True, align='mid') |