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Module containing utilities for NDFrame.sample() and .GroupBy.sample()
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Process and validate the `weights` argument to `NDFrame.sample` and
`.GroupBy.sample`.
Returns `weights` as an ndarray[np.float64], validated except for normalizing
weights (because that must be done groupwise in groupby sampling).
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Process and validate the `n` and `frac` arguments to `NDFrame.sample` and
`.GroupBy.sample`.
Returns None if `frac` should be used (variable sampling sizes), otherwise returns
the constant sampling size.
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Randomly sample `size` indices in `np.arange(obj_len)`
Parameters
----------
obj_len : int
The length of the indices being considered
size : int
The number of values to choose
replace : bool
Allow or disallow sampling of the same row more than once.
weights : np.ndarray[np.float64] or None
If None, equal probability weighting, otherwise weights according
to the vector normalized
random_state: np.random.RandomState or np.random.Generator
State used for the random sampling
Returns
-------
np.ndarray[np.intp]
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