REF: use array_algos shift for Categorical.shift #33663
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jreback
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Apr 20, 2020
| @@ -10,6 +10,10 @@ | |||
| def shift(values: np.ndarray, periods: int, axis: int, fill_value) -> np.ndarray: | |||
| new_values = values | |||
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| if periods == 0: | |||
| # TODO: should we copy here? | |||
| return new_values | |||
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I think we should, do we elsewhere?
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looks like we currently do a copy in 1/2 of places where this is called
|
lgtm. comment (can merge and followon or do here). |
Will do follow-up to make the copy consistent (and occur in exactly one place) |
gr8 |
CloseChoice
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We have duplicate code in Categorical.shift and Categorical.take that can be refactored out into Categorical._validate_fill_value (which is the name that DTA/TDA/PA use for the same method, which I intend to share eventually, xref #33660). From there the rest of Categorical.shift can dispatch to array_algos.transforms.shift.
The logic changed here is a TypeError becoming a ValueError (which matches what DTA/TDA/PA do)