Fix IntegerArray pow for special cases #30210
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When dividing by 0, the result should be `inf`, not `NaN`. Closes pandas-dev#27398
x^0 == 1 1^x == 1
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FYI @jorisvandenbossche this is slightly blocking #29964. It'll make the changes there more focused. |
| mask = np.where(other == 1, False, mask) | ||
| # 1 ** x is 1. | ||
| if omask is not None: | ||
| mask = np.where((other == 1) & ~omask, False, mask) |
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shouldn't this check for self._data == 1 ?
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Ah, no, because it is for the reversed op? (maybe add a comment)
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Your call on whether a comment is needed. It's clear IMO, though I wrote it :)
Co-Authored-By: Joris Van den Bossche <[email protected]>
…r/pandas into integer-array-pow-2
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@jorisvandenbossche good to go here? |
jorisvandenbossche
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Dec 14, 2019
proost
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Dec 19, 2019
x^0 == 1 1^x == 1
proost
pushed a commit
to proost/pandas
that referenced
this pull request
Dec 19, 2019
x^0 == 1 1^x == 1
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Split from #29964
Only 9e5a69c is relevant. The rest is #30183, but pushing this up now.