BUG GH11693 Support NaT series concatenation #11705
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| y = pd.Series( pd.date_range('20151124 10:00', '20151124 11:00', freq = '1h', tz = "US/Eastern") ) | ||
| y[:] = pd.NaT | ||
| xy = pd.concat([x,y]) | ||
| tm.assert_equal(xy[0], x[0]) |
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use tm.assert_series_equal & construct the expected series
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couple comments, pls add a whatsnew note |
| x = pd.Series( pd.date_range('20151124 08:00', '20151124 09:00', freq = '1h', tz = "US/Eastern") ) | ||
| y = pd.Series( pd.date_range('20151124 10:00', '20151124 11:00', freq = '1h', tz = "US/Eastern") ) | ||
| y[:] = pd.NaT | ||
| xy = pd.concat([x,y]) |
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not 100% sure that we have all of these tests, so can you add this for no-tz's as well, and both series all-nat (both with and w/o tz's). use a loop to check all 4 conditions.
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further a concat of tz-aware and (different tz or no tz) should result in object (works, just put all tests in the same place).
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if we have other tests in merge which test this kind of thing, pls move to a similar location (I don't know if we do)
jreback
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can you update according to comments |
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apologies for the delay. Will fix over the weekend. |
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| @@ -955,8 +955,12 @@ def get_result(self): | |||
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| # stack blocks | |||
| if self.axis == 0: | |||
| new_data = com._concat_compat([x._values for x in self.objs]) | |||
| to_concat = [x._values for x in self.objs] | |||
| typs = com.get_dtype_kinds(to_concat) | |||
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this should be fixed solely in _concat_compat
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can you update |
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superseded by #12195 |
Please review .
Closes #11693