BUG: to_datetime when called with a unit and coerce is buggy #13033
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jreback
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@jorisvandenbossche straightforward but lots of cases. So actually what I need is a bunch more tests. Stuff like mixed float/int/string (that are integer/float-like) with some NaT's thrown in (these should pass). |
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This was referenced Apr 30, 2016
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| .. ipython:: python | ||
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| pd.to_datetime(1420043460, unit='s', errors='coerce') | ||
| pd.to_datetime(11111111, unit='D', errors='ignore') |
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You show the changes for errors='ignore' and errors='coerce', but I think the default behaviour (for errors='raise') also changed? (from OverflowError to ValueError)?
Maybe good to add this case as well to the examples
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Version 0.18.1 * tag 'v0.18.1': (96 commits) RLS: v0.18.1 DOC: update release notes BUG: More followups on to_datetime exceptions, xref pandas-dev#13033 BUG: COMPAT:0.18 added scipy version check TST: add nose import for skipped scipy tests CLN: move interpolation tests from test_generic to test_missing BUG: introduced in pandas-dev#13033 BUG: .isin(...) now coerces sets to lists COMPAT: Expand compatibility with fromnumeric.py TST: fixup codecov.yml DOC: Add tutorial link PERF: Sparse IntIndex.make_union / Numeric ops COMPAT: ensure platform it on 32-bit DOC: whatsnew fixes TST: properly handle unit='ns' and object/int arrays BUG: to_datetime when called with a unit and coerce is buggy TST: more salary.table location issues TST: move salar.table to correct url location CLN: fix up parser setup structure TST: windows compat on to_numeric tests ...
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closes #11758