Bug in to_datetime raising ValueError with None and NaT and more than 50 elements #41006
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phofl
added
Dtype Conversions
| def test_convert_object_to_datetime_with_cache(self): | ||
| # GH#39882 | ||
| ser = pd.Series( | ||
| [None] + [pd.NaT] * 50 + [pd.Timestamp("2012-07-26")], dtype="object" |
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could make 50 parameter in tools.datetimes, ensures that the test stays valid even if that gets changed
jreback
requested changes
Apr 19, 2021
| @@ -225,3 +227,16 @@ def test_convert_bool_dtype(self): | |||
| # GH32287 | |||
| df = pd.DataFrame({"A": pd.array([True])}) | |||
| tm.assert_frame_equal(df, df.convert_dtypes()) | |||
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| def test_convert_object_to_datetime_with_cache(self): | |||
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can you put this with the other to_datetime tests: pandas/tests/tools/test_to_datetime.py; there a number of caching tests if you can locate nearby
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Moved, hope the location is ok, cache tests are everywhere there :)
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yep lgtm. lots of tests :->
|
@jreback greenish |
jreback
approved these changes
Apr 20, 2021
|
thanks @phofl |
yeshsurya
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yeshsurya
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None and NaT are different for unique while convert_listlike casts None to NaT, hence causing dups
Not sure if we could do something better.