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modified changes for datetime and NaT Objects Behavior closes #43280 #43289

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modified changes for datetime and NaT Objects Behavior closes #43280 #43289

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Navaneethan2503
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@Navaneethan2503 Navaneethan2503 commented Aug 29, 2021 •
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**Modified datatime object 👍 **
i have changed view values to numeric of date and missing data found in pd series is returns Nan when coerce errors .

**Example for solved changes 💯 **

>>> pd.to_numeric(pd.Series(datetime(2021, 8, 22)), errors="coerce")
[OUT]
0    20210822
dtype: int64

>>> pd.to_numeric(pd.Series(pd.NaT), errors="coerce")
[OUT]
0   NaN
dtype: float64

>>> s = pd.to_numeric(datetime(2021, 8, 22), errors="coerce")
0 20210822
dtype: Int64
>>> s = pd.to_numeric(pd.NaT, errors="coerce")
 nan

@pep8speaks
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pep8speaks commented Aug 29, 2021 •
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Hello @Navaneethan2503! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

Line 162:23: E271 multiple spaces after keyword
Line 185:14: W291 trailing whitespace

Line 795:5: E265 block comment should start with '# '
Line 800:1: E302 expected 2 blank lines, found 1
Line 801:5: E265 block comment should start with '# '
Line 806:1: E302 expected 2 blank lines, found 1
Line 807:5: E265 block comment should start with '# '
Line 812:1: E302 expected 2 blank lines, found 1
Line 813:5: E265 block comment should start with '# '
Line 816:1: W391 blank line at end of file

Comment last updated at 2021-08-31 14:28:48 UTC

@Navaneethan2503 Navaneethan2503 changed the title BUG: modified changes for datetime and NaT Objects Behavior closes #43280 modified changes for datetime and NaT Objects Behavior closes #43280 Aug 29, 2021
@Navaneethan2503 Navaneethan2503 mentioned this pull request Aug 29, 2021
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@hec10r
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hec10r commented Aug 29, 2021

Hi @Navaneethan2503, thank you for this PR. I think that this solves the problem for pd.NaT, but there is still an inconsistency for scalar arguments vs pd.Series:

>>> import pandas as pd
>>> from datetime import datetime
>>> pd.to_numeric(pd.Series(datetime(2021,8,22)), errors="coerce")
0    20210822
dtype: int64
>>> pd.to_numeric(datetime(2021,8,22), errors="coerce")
nan

Additionally, I am not sure that the idea is to change the current behavior of datetime series for a new one. Instead, the idea should be to apply the current behavior to scalar arguments.

Kavyasilam
Kavyasilam approved these changes Aug 29, 2021
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Good approach @Navaneethan2503

@Kavyasilam
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Hi @Navaneethan2503, thank you for this PR. I think that this solves the problem for pd.NaT, but there is still an inconsistency for scalar arguments vs pd.Series:

>>> import pandas as pd
>>> from datetime import datetime
>>> pd.to_numeric(pd.Series(datetime(2021,8,22)), errors="coerce")
0    20210822
dtype: int64
>>> pd.to_numeric(datetime(2021,8,22), errors="coerce")
nan

Additionally, I am not sure that the idea is to change the current behavior of datetime series for a new one. Instead, the idea should be to apply the current behavior to scalar arguments.

I thing all scalar argument are passed , my suggestion idea is good because datatime behaviour are all type passed

jreback
jreback requested changes Aug 29, 2021
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always always start with tests that fail w/o the change and pass with

@Navaneethan2503
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Final PR pass all scalar arguments including datetime and NaT DataType , make it merge

simonjayhawkins
simonjayhawkins requested changes Aug 30, 2021
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I think the expected behavior is still being discussed? This is breaking tests.

simonjayhawkins
simonjayhawkins requested changes Aug 30, 2021
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you have requested review but I see no changes since the previous review and ci is failing?

also can you move the tests from the docstring to pandas/tests and add a release note

simonjayhawkins
simonjayhawkins reviewed Aug 31, 2021
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doc/source/whatsnew/v1.4.0.rst
@@ -267,7 +267,7 @@ Datetimelike
^^^^^^^^^^^^
- Bug in :class:`DataFrame` constructor unnecessarily copying non-datetimelike 2D object arrays (:issue:`39272`)
- :func:`to_datetime` would silently swap ``MM/DD/YYYY`` and ``DD/MM/YYYY`` formats if the given ``dayfirst`` option could not be respected - now, a warning is raised in the case of delimited date strings (e.g. ``31-12-2012``) (:issue:`12585`)
-
-Bug in :class:'Series and scalar' to_numeric as inconsistent behaviour for datatime object (:issue:'43280')
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you can build the release notes and check the output https://pandas.pydata.org/pandas-docs/dev/development/contributing_documentation.html#building-the-documentation

@mroeschke
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Thanks for the PR but it appears this is a duplicate of #43315 which is a little further along. Closing as a duplicate but happy to have you work on other issues with a good first issue label.

@mroeschke mroeschke closed this Aug 31, 2021
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@simonjayhawkins simonjayhawkins simonjayhawkins requested changes

@Kavyasilam Kavyasilam Kavyasilam approved these changes

@jreback jreback Awaiting requested review from jreback

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BUG: pd.to_numeric has an inconsistent behavior for datetime objects
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@Navaneethan2503 @pep8speaks @hec10r @Kavyasilam @mroeschke @jreback @simonjayhawkins