DOC/DEPR: ensure that @deprecated functions have correct docstring

[jorisvandenbossche]

Follow-up on #16955, the Series.argmin/argmax now have a docstring.

Currently:

In [1]: pd.Series.argmax? Signature: pd.Series.argmax(*args, **kwargs) Docstring: <no docstring> File: ~/scipy/pandas/pandas/util/_decorators.py Type: function 

With this PR:

In [1]: pd.Series.argmax? Signature: pd.Series.argmax(self, axis=None, skipna=True, *args, **kwargs) Docstring: 'argmax' is deprecated, use 'idxmax' instead. The behavior of 'argmax' will be corrected to return the positional maximum in the future. Use 'series.values.argmax' to get the position of the maximum now. Index *label* of the first occurrence of maximum of values. Parameters ---------- skipna : boolean, default True Exclude NA/null values Returns ------- idxmax : Index of maximum of values Notes ----- This method is the Series version of ``ndarray.argmax``. This method returns the label of the maximum, while ``ndarray.argmax`` returns the position. To get the position, use ``series.values.argmax()``. See Also -------- DataFrame.idxmax numpy.ndarray.argmax File: ~/scipy/pandas/pandas/core/series.py Type: function 

[pep8speaks]

Hello @jorisvandenbossche! Thanks for updating the PR.

• In the file pandas/util/_decorators.py, following are the PEP8 issues :

Line 41:28: W503 line break before binary operator

Comment last updated on November 13, 2017 at 23:33 Hours UTC

[jorisvandenbossche]

This needs #18256 to be merged first

[codecov]

Codecov Report

Merging #18215 into master will decrease coverage by 0.01%.
The diff coverage is 100%.

@@ Coverage Diff @@ ## master #18215 +/- ## ========================================== - Coverage 91.4% 91.38% -0.02%  ========================================== Files 164 164 Lines 49878 49880 +2 ========================================== - Hits 45590 45583 -7  - Misses 4288 4297 +9

Flag	Coverage Δ
#multiple	89.19% <100%> (ø)	⬆️
#single	39.42% <100%> (-0.06%)	⬇️

Impacted Files	Coverage Δ
pandas/core/series.py	95% <ø> (ø)	⬆️
pandas/util/_decorators.py	81.03% <100%> (+0.33%)	⬆️
pandas/io/gbq.py	25% <0%> (-58.34%)	⬇️
pandas/core/frame.py	97.8% <0%> (-0.1%)	⬇️

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