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DOC: Update Series.repeat docstring #20242

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DOC: Update Series.repeat docstring #20242

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DOC: Improved the docstring of Series.repeat
Mar 10, 2018
b89d4f4
Merge remote-tracking branch 'upstream/master' into repeat
Mar 10, 2018
6607f79
Spacing, variables referencing, *args and **kwargs
pedropazzini Mar 10, 2018
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43 changes: 40 additions & 3 deletions pandas/core/series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -918,12 +918,49 @@ def _set_values(self, key, value):
@deprecate_kwarg(old_arg_name='reps', new_arg_name='repeats')
def repeat(self, repeats, *args, **kwargs):
"""
Repeat elements of an Series. Refer to `numpy.ndarray.repeat`
for more information about the `repeats` argument.
Repeat elements of a Series.

Each element of the Series is repeated 'repeats' times.
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Single backtick for parameters like `repeats`


Parameters
----------
repeats : int
The number of repetitions for each element.
*args
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You can remove args and kwargs. The validation function is an implementation detail that users shouldn't have to worry about. repeats is the only valid argument.

You could mention, perhaps in Notes that "unlike numpy.repeat, `axis` is not a valid argument".

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Listen to @jorisvandenbossche about args and kwargs, not me :)

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After discussion, you can document them like

*args, **kwargs
    Additional keywords have no effect but might be accepted for
    compatibility with numpy.

These parameters will be passed to a validation function.
**kwargs
These parameters will be passed to a validation function.

See also
--------
numpy.ndarray.repeat
Series.append : Concatenate two or more Series.
pandas.concat : Concatenate two or more DataFrames.
numpy.repeat : Repeat elements of an array.

Returns
-------
Series
The repeated version of the Series.

Examples
--------
>>> df = pd.DataFrame({'col1' : ['A','B','C'],'col2' : [ 0 , 1 , 2 ]})
>>> df
col1 col2
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Spacing looks off. Should move it over a few spaces I think. Double check that this is right.

0 A 0
1 B 1
2 C 2
>>> df.col1.repeat(3)
0 A
0 A
0 A
1 B
1 B
1 B
2 C
2 C
2 C
Name: col1, dtype: object
"""
nv.validate_repeat(args, kwargs)
new_index = self.index.repeat(repeats)
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