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DOC: update docstring of pandas.Series.add_prefix docstring #20313

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Mar 13, 2018
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DOC: update docstring of pandas.Series.add_prefix docstring #20313

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5e780e9
DOC: Improve the docstring of Series.add_prefix()
astrastefania Mar 12, 2018
397f05d
DOC: Fixe the issues in the comments
astrastefania Mar 13, 2018
c719d7a
DOC: Update panle to Series
astrastefania Mar 13, 2018
e14315d
DOC: Added DataFrame example
astrastefania Mar 13, 2018
f23e340
DOC: Fix PEP8
astrastefania Mar 13, 2018
177285d
DOC: Fix PEP8spaces
astrastefania Mar 13, 2018
67c8dbe
DOC: Fix last docstring issue
astrastefania Mar 13, 2018
6d599ad
Spacing
TomAugspurger Mar 13, 2018
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45 changes: 42 additions & 3 deletions pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2963,15 +2963,54 @@ def _update_inplace(self, result, verify_is_copy=True):

def add_prefix(self, prefix):
"""
Concatenate prefix string with panel items names.
Prefix labels with string `prefix`.

For Series, the row labels are prefixed.
For DataFrame, the column labels are prefixed.

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Panel is deprecated, we may want to use Series or DataFrame, or something generic.

I'd try to find uses cases on the internet for this method, and add in the extended summary when this method can be useful, if possible.

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Thanks! I used Series as it is a Series module in this case.

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For this and #20315, these apply to both Series and DataFrame (and Panel, but we don't care about that). So perhaps

Prefix row labels with a string `prefix`.

I want to avoid items, as (to me) I think dict.items so key-value pairs. But we're just touching the row labels here.

That summary is strange since we use Prefix as a verb and nound. Maybe "Prepend" would be better?

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I see, thank you, my doubt is that on DataFrames add_prefix() adds a prefix on columns names not on rows, for example: df = pd.DataFrame({'A':[1,2,3,4], 'B':[3,4,5,6]}), df.add_suffix('_item'). For this motivations I decided to leave on Series.

Perhaps I could updated the docstring for pandas.DataFrame.add_prefix with the relative example to avoid confusion and let this as it is.

Let me know what sound better. :)

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@TomAugspurger TomAugspurger Mar 13, 2018 •
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Ahh, good catch! I would say splitting the docstring is more complexity that warranted. How about somehting like

"""
Prefix labels with string `prefix`.

For Series, the row labels are prefixed. For DataFrame, the column labels are prefixed

...
"""

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Yes, I do agree, thanks!

I didn't know about the issue of splitting docstring, so in this case is better have the same for both pandas.Series.add_prefix and pandas.DataFrame.add_prefix?

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Yes, the docstring you've been editing in core/generic.py is used by both Series.add_prefix and DataFrame.add_prefix.

Parameters
----------
prefix : string
prefix : str
The string to add before each label.

Returns
-------
with_prefix : type of caller
Series or DataFrame
Original Series or DataFrame with updated labels.
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This make it sound a bit like the object is modified inplace. Could you instead say

Series or DataFrame
    New Series or DataFrame with updated labels.

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Actually is modified inplace, should it be specified?

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Hmm I don't think so

In [6]: s = pd.Series(1, ['a', 'b'])

In [7]: s
Out[7]:
a    1
b    1
dtype: int64

In [8]: s.add_prefix('foo_')
Out[8]:
foo_a    1
foo_b    1
dtype: int64

In [9]: s
Out[9]:
a    1
b    1
dtype: int64

s is unmodified.

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Sorry, I meant it's unmodified! I agree is not modified inplace.


See Also
--------
Series.add_suffix: Suffix labels with string `suffix`.

Examples
--------
>>> s = pd.Series([1, 2, 3, 4])
>>> s
0 1
1 2
2 3
3 4
dtype: int64
>>> s.add_prefix('item_')
item_0 1
item_1 2
item_2 3
item_3 4
dtype: int64
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Add a blank line and then an example with DataFrame.


>>> df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [3, 4, 5, 6]})
>>> df
A B
0 1 3
1 2 4
2 3 5
3 4 6
>>> df.add_suffix('_item')
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This should be the add_prefix example I think :)

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Yes!!! 😄

A_item B_item
0 1 3
1 2 4
2 3 5
3 4 6
"""
new_data = self._data.add_prefix(prefix)
return self._constructor(new_data).__finalize__(self)
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