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API: Added axis argument to rename, reindex #17800
API: Added axis argument to rename, reindex #17800
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Ahh, I forgot that was keyword-only args are python3 only :/ |
OK, this is closer to @jorisvandenbossche's suggesting of adding a new parameter at the beginning. I chose |
Codecov Report
@@ Coverage Diff @@
## master #17800 +/- ##
==========================================
- Coverage 91.24% 91.22% -0.03%
==========================================
Files 163 163
Lines 49967 49993 +26
==========================================
+ Hits 45593 45606 +13
- Misses 4374 4387 +13
Continue to review full report at Codecov.
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Codecov Report
@@ Coverage Diff @@
## master #17800 +/- ##
==========================================
+ Coverage 91.22% 91.22% +<.01%
==========================================
Files 163 163
Lines 49994 50009 +15
==========================================
+ Hits 45606 45621 +15
Misses 4388 4388
Continue to review full report at Codecov.
|
DataFrame docstring:
Examples:
The most concerning part (to me) is the one emitting a warning. I interpret |
Probably too late, but in case it can still be used as inspiration, my original branch: https://github.com/pandas-dev/pandas/compare/master...jorisvandenbossche:harmonize-reindex-drop-original?expand=1 (from a long time ago, in the recent PR I removed the |
pandas/core/generic.py
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Using axis-style parameters | ||
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||
>>> df.rename(str.lower, axis='columns') | ||
A B |
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lower case ?
Are you also going to do |
Working on it now. 1e62a0e refactored the common bits out. Perhaps I'll just push my reindex branch in this PR? They're similar enough. I'll take your tests. |
As you prefer, no problem to have them both here (certainly if they would share code to do the validation) |
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Ok (force) pushed two clean commits, one for rename and one for reindex. I think this should be ready for review. |
doc/source/whatsnew/v0.21.0.txt
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@@ -109,6 +109,33 @@ For example: | |||
# the following is now equivalent | |||
df.drop(columns=['B', 'C']) | |||
|
|||
``rename``, ``reindex`` now also accepts axis keyword |
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Whoops, typo on accepts
-> accept
.
Trying to figure out the failing Panel test https://travis-ci.org/pandas-dev/pandas/jobs/284200489#L1392 now (cc @jreback) Edit: nvm, I think I found it. |
pandas/core/frame.py
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elif axis == 'columns': | ||
columns = arg | ||
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||
elif all(x is not None for x in (arg, index, columns)): |
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Could use pandas.core.common._all_not_none(arg, index, columns)
here instead.
pandas/core/frame.py
Outdated
).format(arg_name=arg_name) | ||
raise TypeError(msg) | ||
|
||
elif axis is None and (arg is not None and index is not None): |
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I think this can just be _all_not_none(arg, index)
. The axis is None
part should always be true due to the first if
statement.
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(didn't look at the tests yet)
Implementation-wise, I am wondering if it would be cleaner to convert the args to axis style instead to index/columns style. As inside reindex
and rename
, the index/column style is then converted to axis style (with _construct_axes_from_arguments
). So now you do the conversion sometimes twice in the different direction.
But if that is harder, I find it more important we get this in than to make it internally cleaner :-)
On a separate note, we should think whether we want to deprecate reindex_axis
and rename_axis
or not (can be separate though).
pandas/core/frame.py
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optional_labels="""labels : array-like | ||
New labels / index to conform the axis specified by 'axis' to.""", | ||
optional_axis="""axis : int or str, optional | ||
Axis to target. Can be either the axis name ('rows', 'columns') |
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rows -> index ?
pandas/core/frame.py
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versionadded_to_excel='', | ||
optional_mapper="""mapper : dict-like or function | ||
Applied to the axis specified by `axis`""", | ||
optional_labels="""labels : array-like |
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this is 'optional' as well (this is also specified for index
/columns
)
@@ -742,11 +742,13 @@ def swaplevel(self, i=-2, j=-1, axis=0): | |||
|
|||
Parameters | |||
---------- | |||
%(optional_mapper)s | |||
%(axes)s : scalar, list-like, dict-like or function, optional | |||
Scalar or list-like will alter the ``Series.name`` attribute, |
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Is this also true for the mapper?
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This is the Series.rename
docstring right now:
Signature: df.A.rename(index=None, **kwargs)
Docstring:
Alter axes input function or functions. Function / dict values must be
unique (1-to-1). Labels not contained in a dict / Series will be left
as-is. Extra labels listed don't throw an error. Alternatively, change
``Series.name`` with a scalar value (Series only).
Parameters
----------
index : scalar, list-like, dict-like or function, optional
Scalar or list-like will alter the ``Series.name`` attribute,
and raise on DataFrame or Panel.
dict-like or functions are transformations to apply to
that axis' values
So i didn't modify the signature at all. It doesn't have an mapper
argument.
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(I think that not having mapper
or axis
kwargs is the better option here, but I may be wrong)
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Sorry, I wanted to say that for the DataFrame docstring (this is in generic.py).
So I meant, for a dataframe.rename, is the explanation of index/column, also valid for mapper (scalar vs mapping)
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Yeah, the dict / function-like arguments descriptions are correct. Scalar / list-like don't apply. I could make that bit a shared_doc section... Let me try quick.
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Although, at some point a separate docstring might be easier.
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Ugh, this is pretty messy. I'm just going to leave as-is for now. For DataFrame.rename
the docstring starts
Parameters
----------
mapper : dict-like or function
Applied to the axis specified by `axis`
index, columns : scalar, list-like, dict-like or function, optional
Scalar or list-like will alter the ``Series.name`` attribute,
and raise on DataFrame or Panel.
dict-like or functions are transformations to apply to
that axis' values
axis : int or str, optional
Axis to target. Can be either the axis name ('index', 'columns')
or number (0, 1).
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I personally would also create separate docstrings for the series/dataframe versions of those methods. It will give a bit of duplication, but it will be much easier and take less time to make sure this duplication is done correctly than trying to figure out how to make it work with the docstring substitution.
But agree that can be in another PR.
pandas/core/generic.py
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Note that ``.reindex`` can be called by specifying either | ||
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* One or both of ``index`` and ``columns`` | ||
* ``labels`` and ``axis`` |
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no indentation needed
def _validate_axis_style_args(self, arg, arg_name, index, columns, | ||
axis, method_name): | ||
if axis is not None: | ||
# Using "axis" style, along with a positional arg |
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I suppose it would make it a lot harder if the default axis=0
is used instead of None ?
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Right now I raise on
df.reindex(labels, axis=0)
df.reindex(index=labels, axis=0)
If I change the default axis to 0, then I can't detect those cases. I could go either way here.
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Why do you raise on df.reindex(labels, axis=0)
? That seems perfectly valid?
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It's valid, just the axis=0
is redundant. Likewise with columns=labels, axis=1
(I currently raise). Happy to adjust that though.
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that are two different things; because you can either specify mapper/axis or index/columns.
df.reindex(labels, axis=0)
is a case of mapper/axis, and is thus perfectly valid (and even more explicit than leaving out axis=0, although it is the default, so I don't think we should raise on this), while df.reindex(columns=labels, axis=1)
is mixture of columns and axis, so OK to raise on that.
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df.reindex(index=labels, axis=0)
is a bit the tricky case, as this one is indeed redundant and mixing the two. So in principle I would also raise here like for df.reindex(columns=labels, axis=1)
.
But if it is easier implementation-wise to allow that, I think that is OK (as although it is mixing both idioms, it is consistent in which axis compared to eg df.reindex(index=labels, axis=1)
.
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Sorry, #17800 (comment) was incorrect. .reindex(labels, axis=0)
should clearly work!
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I do raise on the "mixing" case, so I think we agree on what should happen? And I think the current implementation does that. I'll ensure there are tests for all this.
In [1]: import pandas as pd
d
In [2]: df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
In [3]: df.reindex([0, 1], axis=0)
Out[3]:
A B
0 1 4
1 2 5
In [4]: df.reindex(index=[0, 1], axis=0)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-4-d6f30fd70cc7> in <module>()
----> 1 df.reindex(index=[0, 1], axis=0)
~/Envs/pandas-dev/lib/python3.6/site-packages/pandas/pandas/core/frame.py in reindex(self, labels, index, columns, axis, **kwargs)
2945 index, columns = self._validate_axis_style_args(labels, 'labels',
2946 index, columns,
-> 2947 axis, 'reindex')
2948 return super(DataFrame, self).reindex(index=index, columns=columns,
2949 **kwargs)
~/Envs/pandas-dev/lib/python3.6/site-packages/pandas/pandas/core/frame.py in _validate_axis_style_args(self, arg, arg_name, index, columns, axis, method_name)
2788 "\t.{method_name}.rename(index=index, columns=columns)"
2789 ).format(arg_name=arg_name, method_name=method_name)
-> 2790 raise TypeError(msg)
2791 if axis == 'index':
2792 index = arg
TypeError: Can't specify both 'axis' and 'index' or 'columns'. Specify either
.reindex.rename(labels, axis=axis), or
.reindex.rename(index=index, columns=columns)
In [5]: df.reindex(columns=[0, 1], axis=1)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-02a868f92f79> in <module>()
----> 1 df.reindex(columns=[0, 1], axis=1)
~/Envs/pandas-dev/lib/python3.6/site-packages/pandas/pandas/core/frame.py in reindex(self, labels, index, columns, axis, **kwargs)
2945 index, columns = self._validate_axis_style_args(labels, 'labels',
2946 index, columns,
-> 2947 axis, 'reindex')
2948 return super(DataFrame, self).reindex(index=index, columns=columns,
2949 **kwargs)
~/Envs/pandas-dev/lib/python3.6/site-packages/pandas/pandas/core/frame.py in _validate_axis_style_args(self, arg, arg_name, index, columns, axis, method_name)
2788 "\t.{method_name}.rename(index=index, columns=columns)"
2789 ).format(arg_name=arg_name, method_name=method_name)
-> 2790 raise TypeError(msg)
2791 if axis == 'index':
2792 index = arg
TypeError: Can't specify both 'axis' and 'index' or 'columns'. Specify either
.reindex.rename(labels, axis=axis), or
.reindex.rename(index=index, columns=columns)
doc/source/whatsnew/v0.21.0.txt
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@@ -109,6 +109,33 @@ For example: | |||
# the following is now equivalent | |||
df.drop(columns=['B', 'C']) | |||
|
|||
``rename``, ``reindex`` now also accepts axis keyword |
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add a ref tag
doc/source/whatsnew/v0.21.0.txt
Outdated
@@ -109,6 +109,33 @@ For example: | |||
# the following is now equivalent | |||
df.drop(columns=['B', 'C']) | |||
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``rename``, ``reindex`` now also accepts axis keyword | |||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | |||
|
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needs to be same length as the title (hard to tell)
doc/source/whatsnew/v0.21.0.txt
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.. ipython:: | ||
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df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) | ||
df.rename(str.lower, axis='columns') |
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maybe show both usages?
raise TypeError(msg) | ||
|
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elif _all_not_none(arg, index): | ||
# This is the "ambiguous" case, so emit a warning |
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maybe worth factoring this function out if its common with the drop changes? not sure
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maybe put in pandas/util/_validators.py with all other arg validation code
@@ -837,6 +837,107 @@ def test_rename_objects(self): | |||
assert 'FOO' in renamed | |||
assert 'foo' not in renamed | |||
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def test_rename_columns(self): | |||
df = pd.DataFrame({"A": [1, 2], "B": [1, 2]}, index=['X', 'Y']) |
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issue number
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some minor doc-comments, otherwise lgtm.
doc/source/whatsnew/v0.21.0.txt
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And ``reindex``: | ||
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.. ipython:: |
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maybe add some docs where these are using (in basics.rst), or a link to here?
@@ -802,12 +805,27 @@ def swaplevel(self, i=-2, j=-1, axis=0): | |||
0 1 4 | |||
1 2 5 | |||
2 3 6 | |||
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Using axis-style parameters |
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are you showing examples of both? maybe put your highly recommended warning here?
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Yep, added.
@@ -2825,6 +2849,26 @@ def sort_index(self, axis=0, level=None, ascending=True, inplace=False, | |||
IE10 404 0.08 | |||
Chrome 200 0.02 | |||
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We can also reindex the columns. |
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same add the warning?
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Added above.
Got all the doc comments addressed I think. I haven't had time to clean up the implementation to either refactor the changes to |
@TomAugspurger ping when ready to have a look |
I think it's ready. I still haven't had time to refactor the implementation, and probably won't have time before the RC. |
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Some minor comments/
There are two cases that currently do not fail:
In [9]: df.rename(index=id, axis=0)
Out[9]:
A B
139753784065696 1 4
139753784065728 2 5
139753784065760 3 6
In [10]: df.rename(columns=id, axis=0)
Out[10]:
139753756957136 139753785070512
0 1 4
1 2 5
2 3 6
But since axis=0
is the default we cannot detect this I suppose? (and I asked myself to make axis=0
the default instead of axis=None
:-)). In that case, I prefer keeping the default axis and not raising for those above.
(so as it is now :-))
doc/source/whatsnew/v0.21.0.txt
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The :meth:`DataFrame.rename` and :meth:`DataFrame.reindex` methods have gained | ||
the ``axis`` keyword to specify the axis to target with the operation. This | ||
harmonizes the method signature of these methods with most of the rest of the | ||
library (:issue:`12392`). |
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I personally wouldn't add the "harmonizes the method signature of these methods with most of the rest of the library " (but that's more personal preference maybe :-) as I said in the issue, IMO it is not comparable with many other functions that use axis as arg, as it is a different use case, it does make it consistent with drop
though, so I would mention that (which also makes it more match with the whatsnew entry about drop above))
doc/source/whatsnew/v0.21.0.txt
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.. ipython:: python | ||
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df.rename(index=id, columns=str.lower) | ||
|
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maybe add df.reindex(index=[0, 1, 3], columns=['A', 'B', 'C'])
as well? to make it clear that it is not only rename
but also reindex
that keeps the old way
@@ -742,11 +742,13 @@ def swaplevel(self, i=-2, j=-1, axis=0): | |||
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Parameters | |||
---------- | |||
%(optional_mapper)s | |||
%(axes)s : scalar, list-like, dict-like or function, optional | |||
Scalar or list-like will alter the ``Series.name`` attribute, |
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I personally would also create separate docstrings for the series/dataframe versions of those methods. It will give a bit of duplication, but it will be much easier and take less time to make sure this duplication is done correctly than trying to figure out how to make it work with the docstring substitution.
But agree that can be in another PR.
pandas/core/frame.py
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warnings.warn(msg, stacklevel=3) | ||
index, columns = arg, index | ||
elif index is None: | ||
index = arg |
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This is for the default (labels, axis=0) case ? (if so, maybe good to add a comment)
with tm.assert_raises_regex(TypeError, None): | ||
df.rename(str.lower, str.lower, str.lower) | ||
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def test_drop_api_equivalence(self): |
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this one already existed, and I don't see it removed somewhere else in the diff (if you would have moved it from another file). So maybe this was duplicated by accident?
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Oh, I messed up when I brought in your tests.
pandas/core/frame.py
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@@ -2891,7 +2940,11 @@ def align(self, other, join='outer', axis=None, level=None, copy=True, | |||
broadcast_axis=broadcast_axis) | |||
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@Appender(_shared_docs['reindex'] % _shared_doc_kwargs) | |||
def reindex(self, index=None, columns=None, **kwargs): | |||
def reindex(self, labels=None, index=None, columns=None, axis=0, |
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it might be easier to simply default axis=None
, then in the code if you can set it to 0 where appropriate. This way you can detect whether its set.
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This messes with the default displayed in the method signature though (I believe that was @jorisvandenbossche's reason for wanting axis=0
as the default?).
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Yeah, I am not too fixed on it. It is just a trade-off between having a more informative function signature (having the actual default value) vs being able to raise an error in the corner case of the user specifying df.reindex/rename(columns=.., axis=0)
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oh, you have to give that up. We don't do this anywhere else. Sure if you can preserve it would be great, but generally wouldn't work too hard.
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when I mean we don't do this anywhere else is that when we need to change an arg to see if we need to deprcate it, it should simply be None
. this case is a little different so it may be possible to preserve it.
Fixups:
|
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Some doc comments
pandas/core/frame.py
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---------- | ||
mapper : dict-like or function, optional | ||
Applied to the axis specified by ``axis`` | ||
index, columns : scalar, list-like, dict-like or function, optional |
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'scalar' is not correct anymore ? (as this is only for series)
also list-like is here and not for mapper
. Although I am not sure when you actually can use a list-like
BTW, since the type and explanation of both mapper and index/columns are the same, we could also combine all three of them like now index, columns are combined.
Then inside the description can explain that either axis needs to be specified or either index/columns can be used.
pandas/core/frame.py
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|
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See Also | ||
-------- | ||
pandas.NDFrame.rename_axis |
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NDFrame -> DataFrame
pandas/core/series.py
Outdated
def rename(self, index=None, **kwargs): | ||
"""Alter Series row labels or name |
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'row labels' -> 'index labels' ? (only a suggestion)
pandas/core/series.py
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|
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Parameters | ||
---------- | ||
index : scalar, list-like, dict-like or function, optional |
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Same here as before, I am not sure about the 'list-like'. I tried a few cases and it just errors. When looking at the code, list-likes seem to take the "changing Series.name" route, but names need to be hashable. So a tuple works, but not a list.
pandas/core/series.py
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See Also | ||
-------- | ||
pandas.DataFrame.rename_axis |
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DataFrame -> Series
lgtm merge when ready (rebase) |
de8db68
to
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@TomAugspurger Thanks a lot for finishing this! Any opinion on #17833 ? |
* API: Added axis argument to rename xref: pandas-dev#12392 * API: Accept 'axis' keyword argument for reindex
One backwards-incompatible change that I didn't consider, using In [8]: df = pd.DataFrame(columns=['A', 'B'])
In [10]: df.rename(None, str.lower)
Out[10]:
Empty DataFrame
Columns: [A, B]
Index: [] In previous versions that meant |
* API: Added axis argument to rename xref: pandas-dev#12392 * API: Accept 'axis' keyword argument for reindex
* API: Added axis argument to rename xref: pandas-dev#12392 * API: Accept 'axis' keyword argument for reindex
xref: #12392
I want to test this a bit further and clean up the code for a bit, but figured I'd put this up as I'm going offline for a few hours.
Any comments on the general approach of adding
*args
, and then manually validating that the parameters are consistent?