API: allow DataFrame.rename to take a list-like of colums

[chris-b1]

This is closely related to #12392, but I think separate issue. Proposal would be to be able to pass a list-like to DataFrame.rename to make method-chaining easier. I think it would also be consistent with #11980 (Series rename)

df = pd.DataFrame({'a': [1,2], 'b': [3, 4]})

# make this
df = df.rename(columns=['j', 'k'])

# equivalent to 
df.columns = ['j', 'k']

[jreback]

note that Series.rename is affecting the .name and NOT an index. So though I like that this works like .set_index it might be a bit of an odd duck.

[chris-b1]

Yeah, it's a bit odd - I actually could make [5] below work - but at best confusing next to [4]

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

In [2]: s
Out[2]: 
0    a
1    b
dtype: object

In [3]: s.rename('my_series')
Out[3]: 
0    a
1    b
Name: my_series, dtype: object

In [4]: s.rename((1,2))
Out[4]: 
0    a
1    b
Name: (1, 2), dtype: object

In [5]: s.rename([1,2])
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
TypeError: Series.name must be a hashable type

[jorisvandenbossche]

There is also the idea to call this relabel (I thought there was an issue about this, but it is mentioned here: #12392 (comment), #11980 (comment)).
If we do this, this makes it possible to more easily expand the possibilities here without conflicting with the series name renaming case.

[chris-b1]

Thanks @jorisvandenbossche - although I'm a little wary of adding another DataFrame method, I am in favor of calling this relabel vs adding functionality to rename

[jorisvandenbossche]

although I'm a little wary of adding another DataFrame method

fully agree, but the double use case of rename is also not nice ..

[TomAugspurger]

From @toobaz in #16990 (comment):

My proposal is the following:

• add a new method .relabel, which changes the content of the axis, as in

df.relabel(['l1', 'l2', 'l3']) # changes df.index labels - assuming df.index is flat
df.relabel([['l1a', 'l1b', 'l1c'], [...], [...]]) # changes df.index labels - assuming df.index has 3 levels
df.relabel(a_dict) # again, changes the index labels, analogously to what df.rename(a_dict) currently does

• deprecate the use of .rename and .rename_index for doing the same operation, that is when the index or mapper argument (respectively) is a callable or dict-like; keep them (or, even better, keep one and deprecate the other) for changing only index names

I would add that df.relabel would also take a function mapping old index labels to new.

[TomAugspurger]

Could we do an up / down vote on:

a. Adding .relabel method for changing the index / column labels
b. Deprecating the relabeling behavior of .rename

I'm +1 on a and -0 on b.

[jreback]

.set_axis does the job with the new signature. (#16994)

So I would be ok with

• use this new impl .set_axis as .relabel and deprecate .set_axis
• remove .rename/.rename_axis relableing behavior (b)

[jreback]

another possibility is .relabel_index, slightly longer but in the same vein as .set_index so maybe more clear