python pandas: rename single column label in multi-index dataframe

Question

I have a df that looks like this:

df = pd.DataFrame(np.random.random((4,4)))
df.columns = pd.MultiIndex.from_product([['1','2'],['A','B']])
print df
          1                   2          
          A         B         A         B
0  0.030626  0.494912  0.364742  0.320088
1  0.178368  0.857469  0.628677  0.705226
2  0.886296  0.833130  0.495135  0.246427
3  0.391352  0.128498  0.162211  0.011254

How can I rename column '1' and '2' as 'One' and 'Two'?

I thought df.rename() would've helped but it doesn't. Have no idea how to do this?

In newer versions of pandas, `df.rename()` can be used to rename particular levels. See [kadee's](https://stackoverflow.com/a/50348947/3388962) answer below. — normanius, Nov 25 '20 at 18:42

score 25 · Accepted Answer · answered Mar 31 '15 at 13:24

That is indeed something missing in rename (ideally it should let you specify the level).
Another way is by setting the levels of the columns index, but then you need to know all values for that level:

In [41]: df.columns.levels[0]
Out[41]: Index([u'1', u'2'], dtype='object')

In [43]: df.columns = df.columns.set_levels(['one', 'two'], level=0)

In [44]: df
Out[44]:
        one                 two
          A         B         A         B
0  0.899686  0.466577  0.867268  0.064329
1  0.162480  0.455039  0.736870  0.759595
2  0.620960  0.922119  0.060141  0.669997
3  0.871107  0.043799  0.080080  0.577421

In [45]: df.columns.levels[0]
Out[45]: Index([u'one', u'two'], dtype='object')

kadee · Answer 2 · 2018-05-15T11:31:31.200

As of pandas 0.22.0 (and probably much earlier), you can specify the level:

df = df.rename(columns={'1': one, '2': two}, level=0)

or, alternatively (new notation since pandas 0.21.0):

df = df.rename({'1': one, '2': two}, axis='columns', level=0)

But actually, it works even when omitting the level:

df = df.rename(columns={'1': one, '2': two})

In that case, all column levels are checked for occurrences to be renamed.

score 5 · Answer 3 · answered Mar 31 '15 at 13:24

5

Use set_levels:

>>> df.columns.set_levels(['one','two'], 0, inplace=True)
>>> print(df)
        one                 two          
          A         B         A         B
0  0.731851  0.489611  0.636441  0.774818
1  0.996034  0.298914  0.377097  0.404644
2  0.217106  0.808459  0.588594  0.009408
3  0.851270  0.799914  0.328863  0.009914

answered Mar 31 '15 at 13:24

TheBlackCat

9,791
3
24
31

Thanks for the effort! – Boosted_d16 Mar 31 '15 at 13:56

score 4 · Answer 4 · answered Mar 31 '15 at 13:24

4

df.columns.set_levels(['one', 'two'], level=0, inplace=True)

answered Mar 31 '15 at 13:24

Cristián Antuña

871
4
15

Thanks for the effort! – Boosted_d16 Mar 31 '15 at 13:56

score 4 · Answer 5 · answered Nov 03 '16 at 19:58

4

df.rename_axis({'1':'one', '2':'two'}, axis='columns', inplace=True)

answered Nov 03 '16 at 19:58

amn34

76
1

score 0 · Answer 6 · answered Jun 14 '16 at 15:22

This is a good question. Combining the answer above, you can write a function:

def rename_col( df, columns, level = 0 ):

    def rename_apply ( x, rename_dict ):
        try:
            return rename_dict[x]
        except KeyError:
            return x

    if  isinstance(df.columns, pd.core.index.MultiIndex):
        df.columns = df.columns.set_levels([rename_apply(x, rename_dict = columns ) for x in df.columns.levels[level]], level= level)
    else:
        df.columns =                       [rename_apply(x, rename_dict = columns ) for x in df.columns              ] 

    return df

It worked for me.

Ideally, a functionality like this should be integrated into the "official" "rename" function in the future, so you don't need to write a hack like this.

python pandas: rename single column label in multi-index dataframe

6 Answers6