Pandas IndexSlice does not work with pd.style

Question

Given this data format:

In [1]: df = pd.DataFrame(np.random.rand(4,4),
                          index=['A','B','C','All'],
                          columns=[2011,2012,2013,'All']).round(2)
        print(df)
Out[1]:

     2011  2012  2013   All
A    0.94  0.17  0.06  0.64
B    0.49  0.16  0.43  0.64
C    0.16  0.20  0.22  0.37
All  0.94  0.04  0.72  0.18

I am trying to use pd.styleto format data output. One keyword subsetwhere you determine where to apply formatting rules (for example: highlight the maximum). The documentation for pd.style states that it’s better to use pd.IndexSlice:

The value passed in subsetbehaves similarly to slicing a DataFrame.

• A scalar is treated as a column label.
• List (or series or numpy array)
• A tuple is considered as (row_indexer, column_indexer)

Consider using pd.IndexSliceto build a tuple for the latter.

I am trying to understand why in some cases this fails.

, , , , .

IndexSlice :

In [2]: df.ix[pd.IndexSlice[1:-1,:-1]]
Out[2]:
   2011  2012  2013
B  0.49  0.16  0.43
C  0.16  0.20  0.22

style.bar, :

In [3]: df.style.bar(subset=pd.IndexSlice[1:-1,:-1], color='#d65f5f')

TypeError: cannot do slice indexing on <class 'pandas.indexes.base.Index'>
with these indexers [1] of <class 'int'>

, :

In [4]: df.style.bar(subset=pd.IndexSlice[df.index[1:-1],df.columns[:-1]],
                     color='#d65f5f')

, . , pd.IndexSlice, , , - . ​​pd.style ( , 0.17.1).

- , ?

Answer 1

, . , , . doc :

(row_indexer, column_indexer)

, :

In [1]: pd.IndexSlice[1:-1,:-1]
Out[2]: (slice(1, -1, None), slice(None, -1, None))

- :

In [3]: pd.IndexSlice[df.index[1:-1],df.columns[:-1]]
Out[4]: (Index(['B', 'C'], dtype='object'), Index([2011, 2012, 2013], dtype='object'))

, pd.IndexSlice -, . :

df.style.bar(subset=(df.index[1:-1],df.columns[:-1]),
                     color='#d65f5f')