Pandas style object with multi-index

Question

I am formatting a pandas dataframe with styler to highlight columns and format numbers. I also want to apply multi-index for more clear, pleasant and easy to read. Since I apply Styler to subset of columns it does not work work with the multi-index.

Example:

arrays = [np.hstack([['One']*2, ['Two']*2]) , ['A', 'B', 'C', 'D']]
columns = pd.MultiIndex.from_arrays(arrays)
data =  pd.DataFrame(np.random.randn(5, 4), columns=list('ABCD'))
data.columns = columns 
import seaborn as sns
cm = sns.light_palette("green", as_cmap=True)
data.style.background_gradient(cmap=cm, subset=['A'])

Is there a way to subset the columns so the styler can work. According to the below sources this is implemented but there is not examples so it is hard to me to understand how to apply it: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.formats.style.Styler.html https://github.com/pandas-dev/pandas/issues/11655

thank you !

Answer 1

I think you can use pd.IndexSlice[...] method:

data.style.background_gradient(cmap=cm, subset=pd.IndexSlice[:, pd.IndexSlice[:, 'A']])

Demo:

In [5]: data.loc[pd.IndexSlice[:, pd.IndexSlice[:, 'A']]]
Out[5]:
        One
          A
0 -0.808483
1  0.009371
2  0.977138
3 -0.875554
4 -0.052424

In [6]: data
Out[6]:
        One                 Two
          A         B         C         D
0 -0.808483 -2.280683  0.576145  0.649688
1  0.009371  0.721510  1.013764 -0.157493
2  0.977138  1.441392  1.718618 -0.320826
3 -0.875554 -1.060507  1.457075  0.570195
4 -0.052424 -0.742842 -0.203830 -1.202091

in Jupyter:

Answer 2

Here, is another way:

data.style.background_gradient(cmap=cm, subset=data.columns.get_loc_level('A', level=1)[0])

Output: