Highlight distinct cells based on a different cell in the same row in a multiindex pivot table

Question

I have created a pivot table where the column headers have several levels. This is a simplified version:

index = ['Person 1', 'Person 2', 'Person 3']
columns = [
    ["condition 1", "condition 1", "condition 1", "condition 2", "condition 2", "condition 2"],
    ["Mean", "SD", "n", "Mean", "SD", "n"],
]
data = [
    [100, 10, 3, 200, 12, 5],
    [500, 20, 4, 750, 6, 6],
    [1000, 30, 5, None, None, None],
]
df = pd.DataFrame(data, columns=columns)

df

Now I would like to highlight the adjacent cells next to SD if SD > 10. This is how it should look like:

I found this answer but couldn't make it work for multiindices.

Thanks for any help.

Answer 1

Use Styler.apply with custom function - for select column use DataFrame.xs and for repeat boolean use DataFrame.reindex:

def hightlight(x):
    c1 = 'background-color: red'

    mask = x.xs('SD', axis=1, level=1).gt(10)
    #DataFrame with same index and columns names as original filled empty strings
    df1 = pd.DataFrame('', index=x.index, columns=x.columns)
    #modify values of df1 column by boolean mask
    return df1.mask(mask.reindex(x.columns, level=0, axis=1), c1)

df.style.apply(hightlight, axis=None)