Pandas style function to highlight specific columns

Question

I have been trying to write a function to use with pandas style. I want to highlight specific columns that I specify in the arguments. This is not very elegant, but for example:

data =  pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))

def highlight_cols(df, cols, colcolor = 'gray'):
    for col in cols:
        for dfcol in df.columns:
            if col == cols:
                color = colcolor
    return ['background-color: %s' % color]*df.shape[0]

then call with:

data.style.apply(highlight_cols(cols=['B','C']))

I get an error: 'Series' object has no attribute 'columns'

I think I fundamentally don't quite understand how the styler calls and applyies the function.

Answer 1

I think you can use Slicing in Styles for select columns B and C and then Styler.applymap for elementwise styles.

import pandas as pd
import numpy as np

data =  pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
#print (data)

def highlight_cols(s):
    color = 'grey'
    return 'background-color: %s' % color

data.style.applymap(highlight_cols, subset=pd.IndexSlice[:, ['B', 'C']])

If you want more colors or be more flexible, use Styler.apply(func, axis=None), the function must return a DataFrame with the same index and column labels:

import pandas as pd
import numpy as np

data =  pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
#print (data)

def highlight_cols(x):
    #copy df to new - original data are not changed
    df = x.copy()
    #select all values to default value - red color
    df.loc[:,:] = 'background-color: red'
    #overwrite values grey color
    df[['B','C']] = 'background-color: grey'
    #return color df
    return df    

data.style.apply(highlight_cols, axis=None)