Highlight Pandas DataFrame's specific columns using apply()

# importing pandas as pd 
import pandas as pd 

# creating the dataframe
df = pd.DataFrame({"A" : [14, 4, 5, 4, 1],
                   "B" : [5, 2, 54, 3, 2],
                   "C" : [20, 20, 7, 3, 8], 
                   "D" : [14, 3, 6, 2, 6],
                   "E" : [23, 45, 64, 32, 23]}) 

print("Original DataFrame :")
display(df)

# function definition
def highlight_cols(x):
    
    # copy df to new - original data is not changed
    df = x.copy()
    
    # select all values to green color
    df.loc[:, :] = 'background-color: green'
    
    # overwrite values grey color
    df[['B', 'C', 'E']] = 'background-color: grey'
    
    # return color df
    return df 

print("Highlighted DataFrame :")
display(df.style.apply(highlight_cols, axis = None))

# importing pandas as pd 
import pandas as pd 

# creating the dataframe
df = pd.DataFrame({"Name" : ["Yash", "Ankit", "Rao"],
                   "Age" : [5, 2, 54]}) 

print("Original DataFrame :")
display(df)

# function definition
def highlight_cols(x):
    
    # copy df to new - original data is not changed
    df = x.copy()
    
    # select all values to yellow color
    df.loc[:, :] = 'background-color: yellow'
    
    # return color df
    return df 

print("Highlighted DataFrame :")
display(df.style.apply(highlight_cols, axis = None))