Highlight row based on boolean column

Question

Have a dataframe for which I've created the boolean column 'Late Submission', where 'True' means it was late and 'False' is on-time.

I want to highlight 'True' rows in red and 'False' in green but I can't seem to get it working as I'm still pretty new to Python. I've tried the code below, any ideas why it's not working?

def highlight_late(s):
    if s['Late Submission'] == True:
        return 'background-color: red'
    elif s['Late Submission'] == False:
        return 'background-color: green'
    
df7.style.apply(highlight_late, axis = 1)

The error given is:

Result has shape: (281556,)
Expected shape:   (281556, 6)

Thanks in advance

Answer 1

I used this simple df to show how it works, based on this pandas doc

import pandas as pd
import numpy as np
df = pd.DataFrame({'a': np.random.randint(0, 10, 10), 'b': np.random.randint(0, 10, 10), 'late': np.random.choice([0, 1], 10).astype(np.bool)})

this gives us:

|    |   a |   b | late   |
|---:|----:|----:|:-------|
|  0 |   3 |   2 | False  |
|  1 |   1 |   0 | False  |
|  2 |   3 |   6 | False  |
|  3 |   0 |   1 | True   |
|  4 |   6 |   7 | True   |
|  5 |   0 |   0 | False  |
|  6 |   0 |   7 | False  |
|  7 |   6 |   4 | True   |
|  8 |   7 |   0 | True   |
|  9 |   7 |   7 | False  |

Now we use a function to apply the style:

def highlight_late(s):
    return ['background-color: red' if s_ else 'background-color: green' for s_ in s]

and then:

df.style.apply(highlight_late, subset=['late'])

results in: