I want to be able to hide certain rows/columns from my styled Dataframe post-styling.

This is how my dataframe/style object currently looks, and is produced by the below code

data = {
    'site': ['Brighton', 'London', 'Manchester', 'Leicester'],
    'wait_time': [10, 15, 20, 25],
    'wait_time_change_percent': [5, 10, -5, 0],
    'calls': [100, 150, 120, 130],
    'calls_change_percent': [10, -5, 20, 15],
    'complaints': [5, 10, 15, 20],
    'complaints_change_percent': [5, 10, -5, 0]
}

df = pd.DataFrame(data).set_index('site')

def color_change(val):
    color = 'red' if val < 0 else 'green'
    return f'color: {color}'

df_styled = df.style.applymap(lambda val: color_change(val), subset=pd.IndexSlice[:, ['wait_time_change_percent', 'calls_change_percent', 'complaints_change_percent']])

I’ve made this a lot simpler than my actual code just for example purposes so pls don’t ask me to use a different method as there’s a reason I have to remove the columns after the styling and not before 🙂

Now I thought I could use hide() by inserting this line:

df_styled_hidden = df_styled.hide(subset=['wait_time', 'calls', 'complaints'], axis=1)

But when I go to write df_styled_hidden, it just looks exactly the same as my screenshot. Is this a bug with style.hide() or am I just using it incorrectly? Thanks!