CODEWITHSUNDEEP
pythonpandasdataframe
moys
moys

Reputation: 8033

How to apply conditional color styling to a column in a Multi-index pandas dataframe

I already had a question answered for conditionally applying color with a normal Dataframe. Link

The question I have is how do I do that with a multi-index data-frame? The dataframe in the previous question was

Value       Limit    Actual
Issues      < 33     0
Rating      > 4      4.2
Complaints  < 15     18
Time        30 - 45  41
Tip         --       -

The new dataframe is the same dataframe but with header like below

df.columns =pd.MultiIndex.from_product([['summary'], df.columns])
df

So the new dataframe is like so

Summary
Value       Limit    Actual
Issues      < 33     0
Rating      > 4      4.2
Complaints  < 15     18
Time        30 - 45  41
Tip         --       -

The out put expected is like the previous question itself but with a additional header row at the top.

enter image description here

I tried replacing row['Limit'] with x.loc[:,idx[:,'Limit']] where idx is pd.IndexSlice but it did not work

import re

def highlight(row):
    numbers = re.findall('[0-9]+', row['Limit'])
    if row['Value'] in ('Issues','Rating','Complaints'):
        if '>' in row['Limit'] and row['Actual'] > numbers[0]:
            color = 'green'
        elif row['Actual'] < numbers[0]:
            color = 'green'
        else:
            color = 'red'
    else:
        if len(numbers) == 0:
            color = 'yellow'
        elif row['Actual'] > numbers[0] and row['Actual'] < numbers[1]:
            color = 'green'
        else:
            color = 'red'
    return f"background-color: {color}"

Upvotes: 1

Views: 346

Answers (1)

jezrael
jezrael

Reputation: 863501

You need change:

row['Limit']

to:

row[('summary', 'Limit')]

for select by MultiIndex in columns.

EDIT:

If use:

row[(slice(None),'Limit')]
row[idx[:,'Actual']]

output is one element Series.

So need select first value in this methods for scalar:

row[(slice(None),'Limit')].iat[0]
row[idx[:,'Actual']].iat[0]

Upvotes: 1

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