conditionally highlighting values in python based on additional columns

Question

I have a dataframe that looks like this:

names=pd.Dataframe({'name': ['ben','adam','steve'],
'name1':['ben1','adam1','steve1'],
'name2':['ben2','adam2','steve2'],
'name3':['ben3','adam3','steve3'],
'name1_comp':[1,0,1],
'name2_comp':[0,1,1],
'name3_comp':[0,1,1]}]

I would like an output of :

names=pd.Dataframe({'name': ['ben','adam','steve'],
'name1':['ben1','adam1','steve1'],
'name2':['ben2','adam2','steve2'],
'name3':['ben3','adam3','steve3']}]

with ben1, adam2, adam3, steve1,steve2,steve3 highlighted. This will be written into excel afterwards.

How would I go about doing this? Thanks

The names you want to be highlighted do not match the boolean table provided (ben3 should not be highlighted, should it?) — jthulhu
– jthulhu, Commented Jun 8, 2022 at 9:18
so, "highlighting" here means the cells should be coloured differently in the exported excel file? — Anentropic
– Anentropic, Commented Jun 8, 2022 at 9:50

mozway · Accepted Answer · 2022-06-08 09:57:33Z

1

You can use:

names2 = names.filter(like='_comp').rename(columns=lambda x: x[:-5])

def hl(df):
    style = 'background-color: yellow'
    return np.where(names2.reindex_like(df).eq(1), style, '')

names.filter(regex=r'(?<!_comp)$').style.apply(hl, axis=None)

output:

For the full DataFrame:

def hl(df):
    style = 'background-color: yellow'
    df2 = df.filter(like='_comp').rename(columns=lambda x: x[:-5]).reindex_like(df)
    return np.where(df2.eq(1), style, '')

names.style.apply(hl, axis=None)

output:

answered Jun 8, 2022 at 9:57

mozway

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7 Comments

aasseeedd Over a year ago

After using your code, I get an error saying that "Function <function hl at 0x7f16c24da550> must return a dataFrame when passed to 'Styler.apply' with axis=None"

mozway Over a year ago

which pandas version do you have? Try: names2.reindex_like(df).eq(1).map({True: style, False: ''})/return df2.eq(1).map({True: style, False: ''})

aasseeedd Over a year ago

I am using python 3 on a jupyter notebook. The fix you suggested doesn't seem to work either.

mozway Over a year ago

I'm talking about the pandas version: pd.__version__

aasseeedd Over a year ago

Oops sorry misread your comment. 1.0.5

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