'Confronting values between dataframe

I'm trying to find a way to confront the equality of values contained into a different dataframes having different column names.

label = {
    'aoo' : ['a', 'b', 'c'],
    'boo' : ['a', 'b', 'c'],
    'coo' : ['a', 'b', 'c']
    'label': ['label', 'label', 'label']
}

unlabel = {
    'unlabel1' : ['a', 'b', 'c'],
    'unlabel2' : ['a', 'b', 'c'],
    'unlabel3': ['a', 'b', 'hhh']

}

label = pd.DataFrame(label)
unlabel = pd.DataFrame(unlabel)

Desired output is a dataframe that contains the column where their values is equal and the column label. Where a single value is not equal unlabel['unlabel3'] i don't want to keep the values in the output.

desired_output = {
    'unlabel1' : ['a', 'b', 'c'],
    'unlabel2' : ['a', 'b', 'c'],
    'label' : ['label', 'label', 'label']
}

If the labels where numbers I could try np.where but I can't find similar helper for string.

Could you help? Thanks

python pandas

Solution 1:^[1]

You can use pd.merge and specify the columns to merge with left_on and right_on

out = unlabel.merge(label, left_on=['unlabel1', 'unlabel2', 'unlabel3'], right_on=['aoo', 'boo', 'coo'], how='left').drop(['unlabel3', 'aoo', 'boo', 'coo'], axis=1)

print(out)

  unlabel1 unlabel2  label
0        a        a  label
1        b        b  label
2        c        c    NaN

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'Confronting values between dataframe

Solution 1:[1]

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Solution 1:^[1]