Passing a function with multiple arguments to DataFrame.apply

It's just the way you think it would be, apply accepts args and kwargs and passes them directly to some_func.

df.apply(some_func, var1='DOG', axis=1)

Or,

df.apply(some_func, args=('DOG', ), axis=1)

0    foo-x-DOG
1    bar-y-DOG
dtype: object

You should use vectorized logic:

df['C'] = df['A'] + '-' + df['B'] + '-DOG'

If you really want to use df.apply, which is just a thinly veiled loop, you can simply feed your arguments as additional parameters:

def some_func(row, var1):
    return '{0}-{1}-{2}'.format(row['A'], row['B'], var1)

df['C'] = df.apply(some_func, var1='DOG', axis=1)

As per the docs, df.apply accepts both positional and keyword arguments.

I think it can be

df.apply('-'.join,1)+'-DOG'
Out[157]: 
0    foo-x-DOG
1    bar-y-DOG
dtype: object

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