Pandas: Add column to DataFrame based on Series values

Question

I performed a groupby which gives me a pd.Series object. Something like this:

import pandas as pd
spanish = pd.Series(['uno', 'dos', 'tres'], ['one', 'two', 'three'])
>>> spanish
    one       uno
    two       dos
    three    tres
    dtype: object

I have my original pd.DataFrame containing one column who's indices match with the pd.Series:

df = pd.DataFrame({'german': ['eins', 'zwei', 'drei'],
                   'english': ['one', 'two', 'three']},
                  index=[1, 2, 3])
>>> df
      german english
    1   eins     one
    2   zwei     two
    3   drei   three

As can be seen above, the english column matches with the indices from the spanish series. I now want to add the spanish values to df. In other words, I want to get this:

>>> df
      german english spanish
    1   eins     one     uno
    2   zwei     two     dos
    3   drei   three    tres

Note: I tried to use loc to assign spanish[df['english'][i]] when iterating, but this process is extremely slow (my real DataFrame has around 6 million entries). Furthermore, I can't use groupby.transform() because I'm grouping on another DataFrame. Lastly, I can't use indices (0, 1, 2) because they don't match either.

Thanks in advance.