Pandas fuzzy merge/match name column, with duplicates

Question

I have two dataframes currently, one for donors and one for fundraisers. I\'m trying to find if any fundraisers also gave donations, a

Answer 1

Here's a bit more pythonic (in my view), working (on your example) code, without explicit loops:

def get_donors(row):
    d = donors.apply(lambda x: fuzz.ratio(x['name'], row['name']) * 2 if row['Email'] == x['Email'] else 1, axis=1)
    d = d[d >= 75]
    if len(d) == 0:
        v = ['']*3
    else:
        v = donors.ix[d.idxmax(), ['name','Email','Date']].values
    return pd.Series(v, index=['donor name', 'donor email', 'donor date'])

pd.concat((fundraisers, fundraisers.apply(get_donors, axis=1)), axis=1)

Output:

                 Date           Email        name donor name     donor email           donor date
0 2013-03-27 10:00:00          a@a.ca    John Doe   John Doe          a@a.ca  2013-03-01 10:39:00
1 2013-03-01 10:39:00          a@a.ca    John Doe   John Doe          a@a.ca  2013-03-01 10:39:00
2 2013-03-02 10:39:00          d@d.ca  Kathy test   Kat test          d@d.ca  2013-03-27 10:39:00
3 2013-03-03 10:39:00    asdf@asdf.ca   Tes Ester                                                
4 2013-03-04 10:39:00  something@a.ca    Jane Doe   Jane Doe  something@a.ca  2013-03-04 10:39:00