Pandas: matching a string in series with string from another series

Question

I have a DataFrame that looks like this:

Full                          Partial
ABCDEFGHIJKLMNOPQRSTUVWXYZ    FGHIJKL
ANLHDFKNADHFBAKHFGBAKJFB      FKNADH
JABFKADFNADKHFBADHBFJDHFBADF  ABFKA

What I want to do is to put everything from Full that does NOT match Partial in lowercase, yielding the following:

Coverage
abcdef_GHIJKL_mnopqrstuvwxyz
anlhd_FKNADH_fbakhfgbakjfb
j_ABFKA_dfnadkhfbadhbfjdhfbadf

How would I do this? I looked around and it seems that series.str.extract() could be a solution, but I'm not certain as when I try to do this:

df['Full'].str.extract(data['Partial'])

... it only says that Series can't be hashable. I assume that extract only takes a single argument, rather than a Series? Is there any way to bypass this? Is extract even the correct way to achieve what I'm looking for, or is there another way? I'm thinking I could perhaps find som way to extract the string indexes and do the following pseudocode:

df['Coverage'] = data['Full'][:start].lower() + '_' + data['Partial'] + \
     '_' + data['Full'][End:].lower()

... where Start and End is the indexes for where data['Partial'] starts and ends, respectively. Thoughts?

Answer 1

Not the most elegant perhaps, but here is one solution:

For df:

                           Full  Partial
0    ABCDEFGHIJKLMNOPQRSTUVWXYZ  FGHIJKL
1      ANLHDFKNADHFBAKHFGBAKJFB   FKNADH
2  JABFKADFNADKHFBADHBFJDHFBADF    ABFKA

This:

df.apply(lambda r: r.Full.lower().replace(r.Partial.lower(), '_' + r.Partial + '_'), axis=1)

Returns:

0      abcde_FGHIJKL_mnopqrstuvwxyz
1        anlhd_FKNADH_fbakhfgbakjfb
2    j_ABFKA_dfnadkhfbadhbfjdhfbadf

For each row, you convert the full string to lowercase, and replace the 'partial string to lower' with the original partial string with two underscores added on both sides.