Pandas Inner Join with Lambda

Question

I have the following two frames:

frame1:

            id
0  111-111-111
1  111-111-222
2  222-222-222
3  333-333-333

frame2:

     data       id
0    ones  111-111
1  threes  333-333

And, I have a lambda function that maps the frame1.id to frame2.id :

id_map = lambda x: x[:7]

My goal is to perform an inner join between these two tables, but to have the id go through the lambda. So that the output is:

            id    data
0  111-111-111    ones
1  111-111-222    ones
2  333-333-333  threes

I've come up with a rather non-elegant solution that almost does what I'm trying to do, however it messes up when the inner join removes rows:

# Save a copy the original ids of frame1
frame1_ids = frame1['id'].copy()
# Apply the id change to frame1
frame1['id'] = frame1['id'].apply(id_map)
# Merge
frame1 = frame1.merge(frame2, how='inner', on='id')
# Set the ids back to what they originally were
frame1['id'] = frame1_ids

Is there a elegant solution for this?

Answer 1

Could use assign to create a dummy id column (newid) to join on like this:

frame1.assign(newid=frame1['id'].str[:7])
      .merge(frame2, left_on='newid', right_on='id', suffixes=('','_y'))
      .drop(['id_y','newid'], axis=1)

Output:

            id    data
0  111-111-111    ones
1  111-111-222    ones
2  333-333-333  threes