python - How to remove nan value while combining two column in Panda Data frame?

Question

I am trying but not able to remove nan while combining two columns of a DataFrame.

Data is like:

feedback_id                  _id
568a8c25cac4991645c287ac     nan    
568df45b177e30c6487d3603     nan    
nan                          568df434832b090048f34974       
nan                          568cd22e9e82dfc166d7dff1   
568df3f0832b090048f34711     nan
nan                          568e5a38b4a797c664143dda   

I want:

feedback_request_id
568a8c25cac4991645c287ac
568df45b177e30c6487d3603
568df434832b090048f34974
568cd22e9e82dfc166d7dff1
568df3f0832b090048f34711
568e5a38b4a797c664143dda

Here is my code:

df3['feedback_request_id'] = ('' if df3['_id'].empty else df3['_id'].map(str)) + ('' if df3['feedback_id'].empty else df3['feedback_id'].map(str))

Output I'm getting:

feedback_request_id
568a8c25cac4991645c287acnan
568df45b177e30c6487d3603nan
nan568df434832b090048f34974
nan568cd22e9e82dfc166d7dff1
568df3f0832b090048f34711nan
nan568e5a38b4a797c664143dda

I have tried this, also:

df3['feedback_request_id'] = ('' if df3['_id']=='nan' else df3['_id'].map(str)) + ('' if df3['feedback_id']=='nan' else df3['feedback_id'].map(str))

But it's giving the error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

question from:https://stackoverflow.com/questions/34989341/how-to-remove-nan-value-while-combining-two-column-in-panda-data-frame

Answer 1

You can use combine_first or fillna:

print df['feedback_id'].combine_first(df['_id'])
0    568a8c25cac4991645c287ac
1    568df45b177e30c6487d3603
2    568df434832b090048f34974
3    568cd22e9e82dfc166d7dff1
4    568df3f0832b090048f34711
5    568e5a38b4a797c664143dda
Name: feedback_id, dtype: object

print df['feedback_id'].fillna(df['_id'])
0    568a8c25cac4991645c287ac
1    568df45b177e30c6487d3603
2    568df434832b090048f34974
3    568cd22e9e82dfc166d7dff1
4    568df3f0832b090048f34711
5    568e5a38b4a797c664143dda
Name: feedback_id, dtype: object