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                        


        

Answer 1

For an in-place solution, you can use pd.Series.update with pd.DataFrame.pop:

df['feedback_id'].update(df.pop('_id'))

print(df)

                feedback_id
0  568a8c25cac4991645c287ac
1  568df45b177e30c6487d3603
2  568df434832b090048f34974
3  568cd22e9e82dfc166d7dff1
4  568df3f0832b090048f34711
5  568e5a38b4a797c664143dda

Answer 2

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

Answer 3

If you want a solution that doesn't require referencing df twice or any of its columns explicitly:

df.bfill(axis=1).iloc[:, 0]

With two columns, this will copy non-null values from the right column into the left, then select the left column.