Merge Disjoint Columns in Pandas

Question

I have a pretty simple Pandas question that deals with merging two series. I have two series in a dataframe together that are similar to this:

     Column1     Column2
0        Abc         NaN
1        NaN         Abc
2        Abc         NaN
3        NaN         Abc
4        NaN         Abc

The answer will probably end up being a really simple .merge() or .concat() command, but I'm trying to get a result like this:

     Column1
0        Abc
1        Abc
2        Abc
3        Abc
4        Abc

The idea is that for each row, there is a string of data in either Column1, Column2, but never both. I did about 10 minutes of looking for answers on StackOverflow as well as Google, but I couldn't find a similar question that cleanly applied to what I was looking to do.

I realize that a lot of this question just stems from my ignorance on the three functions that Pandas has to stick series and dataframes together. Any help is very much appreciated. Thank you!

Possible duplicate of https://stackoverflow.com/questions/34989341/how-to-remove-nan-value-while-combining-two-column-in-panda-data-frame — Sumit S Chawla, Jun 27 '18 at 15:12

score 2 · Accepted Answer · edited Jun 27 '18 at 15:12

2

You can just use pd.Series.fillna:

df['Column1'] = df['Column1'].fillna(df['Column2'])

Merge or concat are not appropriate here; they are used primarily for combining dataframes or series based on labels.

Use groupby with first

df.groupby(df.columns.str[:-1],axis=1).first()
Out[294]: 
  Column
0    Abc
1    Abc
2    Abc
3    Abc
4    Abc

Or :

`ndf = pd.DataFrame({'Column1':df.fillna('').sum(1)})`

edited Jun 27 '18 at 15:12

Bharath M Shetty

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answered Jun 27 '18 at 15:10

jpp

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That worked perfectly! Thanks so much-- It says I have to wait 10 minutes to mark it as a correct answer. I'll do that shortly. – Matt Youngberg Jun 27 '18 at 15:12

Merge Disjoint Columns in Pandas

1 Answers1