I have a pandas data frame like this:
Column1 Column2 Column3 Column4 Column5
0 a 1 2 3 4
1 a 3 4
You can call apply pass axis=1 to apply row-wise, then convert the dtype to str and join:
In [153]:
df['ColumnA'] = df[df.columns[1:]].apply(
lambda x: ','.join(x.dropna().astype(str)),
axis=1
)
df
Out[153]:
Column1 Column2 Column3 Column4 Column5 ColumnA
0 a 1 2 3 4 1,2,3,4
1 a 3 4 5 NaN 3,4,5
2 b 6 7 8 NaN 6,7,8
3 c 7 7 NaN NaN 7,7
Here I call dropna to get rid of the NaN, however we need to cast again to int so we don't end up with floats as str.