Merge multiple column values into one column in python pandas

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.

I propose to use .assign

df2 = df.assign(ColumnA = df.Column2.astype(str) + ', ' + \
  df.Column3.astype(str) + ', ' df.Column4.astype(str) + ', ' \
  df.Column4.astype(str) + ', ' df.Column5.astype(str))

it's simple, maybe long but it worked for me