How to efficiently combine multiple pandas columns into one array-like column?

Question

It is easy to create (or load) a DataFrame with something like an object-typed column, as so:

[In]: pdf = pd.DataFrame({
                     "a": [1, 2, 3], 
                     "b": [4, 5, 6], 
                     "c": [7, 8, 9], 
                     "combined": [[1, 4, 7], [2, 5, 8], [3, 6, 9]]}
      )

[Out]
   a  b  c   combined
0  1  4  7  [1, 4, 7]
1  2  5  8  [2, 5, 8]
2  3  6  9  [3, 6, 9]

I am currently in the position where I have, as separate columns, values that I am required to return as a single column, and need to do so quite efficiently. Is there a fast and efficient way to combine columns into a single object-type column?

In the example above, this would mean already having columns a, b, and c, and I wish to create combined.

I failed to find a similar example of question online, feel free to link if this is a duplicate.

Answer 1

Use DataFrame.agg and pass list as aggregate method, with axis=1, then assign it to a new column

>>> pdf.assign(combined=pdf.agg(list, axis=1))

   a  b  c   combined
0  1  4  7  [1, 4, 7]
1  2  5  8  [2, 5, 8]
2  3  6  9  [3, 6, 9]