Pandas Series to Numpy ndarray

Question

I have a dataframe similar to this (but much larger).

>>> df = pd.DataFrame([ [ 'a', np.array([ 1, 2]) ], [ 'b', np.array([ 3, 4 ]) ] ])
   0       1
0  a  [1, 2]
1  b  [3, 4]

The last column has the shape listed as...

>>> df[1].shape
(2,)

I'd like it to be listed as (2,2). I was able to do this via the following line, but the performance of tolist() is... bad.

>>> np.array(df[1].tolist()).shape
(2, 2)

It could also be a Pandas dataframe as long as it correctly reports the shape. Any other suggestions?

Answer 1

This is not possible!

Pandas keeps each Series as a single dimensional ndarray. If you have multiple dimensions that you are trying to squeeze into it, Pandas will force this to be a single dimensional array with dtype of object.

If you simply want to get the contents and make it into a 2 dimensional array then I'd suggest

np.array(df[1].values.tolist())

Otherwise, I'd suggest you keep them in two different columns.