How to initialize Numpy array of list objects

Question

I'm trying to create a numpy array that looks like

array([[list([]), list([])],
       [list([]), list([])],
       [list([]), list([])]], dtype=object)

This array has shape (3,2). However, whenever I do

np.array([[list(), list()], [list(), list()], [list(), list()]])

I end up getting

array([], shape=(3, 2, 0), dtype=float64)

How do I solve this?

It is very likely that you do not want a numpy array of lists. — rafaelc
– rafaelc, Commented Aug 5, 2019 at 20:10
np.array tries to create multidimensional numeric (or string) array, which it can do if all the input lists have a consistent size. It's only when the sizes differ that it falls back on creating an object dtype array (or in some cases raising an error). — hpaulj
– hpaulj, Commented Aug 5, 2019 at 20:17

hilberts_drinking_problem · Accepted Answer · 2019-08-05 18:48:30Z

9

You could use the following:

np.frompyfunc(list, 0, 1)(np.empty((3,2), dtype=object))

We first turn list into a ufunc that takes no arguments and returns a single empty list, then apply it to an empty 3x2 array of object type.

answered Aug 5, 2019 at 18:48

hilberts_drinking_problem

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1 Comment

hpaulj Over a year ago

I've recommended frompyfunc as a way of filling an array with custom class instances. This is a nice use of the idea with standard types like list.

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