How to make a multidimension numpy array with a varying row size?

Question

I would like to create a two dimensional numpy array of arrays that has a different number of elements on each row.

Trying

cells = numpy.array([[0,1,2,3], [2,3,4]])

gives an error

ValueError: setting an array element with a sequence.

Answer 1

While Numpy knows about arrays of arbitrary objects, it's optimized for homogeneous arrays of numbers with fixed dimensions. If you really need arrays of arrays, better use a nested list. But depending on the intended use of your data, different data structures might be even better, e.g. a masked array if you have some invalid data points.

If you really want flexible Numpy arrays, use something like this:

numpy.array([[0,1,2,3], [2,3,4]], dtype=object)

However this will create a one-dimensional array that stores references to lists, which means that you will lose most of the benefits of Numpy (vector processing, locality, slicing, etc.).

Answer 2

This isn't well supported in Numpy (by definition, almost everywhere, a "two dimensional array" has all rows of equal length). A Python list of Numpy arrays may be a good solution for you, as this way you'll get the advantages of Numpy where you can use them:

cells = [numpy.array(a) for a in [[0,1,2,3], [2,3,4]])