Selecting specific rows of numpy.ndarray containing numpy.ndarrays of different size

Question

I have a numpy.ndarray containing numpy.ndarray's of different size and i want to extract some rows where the first number of each of these rows are in a certain list.

Example:

>>>a
array([array([1]), array([2, 3]), array([3, 1, 1]), array([2, 3, 3, 4])], dtype=object)

>>> idx
[2]

I need:

>>>a
array([array([2, 3]), array([2, 3, 3, 4])], dtype=object)

So i want only the rows (or arrays) of a which have a 2 as the first number. Is there a simple and nice way to do so like in this post here?

hpaulj · Accepted Answer · 2018-11-03 17:06:09Z

2

An object dtype array like this is more like a list of lists than a 2d array. a actually has pointers to the element arrays, just a list would.

In [517]: a=array([array([1]), array([2, 3]), array([3, 1, 1]), array([2, 3, 3, 4])], dtype=object)
In [518]: a
Out[518]: 
array([array([1]), array([2, 3]), array([3, 1, 1]), array([2, 3, 3, 4])],
      dtype=object)

A straightforward way of selecting the elements of a that match this criteria is to use a list comprehension:

In [519]: [row for row in a if row[0]==2]
Out[519]: [array([2, 3]), array([2, 3, 3, 4])]

Almost all operations on an object dtype array like this involve a list iteration like this.

answered Nov 3, 2018 at 17:06

hpaulj

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