For example, I have a ndarray
that is:
a = np.array([1, 3, 5, 7, 2, 4, 6, 8])
Now I want to split a
into two parts, one is all numbers <5 and the other is all >=5:
[array([1,3,2,4]), array([5,7,6,8])]
Certainly I can traverse a
and create two new array. But I want to know does numpy provide some better ways?
Similarly, for multidimensional array, e.g.
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9],
[2, 4, 7]])
I want to split it according to the first column <3 and >=3, which result is:
[array([[1, 2, 3],
[2, 4, 7]]),
array([[4, 5, 6],
[7, 8, 9]])]
Are there any better ways instead of traverse it? Thanks.
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