I have a large numpy array (8 by 30000) and I want to delete some rows according to some criteria. This criteria is only applicable in one column.
Example:
>>> p = np.array([[0, 1, 3], [1 , 5, 6], [4, 3, 56], [1, 34, 4]])
>>> p
array([[ 0, 1, 3],
[ 1, 5, 6],
[ 4, 3, 56],
[ 1, 34, 4]])
here I would like to remove every row in which the value of the 3rd column is >30, ie. here row 3.
As the array is pretty large, I'd like to avoid for loops. I thought of this:
>>> a[~(a>30).any(1), :]
array([[0, 1, 3],
[1, 5, 6]])
But there, it obviously removes the two last rows. Any ideas on how to do that in a efficient way?
