Find rows in numpy.array (A) that are not in numpy.array(B)

Asked Apr 23 '20 at 15:09

Active Apr 23 '20 at 15:09

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I am working with two 2D numpy array that have ~20k and ~30k rows. Both A and B have 270 columns. I need to find the rows that are in A but not in B. I used the code below but it is too slow.

B = np.array([x for x in A if x.tolist() not in A.tolist()])

I need a fast version of this line of code. Any thoughts are appreciated!

asked Apr 23 '20 at 15:09

user9439906

Please share a [Minimal, Complete, and Verifiable example](https://stackoverflow.com/help/mcve) – yatu Apr 23 '20 at 15:10
Use the mask off the linked question as `mask` and use it with `A[~mask]`. – Divakar Apr 23 '20 at 15:16

Find rows in numpy.array (A) that are not in numpy.array(B)

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