How to convert values in specific column into integer type under numpy matrix

Question

How can I convert the second column of this matrix into int type inplace?

import numpy as np
x = np.array([[1.23e+02, 2.3], [1.3e+01, 2.9],[1.2e+01, 83.3]])

Desired output:

array([[ 123. ,    2],
       [  13. ,    2],
       [  12. ,   83]])

The best I can come out with is this, but not inlace

x[:,1].astype(int)

You can't change the typing of the array in-place (unless I'm grossly mistaken), but you can floor. — orlp
– orlp, Commented Nov 27, 2015 at 5:44
Only one dtype per array, either all int or all float. (or all object to allow both int and float, but that's idiotic: you'll loose all of numpy numerical performance...) — Julien
– Julien, Commented Nov 27, 2015 at 5:50
Why do you need to convert it, and why does it need to be 'inplace'? — hpaulj
– hpaulj, Commented Nov 27, 2015 at 7:01

orlp · Accepted Answer · 2015-11-27 05:56:01Z

2

You can't change the typing of the array in-place, but you can truncate (or floor if you prefer):

>>> import numpy as np
>>> x = np.array([[1.23e+02, 2.3], [1.3e+01, 2.9],[1.2e+01, 83.3]])
>>> np.trunc(x[:,1], x[:,1])
array([  2.,   2.,  83.])
>>> x
array([[ 123.,    2.],
       [  13.,    2.],
       [  12.,   83.]])

answered Nov 27, 2015 at 5:56

orlp

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