How To Remove A Column In A Numpy Array?

Imagine we have a 5x4 matrix. We need to remove only the first dimension. How can we do it with numpy? array([[ 0., 1., 2., 3.], [ 4., 5., 6., 7.], [

Solution 1:

If you want to remove a column from a 2D Numpy array you can specify the columns like this

to keep all rows and to get rid of column 0 (or start at column 1 through the end)

a[:,1:]

another way you can specify the columns you want to keep ( and change the order if you wish) This keeps all rows and only uses columns 0,2,3

a[:,[0,2,3]]

The documentation on this can be found here

And if you want something which specifically removes columns you can do something like this:

idxs = list.range(4)
idxs.pop(2) #this removes elements from the lista[:, idxs]

and @hpaulj brought up numpy.delete()

This would be how to return a view of 'a' with 2 columns removed (0 and 2) along axis=1.

np.delete(a,[0,2],1)

This doesn't actually remove the items from 'a', it's return value is a new numpy array.

Solution 2:

The correct way to use delete is to specify index and dimension, eg. remove the 1st (0) column (dimension 1):

In [215]: np.delete(np.arange(20).reshape(5,4),0,1)
Out[215]: 
array([[ 1,  2,  3],
       [ 5,  6,  7],
       [ 9, 10, 11],
       [13, 14, 15],
       [17, 18, 19]])

other expressions that work:

np.arange(20).reshape(5,4)[:,1:]
np.arange(20).reshape(5,4)[:,[1,2,3]]
np.arange(20).reshape(5,4)[:,np.array([False,True,True,True])]

Solution 3:

You don't need the second reshape.

matrix=np.delete(matrix,0,1)