I have a numpy array:
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
Now I want to add a column of all ones in front of it to get:
array([[1, 1, 2, 3],
[1, 4, 5, 6],
[1, 7, 8, 9]])
I saw many posts pertaining to my question, but none of them could solve my problem. I tried np.concatenate np.append np.hstack but unfortunately none of them worked.
Simply use np.concatenate:
>>> import numpy as np
>>> arr = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
>>> np.concatenate((np.array([0,0,0])[:, np.newaxis], arr), axis=1)
array([[0, 1, 2, 3],
[0, 4, 5, 6],
[0, 7, 8, 9]])
But hstack works too:
>>> np.hstack((np.array([0,0,0])[:, np.newaxis], arr))
array([[0, 1, 2, 3],
[0, 4, 5, 6],
[0, 7, 8, 9]])
The only "tricky" part is that both arrays must have the same number of dimensions, that's why I added the [:, np.newaxis] - which adds a new dimension.
How to change the zeros to ones is left as an (easy) exercise :-)
If you want to prepend a 2D array you have to drop the [:, np.newaxis] part:
np.concatenate((np.zeros((3,3), dtype=int), arr), axis=1)
array([[0, 0, 0, 1, 2, 3],
[0, 0, 0, 4, 5, 6],
[0, 0, 0, 7, 8, 9]])
None: np.array([0,0,0])[:, None]
np.newaxis is just an alias for None, see for example None is np.newaxis = True. But I think it's a bit more explicit and thus preferrable when answering questions for people learning numpy. But nevertheless thank you for the comment, it might help future visitors +1
np.concatenate((np.ones((3, 3))[:, np.newaxis], arr), axis=1) give me the error: ValueError: all the input arrays must have same number of dimensions[:, np.newaxis] part.I prefer this way:
ones = np.ones((3,1)) #3 is a number of rows in your array.
new_array = np.hstack((ones,arr))
vstack behaves a bit more nicely without having to worry about new axes, though MSeifert's answer is probably more correct:
p = np.array([1,1,1])
q = np.array([[1,2,3],[4,5,6],[7,8,9]])
np.vstack((p,q.T)).T
