Trouble using np.append with 2d array

Question

So i'm trying to append 2 np array together but it gives me this error ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 2 dimension(s) and the array at index 1 has 1 dimension(s)I know that this mean the shape of the array are not the same but I don't understand why and how to fix it.

arr1 = np.array([
 [10.24217065  5.63381577]
 [ 2.71521988 -3.33068004]
 [-3.43022486 16.40921457]
 [ 1.4461307  12.59851726]
 [12.34829023 29.67531647] 
 [16.65382971  9.8915765 ]])

arr2 = np.array([4.62643996 5.14587112])

arr3 = np.append(arr1,arr2,axis=0)

It should be obvious to you that arr1 is 2d with shape (6,2), and arr2 is 1d with shape (2,). If not, then you need to read some more numpy basics. — hpaulj
– hpaulj, Commented Jun 6, 2020 at 15:54
np.append with axis parameter just uses np.concatenate([ arg1, args2], axis=0). Concatenate is picky about the number of dimensions, and patching shapes. I'd recommend staying away from np.append, and learn enough about dimensions to use np.concatenate correctly. — hpaulj
– hpaulj, Commented Jun 6, 2020 at 15:58

ywbaek · Accepted Answer · 2020-06-06 15:31:12Z

1

Simply make them the same dimension:

arr3 = np.append(arr1, [arr2], axis=0)

answered Jun 6, 2020 at 15:31

ywbaek

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bnaecker · Accepted Answer · 2020-06-06 15:34:25Z

1

arr2 has only a single dimension, since its shape is (2,). arr1 on the other hand has two dimensions, since its shape is (6, 2). These aren't compatible for np.append, as it says.

You can make arr2 have the required number of dimensions in many ways. One of them is reshaping:

arr3 = np.append(arr1, arr2.reshape(1, 2), axis=0)

At this point, the arrays have shape (6, 2) and (1, 2), which np.append knows how to deal with. The output will have shape (7, 2).

answered Jun 6, 2020 at 15:34

bnaecker

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Glauvus · Accepted Answer · 2020-06-06 15:36:44Z

1

The error message tells you exactly what is the problem. The first array has two dimensions and the second array has one dimension. Another pair of [ ] in the second array will do the job.

arr2 = np.array([[4.62643996 5.14587112]])

answered Jun 6, 2020 at 15:36

Glauvus

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Mark Bakker · Accepted Answer · 2020-06-06 16:20:36Z

0

arr3 = np.vstack((arr1, arr2))

or if you really want to use append, my favorite is

arr3 = np.append(arr1, arr2[np.newaxis, :])

answered Jun 6, 2020 at 16:20

Mark Bakker

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