Concatenate Multidimensional Numpy array with 1D numpy array

Question

I have two numpy arrays (letters from the EMNIST dataset):

import scipy .io
emnist = scipy.io.loadmat(DATA_DIR + '/emnist-letters.mat')
data = emnist ['dataset']
X_train = data ['train'][0, 0]['images'][0, 0]
y_train = data ['train'][0, 0]['labels'][0, 0]

With the following dimensions:

X_train.shape = (124800, 784)

y_train.shape = (124800, 1)

Now, I want to concatenate the two, so that the new shape would be: (124800, 785).

Based on this link, I tried:

np.concatenate((X_train.shape, y_train.shape), axis = 0)

However, that results in the following shape: array([124800, 784, 124800, 1]).

How can I 'paste' y_train behind X_train so that the shape will be (124800, 785)?

JE_Muc · Accepted Answer · 2020-06-16 08:38:29Z

1

If you concatenate two arrays, you have to concatenate the data inside the arrays, not the shape. Furthermore you want to concatenate on the second ("short") axis, which is axis=1:

np.concatenate((X_train, y_train), axis=1)

answered Jun 16, 2020 at 8:38

JE_Muc

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