numpy merge arrays
>>> a = np.array([[1, 2], [3, 4]])
>>> b = np.array([[5, 6]])
>>> np.concatenate((a, b), axis=0)
array([[1, 2],
[3, 4],
[5, 6]])
>>> np.concatenate((a, b.T), axis=1)
array([[1, 2, 5],
[3, 4, 6]])numpy merge arrays
>>> a = np.array([[1, 2], [3, 4]])
>>> b = np.array([[5, 6]])
>>> np.concatenate((a, b), axis=0)
array([[1, 2],
[3, 4],
[5, 6]])
>>> np.concatenate((a, b.T), axis=1)
array([[1, 2, 5],
[3, 4, 6]])np.vstack multiple arrays
>>> import numpy as np
>>> a = ([1,2,3,4,5])
>>> b = ([2,3,4,5,6])
>>> c = ([3,4,5,6,7])
>>> np.array([a, b, c])
array([[1, 2, 3, 4, 5],
[2, 3, 4, 5, 6],
[3, 4, 5, 6, 7]])
>>> np.stack([a, b, c], axis=0)
array([[1, 2, 3, 4, 5],
[2, 3, 4, 5, 6],
[3, 4, 5, 6, 7]])
>>> np.stack([a, b, c], axis=1) # not what you want, this is only to show what is possible
array([[1, 2, 3],
[2, 3, 4],
[3, 4, 5],
[4, 5, 6],
[5, 6, 7]])join two numpy arrays
numpy.concatenate([arr1, arr2]) # Joining arr1 and arr2np.concatenate
>>> a = np.array([[1, 2], [3, 4]])
>>> b = np.array([[5, 6]])
>>> np.concatenate((a, b), axis=0)
array([[1, 2],
[3, 4],
[5, 6]])
>>> np.concatenate((a, b.T), axis=1)
array([[1, 2, 5],
[3, 4, 6]])
>>> np.concatenate((a, b), axis=None)
array([1, 2, 3, 4, 5, 6])np.concatenate
numpy.concatenate((a1, a2, ...), axis)Copyright © 2021 Codeinu
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