Concat两个不同维度的数组numpy

问题描述：

我正在尝试连接两个numpy数组以添加额外的列:array_1是(569, 30)，而array_2是(569, )

I am trying to concatenate two numpy arrays to add an extra column: array_1 is (569, 30) and array_2 is is (569, )

combined = np.concatenate((array_1, array_2), axis=1)

我认为如果设置axis=2可以正常工作，因此它将垂直连接.末尾应为569 x 31阵列.

I thought this would work if I set axis=2 so it will concatenate vertically. The end should should be a 569 x 31 array.

我得到的错误是ValueError: all the input arrays must have same number of dimensions

有人可以帮忙吗?

谢谢！

答

您可以使用numpy.column_stack:

np.column_stack((array_1, array_2))

这会将1-d数组隐式转换为2-d，因此等同于@umutto注释的np.concatenate((array_1, array_2[:,None]), axis=1).

Which converts the 1-d array to 2-d implicitly, and thus equivalent to np.concatenate((array_1, array_2[:,None]), axis=1) as commented by @umutto.

a = np.arange(6).reshape(2,3)
b = np.arange(2)

a
#array([[0, 1, 2],
#       [3, 4, 5]])

b
#array([0, 1])

np.column_stack((a, b))
#array([[0, 1, 2, 0],
#       [3, 4, 5, 1]])

Concat两个不同维度的数组numpy

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