将一维数组附加到 Numpy Python 中的二维数组
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Append a 1d array to a 2d array in Numpy Python
提问by excavator
I have a numpy 2D array [[1,2,3]].
I need to append a numpy 1D array,( say [4,5,6]) to it, so that it becomes [[1,2,3], [4,5,6]]
我有一个 numpy 二维数组[[1,2,3]]。我需要在它上面附加一个 numpy 1D 数组，（比如说[4,5,6]），这样它就变成了[[1,2,3], [4,5,6]]
This is easily possible using lists, where you just call appendon the 2D list.
使用列表很容易做到这一点，您只需在二维列表上调用append 即可。
But how do you do it in Numpy arrays?
但是你如何在 Numpy 数组中做到这一点呢？
np.concatenateand np.appenddont work. they convert the array to 1D for some reason.
np.concatenate并且np.append不工作。他们出于某种原因将数组转换为一维。
Thanks!
谢谢！
采纳答案by Padraic Cunningham
You want vstack:
你想要vstack：
In [45]: a = np.array([[1,2,3]])
In [46]: l = [4,5,6]
In [47]: np.vstack([a,l])
Out[47]:
array([[1, 2, 3],
[4, 5, 6]])
You can stack multiple rows on the condition that The arrays must have the same shape along all but the first axis.
您可以堆叠多行，条件是数组必须沿除第一个轴之外的所有轴具有相同的形状。
In [53]: np.vstack([a,[[4,5,6], [7,8,9]]])
Out[53]:
array([[1, 2, 3],
[4, 5, 6],
[4, 5, 6],
[7, 8, 9]])
回答by Wattanapong Suttapak
Try this:
尝试这个：
np.concatenate(([a],[b]),axis=0)
when
什么时候
a = np.array([1,2,3])
b = np.array([4,5,6])
then result should be:
那么结果应该是：
array([[1, 2, 3], [4, 5, 6]])
数组([[1, 2, 3], [4, 5, 6]])
