ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 1

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ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 1 ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 1 dimension(s) and the array at index 1 has 2 dimension(s)

ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 1 dimension(s) and the array at index 1 has 2 dimension(s)

问题：

解决：

完整错误：

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问题：import numpy as np# create a 1d arrayar1 = np.array([1, 2])# create a 2d arrayar2 = np.array([[0, 0, 0], [1, 1, 1]])# hstack the arraysar_h = np.hstack((ar1, ar2))# display the concatenated arrayprint(ar_h)解决：import numpy as np# create a 1d arrayar1 = np.array([[1, 2], [1, 2]])# create a 2d array ar2 = np.array([[0, 0, 0], [1, 1, 1]])# hstack the arraysar_h = np.hstack((ar1, ar2))# display the concatenated arrayprint(ar_h)*********************************************************************[[1 2 0 0 0] [1 2 1 1 1]]完整错误：---------------------------------------------------------------------------ValueError Traceback (most recent call last)<ipython-input-2-f0ed0654d3e0> in <module> 7 8 # hstack the arrays----> 9 ar_h = np.hstack((ar1, ar2)) 10 # display the concatenated array 11 print(ar_h)<__array_function__ internals> in hstack(*args, **kwargs)D:\anaconda\lib\site-packages\numpy\core\shape_base.py in hstack(tup) 341 # As a special case, dimension 0 of 1-dimensional arrays is "horizontal" 342 if arrs and arrs[0].ndim == 1:--> 343 return _nx.concatenate(arrs, 0) 344 else: 345 return _nx.concatenate(arrs, 1)<__array_function__ internals> in concatenate(*args, **kwargs)ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 1 dimension(s) and the array at index 1 has 2 dimension(s)

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