I suspect you are trying to replicate this working list code:
In [56]: x = []
In [57]: x.append[[1,2]]
In [58]: x
Out[58]: [[1, 2]]
In [59]: np.array[x]
Out[59]: array[[[1, 2]]]
But with arrays:
In [53]: x = np.empty[[2,2],int]
In [54]: x
Out[54]:
array[[[73096208, 10273248],
[ 2, -1]]]
Despite the name, the np.empty array is NOT a close of the empty list. It has 4 elements, the shape that you specified.
In [55]: np.append[x, np.array[[1,2]], axis=0]
---------------------------------------------------------------------------
ValueError Traceback [most recent call last]
in
----> 1 np.append[x, np.array[[1,2]], axis=0]
in append[*args, **kwargs]
/usr/local/lib/python3.6/dist-packages/numpy/lib/function_base.py in append[arr, values, axis]
4691 values = ravel[values]
4692 axis = arr.ndim-1
-> 4693 return concatenate[[arr, values], axis=axis]
4694
4695
in concatenate[*args, **kwargs]
ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 2 dimension[s] and the array at index 1 has 1 dimension[s]
Note that np.append has passed the task on to np.concatenate. With the axis parameter, that's all this append does. It is NOT a list append clone.
np.concatenate demands consistency in the dimensions of its inputs. One is [2,2], the other [2,].
Mismatched dimensions.
np.append is a dangerous function, and not that useful even when used correctly. np.concatenate [and the various stack] functions are useful. But you need to pay attention to shapes. And don't use them iteratively. List append is more efficient for that.
When you got this error, did you look up the np.append, np.empty [and np.concatenate] functions? Read and understand the docs? In the long run SO questions aren't a substitute for reading the documentation.
Created: April-26, 2021 This tutorial will
introduce the methods to append new rows to an empty NumPy array in Python.numpy.append[] Function
Append to NumPy Empty Array With the numpy.append[] Function
If we have an empty array and want to append new rows to it inside a loop, we can use the numpy.empty[] function. Since no data type is assigned to a variable before initialization in Python, we have to specify the data type and structure of the array elements while creating the empty array.
This can be done inside the numpy.empty[] function. We can then append new rows to the empty array with the numpy.append[] function. See the following code example.
import numpy as np
array = np.empty[[0,3], int]
array = np.append[array, np.array[[[1,3,5]]], axis=0]
array = np.append[array, np.array[[[2,4,6]]], axis=0]
print[array]
Output:
[[1 3 5]
[2 4 6]]
We first created an empty array and defined its structure and data type with the np.empty[] function. We then appended two rows along the 0 axis of the
array with the np.append[] function.
Append to NumPy Empty Array With the List Method in Python
We can also achieve the same goal by using the list data structure in Python. We can create empty lists and append rows to them in Python. The list.append[] function appends new elements to a list in Python. We can then convert this list to a NumPy array with
the numpy.array[] function. See the following code example.
import numpy as np
list = []
list.append[[1,3,5]]
list.append[[2,4,6]]
array2 = np.array[list]
print[array2]
Output:
[[1 3 5]
[2 4 6]]
We first created an empty list list and appended new rows to the list with the list.append[] function. In the end, we converted the list to the NumPy array array2 with the np.array[list] function in Python.
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