Question

所以我有一个numpy，python中的数组，看起来像这样：

print array
[[1, 2, 3, 4, 5, 6, 7]]

但是，我想将其更改为：

print array
[1, 2, 3, 4, 5, 6, 7]

原始数组是：

print array
[[ 1]
 [ 2]
 [ 3]
 [ 4]
 [ 5]
 [ 6]
 [ 7]]

我使用以下命令将其更改为我的数组：

x = np.reshape(1, len(array))

如何使用内置的numpy功能完成此更改？
我不想使用循环，因为我需要速度来处理大量数据。

Answer 1

您可以在阵列上使用np.flatten：

>>> x
array([[1],
       [2],
       [3],
       [4],
       [5]])
>>> x.flatten()
array([1, 2, 3, 4, 5])

Answer 2

np.reshape(x,[-1])

来自帮助：

 newshape : int or tuple of ints
        The new shape should be compatible with the original shape. If
        an integer, then the result will be a 1-D array of that length.
        One shape dimension can be -1. In this case, the value is inferred
        from the length of the array and remaining dimensions.
    order : {'C', 'F', 'A'}, optional
        Read the elements of `a` using this index order, and place the elements
        into the reshaped array using this index order.  'C' means to
        read / write the elements using C-like index order, with the last axis index
        changing fastest, back to the first axis index changing slowest.  'F'
        means to read / write the elements using Fortran-like index order, with
        the first index changing fastest, and the last index changing slowest.
        Note that the 'C' and 'F' options take no account of the memory layout
        of the underlying array, and only refer to the order of indexing.  'A'
        means to read / write the elements in Fortran-like index order if `a` is
        Fortran *contiguous* in memory, C-like order otherwise.

g=np.array([1, 2, 3, 4, 5])
d=np.reshape(g,(1,-1))
print( d )
>>>[[1 2 3 4 5]]
f=np.reshape(d,[-1])
print( f)
>>>array([1, 2, 3, 4, 5])

在numpy中将数组从（行，列）更改为（行）

2 个答案: