将numpy数组转换为2d数组 [英] converty numpy array of arrays to 2d array
问题描述
我有一个熊猫系列features
,具有以下值(features.values
)
I have a pandas series features
that has the following values (features.values
)
array([array([0, 0, 0, ..., 0, 0, 0]), array([0, 0, 0, ..., 0, 0, 0]),
array([0, 0, 0, ..., 0, 0, 0]), ...,
array([0, 0, 0, ..., 0, 0, 0]), array([0, 0, 0, ..., 0, 0, 0]),
array([0, 0, 0, ..., 0, 0, 0])], dtype=object)
现在,我真的希望将其识别为矩阵,但是如果我愿意,那么
Now I really want this to be recognized as matrix, but if I do
>>> features.values.shape
(10000,)
而不是我期望的(10000, 3000)
.
如何将其识别为2d而不是将数组作为值的1d数组.还有为什么它不自动将其检测为2d数组?
How can I get this to be recognized as 2d rather than a 1d array with arrays as values. Also why does it not automatically detect it as a 2d array?
推荐答案
在回答您的评论问题时,让我们比较两种创建数组的方法
In response your comment question, let's compare 2 ways of creating an array
首先从数组列表(长度相同)中创建一个数组:
First make an array from a list of arrays (all same length):
In [302]: arr = np.array([np.arange(3), np.arange(1,4), np.arange(10,13)])
In [303]: arr
Out[303]:
array([[ 0, 1, 2],
[ 1, 2, 3],
[10, 11, 12]])
结果是二维数组.
相反,如果我们创建一个对象dtype数组,并用数组填充它:
If instead we make an object dtype array, and fill it with arrays:
In [304]: arr = np.empty(3,object)
In [305]: arr[:] = [np.arange(3), np.arange(1,4), np.arange(10,13)]
In [306]: arr
Out[306]:
array([array([0, 1, 2]), array([1, 2, 3]), array([10, 11, 12])],
dtype=object)
请注意,此显示与您的显示类似.通过设计,这是一维数组.像列表一样,它包含指向内存中其他位置的数组的指针.请注意,这需要额外的构造步骤. np.array
的默认行为是在可以的地方创建一个多维数组.
Notice that this display is like yours. This is, by design a 1d array. Like a list it contains pointers to arrays elsewhere in memory. Notice that it requires an extra construction step. The default behavior of np.array
is to create a multidimensional array where it can.
要解决这个问题需要花费额外的精力.同样,要撤消该操作也需要付出额外的努力-创建2d数字数组.
It takes extra effort to get around that. Likewise it takes some extra effort to undo that - to create the 2d numeric array.
仅在其上调用np.array
不会更改结构.
Simply calling np.array
on it does not change the structure.
In [307]: np.array(arr)
Out[307]:
array([array([0, 1, 2]), array([1, 2, 3]), array([10, 11, 12])],
dtype=object)
stack
确实将其更改为2d. stack
将其视为数组列表,并在新轴上联接.
stack
does change it to 2d. stack
treats it as a list of arrays, which it joins on a new axis.
In [308]: np.stack(arr)
Out[308]:
array([[ 0, 1, 2],
[ 1, 2, 3],
[10, 11, 12]])
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