Python将列表重塑为ndim数组
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Python reshape list to ndim array
提问by BenP
Hi I have a list flat which is length 2800, it contains 100 results for each of 28 variables: Below is an example of 4 results for 2 variables
嗨，我有一个长度为 2800 的列表平面，它包含 28 个变量中的每一个的 100 个结果：下面是 2 个变量的 4 个结果的示例
[0,
0,
1,
1,
2,
2,
3,
3]
I would like to reshape the list to an array (2,4) so that the results for each variable are in a single element.
我想将列表重塑为数组 (2,4)，以便每个变量的结果都在一个元素中。
[[0,1,2,3],
[0,1,2,3]]
采纳答案by kazemakase
You can think of reshaping that the new shape is filled row by row (last dimension varies fastest) from the flattened original list/array.
您可以考虑将新形状从展平的原始列表/数组中逐行填充（最后一个维度变化最快）。
An easy solution is to shape the list into a (100, 28) array and then transpose it:
一个简单的解决方案是将列表整形为 (100, 28) 数组，然后将其转置：
x = np.reshape(list_data, (100, 28)).T
Update regarding the updated example:
关于更新示例的更新：
np.reshape([0, 0, 1, 1, 2, 2, 3, 3], (4, 2)).T
# array([[0, 1, 2, 3],
# [0, 1, 2, 3]])
np.reshape([0, 0, 1, 1, 2, 2, 3, 3], (2, 4))
# array([[0, 0, 1, 1],
# [2, 2, 3, 3]])
回答by cristiandatum
Step by step:
一步步：
# import numpy library
import numpy as np
# create list
my_list = [0,0,1,1,2,2,3,3]
# convert list to numpy array
np_array=np.asarray(my_list)
# reshape array into 4 rows x 2 columns, and transpose the result
reshaped_array = np_array.reshape(4, 2).T
#check the result
reshaped_array
array([[0, 1, 2, 3],
[0, 1, 2, 3]])
回答by Vinay Verma
The answers above are good. Adding a case that I used. Just if you don't want to use numpy and keep it as list without changing the contents.
楼上的回答都不错。添加我使用的案例。只是如果您不想使用 numpy 并将其保留为列表而不更改内容。
You can run a small loop and change the dimension from 1xN to Nx1.
您可以运行一个小循环并将维度从 1xN 更改为 Nx1。
tmp=[]
for b in bus:
tmp.append([b])
bus=tmp
It is maybe not efficient while in case of very large numbers. But it works for a small set of numbers. Thanks
在非常大的数字的情况下，它可能效率不高。但它适用于一小组数字。谢谢
