numpy /弄平列表

发布于 2025-02-11 15:37:14 字数 779 浏览 0 评论 0原文

我创建了这个字符

list1 = [['20']*3,['35']*2,['40']*4,['10']*2,['15']*3]

结果的此：

[['20', '20', '20'], ['35', '35'], ['40', '40', '40', '40'], ['10', '10'], ['15', '15', '15']]

来将其转换为单个列表

charlist = [x for sublist in list1 for x in sublist]
print(charlist)
['20', '20', '20', '35', '35', '40', '40', '40', '40', '10', '10', '15', '15', '15']

我可以使用列表理解我想知道如何使用numpy

listNP=np.array(list1)

给出的输出

array([list(['20', '20', '20']), list(['35', '35']),
       list(['40', '40', '40', '40']), list(['10', '10']),
       list(['15', '15', '15'])], dtype=object)

：事实是 listnp.flatten（）给出输出相同的结果。可能我错过了将列表转换为Numpy数组的步骤

原文

I have create this of character

list1 = [['20']*3,['35']*2,['40']*4,['10']*2,['15']*3]

result :

[['20', '20', '20'], ['35', '35'], ['40', '40', '40', '40'], ['10', '10'], ['15', '15', '15']]

I can convert it into a single list using list comprehension

charlist = [x for sublist in list1 for x in sublist]
print(charlist)
['20', '20', '20', '35', '35', '40', '40', '40', '40', '10', '10', '15', '15', '15']

I was wondering how to do that with numpy

listNP=np.array(list1)

gives as output :

array([list(['20', '20', '20']), list(['35', '35']),
       list(['40', '40', '40', '40']), list(['10', '10']),
       list(['15', '15', '15'])], dtype=object)

The fact is that listNP.flatten() gives as an output the same result. Probably I missed a step when converting the list into an numpy array

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尾戒 2025-02-18 15:37:14

您可以绕过所有额外的操作，并使用np.repeat：

>>> np.repeat(['20', '35', '40', '10', '15'], [3, 2, 4, 2, 3])
array(['20', '20', '20', '35', '35', '40', '40', '40', '40',
       '10', '10', '15', '15', '15'], dtype='<U2')

如果您需要dtype = object，请首先将第一个参数放入数组：

arr1 = np.array(['20', '35', '40', '10', '15'], dtype=object)
np.repeat(arr1, [3, 2, 4, 2, 3])

You can bypass all the extra operations and use np.repeat:

>>> np.repeat(['20', '35', '40', '10', '15'], [3, 2, 4, 2, 3])
array(['20', '20', '20', '35', '35', '40', '40', '40', '40',
       '10', '10', '15', '15', '15'], dtype='<U2')

If you need dtype=object, make the first argument into an array first:

arr1 = np.array(['20', '35', '40', '10', '15'], dtype=object)
np.repeat(arr1, [3, 2, 4, 2, 3])

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半﹌身腐败 2025-02-18 15:37:14

使用 hstack（）

import numpy as np
list1 = [['20']*3,['35']*2,['40']*4,['10']*2,['15']*3]
flatlist = np.hstack(list1)

print(flatlist)

['20''20'20''35'35''30'40'40'40''40''10'10''10'15'15'15'15']

试图构建您的< code> listnp 带有np.array与您在OP中所做的那样，我对锯齿阵列有一个警告，不得不使用dtype = object，但是让<代码> hstack 直接构建它不会引起警告（感谢评论中的@michael delgado）

Use hstack()

import numpy as np
list1 = [['20']*3,['35']*2,['40']*4,['10']*2,['15']*3]
flatlist = np.hstack(list1)

print(flatlist)

['20' '20' '20' '35' '35' '40' '40' '40' '40' '10' '10' '15' '15' '15']

In trying to construct your ListNP with np.array as you do in the OP, I got a warning about jagged arrays and having to use dtype=object, but letting hstack construct it directly doesn't evoke a warning (thanks @Michael Delgado in the comments)

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