英文:
Atributting values to specific numbers trough a file
问题
我有一个问题，是否有办法将第一列的数字与第二列的数字关联起来？这样我就可以阅读第二列的数字，但它们与第一列的数字以某种方式相连，以便我可以像在sorted_resistances列表中那样对它们进行排序，但在对它们进行排序之后，我将它们替换为分配给每个值的第一列中的值。
关于代码的信息是从文件中打开列表，这就是为什么它以这种方式编程的原因。
1 30000
2 30511
3 30052
4 30033
5 30077
6 30055
7 30086
8 30044
9 30088
10 30019
11 30310
12 30121
13 30132
with open("file.txt") as file_in:
list_of_resistances = []
for line in file_in:
list_of_resistances.append(int(line.split()[1]))
sorted_resistances = sorted(list_of_resistances)
英文:
My question is if there's any way to attribute the numbers in the first column to the ones in the second column. So that I can read the numbers in the second column but have them connected to the ones in the first column in some way, so that I can sort them as I do in the sorted_resistances list but after sorting them I replace them with the values in the first column that we're assigned to each of the values.
For information in the code it's opening up from a file the list that's why it's programed like that
1 30000
2 30511
3 30052
4 30033
5 30077
6 30055
7 30086
8 30044
9 30088
10 30019
11 30310
12 30121
13 30132
with open("file.txt") as file_in:
list_of_resistances = []
for line in file_in:
list_of_resistances.append(int(line.split()[1]))
sorted_resistances = sorted(list_of_resistances)
答案1
得分: 0
以下是翻译好的内容：
如果您希望保持两列中值之间的相关性，您可以将每行的所有值保存在一个元组（或列表）中，然后使用特定的片段通过将 lambda 函数传递给 sorted() 函数的 key 参数对元组列表进行排序，告诉它使用每个元组的第二个部分作为排序值。
在这个示例中，我使用了 pprint.pprint 来使列表的输出更容易阅读。
from pprint import pprint
with open("file.txt") as file_in:
list_of_resistances = []
for line in file_in:
list_of_resistances.append(tuple(line.strip().split(' ')))
print("未排序的值:")
pprint(list_of_resistances)
sorted_resistances = sorted(list_of_resistances, key=lambda x: x[1])
print("\n已排序的值:")
pprint(sorted_resistances)
print("\n从第一列排序的键:")
pprint([x[0] for x in sorted_resistances])
输出：
未排序的值:
[('1', '30000'),
('2', '30511'),
('3', '30052'),
('4', '30033'),
('5', '30077'),
('6', '30055'),
('7', '30086'),
('8', '30044'),
('9', '30088'),
('10', '30019'),
('11', '30310'),
('12', '30121'),
('13', '30132')]
已排序的值:
[('1', '30000'),
('10', '30019'),
('4', '30033'),
('8', '30044'),
('3', '30052'),
('6', '30055'),
('5', '30077'),
('7', '30086'),
('9', '30088'),
('12', '30121'),
('13', '30132'),
('11', '30310'),
('2', '30511')]
从第一列排序的键:
['1', '10', '4', '8', '3', '6', '5', '7', '9', '12', '13', '11', '2']
英文:
If you want to keep the correlation between the values in the two columns, you can keep all of the values from each line in a tuple (or list), and then sort the list of tuples using a specific piece by passing a lambda function to the key parameter of the sorted() function that tells it to use the second piece of each tuple as the sort value.
In this example, I used pprint.pprint to make the output the of the lists easier to read.
from pprint import pprint
with open("file.txt") as file_in:
list_of_resistances = []
for line in file_in:
list_of_resistances.append(tuple(line.strip().split(' ')))
print("Unsorted values:")
pprint(list_of_resistances)
sorted_resistances = sorted(list_of_resistances, key=lambda x: x[1])
print("\nSorted values:")
pprint(sorted_resistances)
print("\nSorted keys from column 1:")
pprint([x[0] for x in sorted_resistances])
Output:
Unsorted values:
[('1', '30000'),
('2', '30511'),
('3', '30052'),
('4', '30033'),
('5', '30077'),
('6', '30055'),
('7', '30086'),
('8', '30044'),
('9', '30088'),
('10', '30019'),
('11', '30310'),
('12', '30121'),
('13', '30132')]
Sorted values:
[('1', '30000'),
('10', '30019'),
('4', '30033'),
('8', '30044'),
('3', '30052'),
('6', '30055'),
('5', '30077'),
('7', '30086'),
('9', '30088'),
('12', '30121'),
('13', '30132'),
('11', '30310'),
('2', '30511')]
Sorted keys from column 1:
['1', '10', '4', '8', '3', '6', '5', '7', '9', '12', '13', '11', '2']
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