Python在列表理解中使用枚举

2023-10-19Python开发问题
9

本文介绍了Python在列表理解中使用枚举的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

问题描述

假设我有一个这样的列表:

Lets suppose I have a list like this:

mylist = ["a","b","c","d"]

要获得与索引一起打印的值,我可以像这样使用 Python 的 enumerate 函数

To get the values printed along with their index I can use Python's enumerate function like this

>>> for i,j in enumerate(mylist):
...     print i,j
...
0 a
1 b
2 c
3 d
>>>

现在,当我尝试在 list comprehension 中使用它时,它给了我这个错误

Now, when I try to use it inside a list comprehension it gives me this error

>>> [i,j for i,j in enumerate(mylist)]
  File "<stdin>", line 1
    [i,j for i,j in enumerate(mylist)]
           ^
SyntaxError: invalid syntax

所以,我的问题是:在列表理解中使用 enumerate 的正确方法是什么?

So, my question is: what is the correct way of using enumerate inside list comprehension?

推荐答案

试试这个:

[(i, j) for i, j in enumerate(mylist)]

您需要将 i,j 放入一个元组中,列表解析才能起作用.或者,假设 enumerate() already 返回一个元组,您可以直接返回它而无需先解包:

You need to put i,j inside a tuple for the list comprehension to work. Alternatively, given that enumerate() already returns a tuple, you can return it directly without unpacking it first:

[pair for pair in enumerate(mylist)]

无论哪种方式,返回的结果都符合预期:

Either way, the result that gets returned is as expected:

> [(0, 'a'), (1, 'b'), (2, 'c'), (3, 'd')]

这篇关于Python在列表理解中使用枚举的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持跟版网!

The End

相关推荐

在xarray中按单个维度的多个坐标分组
groupby multiple coords along a single dimension in xarray(在xarray中按单个维度的多个坐标分组)...
2024-08-22 Python开发问题
15

Pandas中的GROUP BY AND SUM不丢失列
Group by and Sum in Pandas without losing columns(Pandas中的GROUP BY AND SUM不丢失列)...
2024-08-22 Python开发问题
17

GROUP BY+新列+基于条件的前一行抓取值
Group by + New Column + Grab value former row based on conditionals(GROUP BY+新列+基于条件的前一行抓取值)...
2024-08-22 Python开发问题
18

PANDA中的Groupby算法和插值算法
Groupby and interpolate in Pandas(PANDA中的Groupby算法和插值算法)...
2024-08-22 Python开发问题
11

PANAS-基于列对行进行分组,并将NaN替换为非空值
Pandas - Group Rows based on a column and replace NaN with non-null values(PANAS-基于列对行进行分组,并将NaN替换为非空值)...
2024-08-22 Python开发问题
10

按10分钟间隔对 pandas 数据帧进行分组
Grouping pandas DataFrame by 10 minute intervals(按10分钟间隔对 pandas 数据帧进行分组)...
2024-08-22 Python开发问题
11