如何在Python中对具有相同名称的元组的值求和

How to sum values of tuples that have same name in Python(如何在Python中对具有相同名称的元组的值求和)
本文介绍了如何在Python中对具有相同名称的元组的值求和的处理方法,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

我有以下列表,其中包含必须值的元组:

I have the following list containing tuples that have to values:

mylist=[(3, 'a'), (2, 'b'), (4, 'a'), (5, 'c'), (2, 'a'), (1, 'b')]

有没有办法对所有同名的值求和?比如:

Is there a way to sum all values that share the same name? Something like:

(9, 'a'), (3, 'b'), (5, 'c')

我尝试使用 for 循环迭代元组,但无法得到我想要的.

I tried iterating tuples with for loop but can't get what i want.

谢谢

推荐答案

你可以使用itertools.groupby(按每个元组的第二个值排序后)创建组.然后对于每个组,对每个元组中的第一个元素求和,然后在列表推导中为每个组创建一个元组.

You can use itertools.groupby (after sorting by the second value of each tuple) to create groups. Then for each group, sum the first element in each tuple, then create a tuple per group in a list comprehension.

>>> import itertools
>>> [(sum(i[0] for i in group), key) for key, group in itertools.groupby(sorted(mylist, key = lambda i: i[1]), lambda i: i[1])]
[(9, 'a'), (3, 'b'), (5, 'c')]

这篇关于如何在Python中对具有相同名称的元组的值求和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!

本站部分内容来源互联网,如果有图片或者内容侵犯了您的权益,请联系我们,我们会在确认后第一时间进行删除!

相关文档推荐

groupby multiple coords along a single dimension in xarray(在xarray中按单个维度的多个坐标分组)
Group by and Sum in Pandas without losing columns(Pandas中的GROUP BY AND SUM不丢失列)
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)
Groupby and interpolate in Pandas(PANDA中的Groupby算法和插值算法)
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)
Grouping pandas DataFrame by 10 minute intervals(按10分钟间隔对 pandas 数据帧进行分组)