根据索引中的关键字汇总行 [英] Summing rows based on keyword within index

问题描述

我正在尝试根据作为索引一部分的关键字将多个行加在一起-但这不是整个索引.例如，索引可能看起来像

I am trying to sum multiple rows together based on a keyword that is part of the index - but it is not the entire index. For example, the index could look like

                   Count
1234_Banana_Green   43
4321_Banana_Yellow  34
2244_Banana_Brown   23
12345_Apple_Red     45

我想对其中具有相同关键字"的所有行求和，并创建一个总的香蕉"行.有没有一种方法可以在不搜索关键字"banana"的情况下进行操作?出于我的目的，此关键字每次都会更改，我希望能够自动执行该求和过程.很感谢任何形式的帮助.

I would like to sum all of the rows that have the same "keyword" within them and create a total "banana" row. Is there a way to do this without searching for the keyword "banana"? For my purposes, this keyword changes every time and I would like to be able to automate this summing process. Any help is very much appreciated.

推荐答案

可能是这样:

df.groupby(df.index.to_series()
           .str.split('_', expand=True)[1]
          )['Count'].sum()

输出:

1
Apple      45
Banana    100
Name: Count, dtype: int64

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