Pandas DataFrame Sort:要进行汇总和排序，但要保留列名 [英] Pandas DataFrame Sort: Want to sum and sort, but keep column names

问题描述

现在，我正在对一个DataFrame对象运行求和并对其进行排序:

Right now, I am running a sum and sort on a DataFrame object:

games_tags.groupby(['GameID', 'GameName', 'Tag']).sum().sort(['Count'], ascending=False)

我遇到的问题是，之后，我希望仍然能够通过row ['GameID']等来获取每一行的GameID，GameName和Tag.但是，我注意到在使用总和后()方法，它将创建一个名为"Count"的列，但我无法再访问任何原始列.

The issue I'm running into is that afterwards, I want to be able to still grab each row's GameID, GameName, and Tag via row['GameID'], etc. However, I noticed that after I use the sum() method, it creates a column named 'Count', but I can no longer access any of the original columns.

我想知道是否有人知道我所缺少的sum()方法的解决方法或某些复杂性.任何帮助表示赞赏.谢谢！

I was wondering if anyone knows a work around or some intricacy to the sum() method that I am missing. Any help is appreciated. Thanks!

推荐答案

您可以在groupby之后重设索引以将列还原回去:

You can reset the index after the groupby to restore the columns back:

game_tags.reset_index(inplace=True)

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