pandas :按组对观察结果进行排序 [英] pandas: sorting observations within groupby groups

问题描述

根据对 pandas groupby在组内进行排序的答案，以便进行排序每个组中的观测值需要对第一个groupby的结果进行第二个groupby.为什么需要第二个groupby?我本以为在运行第一个groupby之后，观察值已经被分组了，而所需要的只是一种枚举那些组的方式(并用order运行apply).

According to the answer to pandas groupby sort within groups, in order to sort observations within each group one needs to do a second groupby on the results of the first groupby. Why a second groupby is needed? I would've assumed that observations are already arranged into groups after running the first groupby and all that would be needed is a way to enumerate those groups (and run apply with order).

推荐答案

因为在groupby之后应用了函数，结果将重新组合为正常的未分组数据帧.使用groupby和诸如sort之类的groupby方法应该被视为 Split-Apply-Combine操作

Because once you apply a function after a groupby the results are combined back into a normal ungrouped data frame. Using groupby and a groupby method like sort should be thought of like a Split-Apply-Combine operation

groupby拆分原始数据帧，并将该方法应用于每个组，但随后再次隐式合并结果.

The groupby splits the original data frame and the method is applied to each group, but then the results are combined again implicitly.

在另一个问题中，他们可以颠倒操作(先排序)，然后不必使用两个groupby.他们可以这样做:

In that other question, they could have reversed the operation (sorted first) and then not have to use two groupbys. They could do:

df.sort(['job','count'],ascending=False).groupby('job').head(3)

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