使用 pandas GroupBy 获取每个组的统计信息(例如计数、平均值等)? [英] Get statistics for each group (such as count, mean, etc) using pandas GroupBy?

问题描述

我有一个数据框 df 并且我使用其中的几列到 groupby:

I have a data frame df and I use several columns from it to groupby:

df['col1','col2','col3','col4'].groupby(['col1','col2']).mean()

通过上面的方式，我几乎得到了我需要的表格(数据框).缺少的是包含每个组中行数的附加列.换句话说，我的意思是但我也想知道使用了多少个数字来获得这些平均值.例如，第一组有 8 个值，第二组有 10 个，依此类推.

In the above way I almost get the table (data frame) that I need. What is missing is an additional column that contains number of rows in each group. In other words, I have mean but I also would like to know how many number were used to get these means. For example in the first group there are 8 values and in the second one 10 and so on.

简而言之:如何获取数据帧的分组统计信息?

In short: How do I get group-wise statistics for a dataframe?

推荐答案

在 groupby 对象上，agg 函数可以带一个列表到 一次应用多种聚合方法.这应该会给你你需要的结果:

On groupby object, the agg function can take a list to apply several aggregation methods at once. This should give you the result you need:

df[['col1', 'col2', 'col3', 'col4']].groupby(['col1', 'col2']).agg(['mean', 'count'])

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