在python中汇总 pandas 数据时，如何计算每组尾巴的和 [英] how to calculate sum|mean|median for tail of each group when pandas data aggregated in python

问题描述

我有如下数据，它是熊猫数据帧格式.

i am having data like following.which is in pandas data frame format.

A  B  C  D  E  F  G
1  1  2  3  1  4  2
1  1  2  4  5  6  7
1  1  2  3  2  3  2
1  1  2  4  5  6  7
2  1  2  3  2  3  4
2  1  2  3  4  3  3
2  1  2  4  5  6  7

此处agg_lvl = ['A'，'B'，'C']

here agg_lvl=['A','B','C']

当数据聚合到agg_lvl时，我想通过在每个组中使用tail(2)记录来计算G变量的均值| median | sum.

I want to calculate mean|median|sum for G variable by using tail(2) records in each group when data aggregated to agg_lvl.

我的预期输出是这样的:

And my expected output is like this:

期望的平均值输出:

A  B  C  G
1  1  2  4.5
2  1  2   5

中位数和总和的输出也将相同，但是要代替平均值，我们必须考虑中位数和总和.

the output will be same for median and sum also,but in place of mean we have to consider median and sum values.

为此，我尝试了以下代码，但未获得预期的输出.

for that i tried the following code but i didn't get the expected output.

df.groupby(agg_lvl,as_index=False).tail(2).agg({'G':'mean'})

谁能帮我解决这个问题.

can anyone help me tackle this issue.

谢谢.

推荐答案

使用

Use GroupBy.transform instead agg for return new column with same shape as filtered DataFrame by tail:

agg_lvl=['A','B','C']
df = df.groupby(agg_lvl,as_index=False).tail(2)
df['G'] = df.groupby(agg_lvl)['G'].transform('mean')
print (df)
   A  B  C  D  E  F    G
2  1  1  2  3  2  3  4.5
3  1  1  2  4  5  6  4.5
5  2  1  2  3  4  3  5.0
6  2  1  2  4  5  6  5.0

df = df.groupby(agg_lvl,as_index=False).tail(2).groupby(agg_lvl,as_index=False)['G'].mean()
print (df)
   A  B  C    G
0  1  1  2  4.5
1  2  1  2  5.0

这篇关于在python中汇总 pandas 数据时，如何计算每组尾巴的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IT屋！