如何在保留原始数据帧的同时获取组级统计信息?

How to get group-level statistics while preserving the original dataframe?

我有以下数据框

one <- c('one',NA,NA,NA,NA,'two',NA,NA)
group1 <- c('A','A','A','A','B','B','B','B')
group2 <- c('C','C','C','D','E','E','F','F')

df = data.frame(one, group1,group2)


> df
   one group1 group2
1  one      A      C
2 <NA>      A      C
3 <NA>      A      C
4 <NA>      A      D
5 <NA>      B      E
6  two      B      E
7 <NA>      B      F
8 <NA>      B      F

我想为 group1group2 的每个组合获取 one 的非缺失观察值的计数。

在 Pandas 中,我会使用 groupby(['group1','group2']).transform,但我如何在 R 中做到这一点?原始数据框很大。

预期输出为:

> df
   one group1 group2 count
1  one      A      C     1
2 <NA>      A      C     1
3 <NA>      A      C     1
4 <NA>      A      D     0
5 <NA>      B      E     1
6  two      B      E     1
7 <NA>      B      F     0
8 <NA>      B      F     0

非常感谢!

data.table:

setDT(df)
df[,count_B:=sum(!is.na(one)),by=c("group1","group2")]

给出:

   one group1 group2 count_B
1: one      A      C       1
2:  NA      A      C       1
3:  NA      A      C       1
4:  NA      A      D       0
5:  NA      B      E       1
6: two      B      E       1
7:  NA      B      F       0
8:  NA      B      F       0

想法是在按 group1group2.

分组时对 B 不是 NA 的真实值(1 一次转换为整数)求和
library(dplyr)

df %>% group_by(group1, group2) %>% mutate(count = sum(!is.na(one)))
Source: local data frame [8 x 4]
Groups: group1, group2 [4]

     one group1 group2 count
  <fctr> <fctr> <fctr> <int>
1    one      A      C     1
2     NA      A      C     1
3     NA      A      C     1
4     NA      A      D     0
5     NA      B      E     1
6    two      B      E     1
7     NA      B      F     0
8     NA      B      F     0

我们不要忘记 base R 可以完成很多事情,尽管有时效率不如 data.tabledplyr:

df$count<-ave(as.integer(df$one),df[,2:3],FUN=function(x) sum(!is.na(x)))
#   one group1 group2 count
#1  one      A      C     1
#2 <NA>      A      C     1
#3 <NA>      A      C     1
#4 <NA>      A      D     0
#5 <NA>      B      E     1
#6  two      B      E     1
#7 <NA>      B      F     0
#8 <NA>      B      F     0