在 dplyr 中有条件地计数

Question

我有一些会员订单数据，我想按订单周汇总。

数据是这样的：

memberorders=data.frame(MemID=c('A','A','B','B','B','C','C','D'),
             week = c(1,2,1,4,5,1,4,1),
             value = c(10,20,10,10,2,5,30,3))

我正在使用 dplyr group_by MemID 并总结 week<=2 和 week<=4 的“价值”（以查看每个成员在第 1 周内订购了多少- 2和1-4.我目前的代码是：

MemberLTV <- memberorders %>%
group_by(MemID) %>%
summarize(
sum2 = sum(value[week<=2]),
sum4 = sum(value[week<=4]))

我现在正尝试在汇总中添加两个字段，count2 和 count4，它们将计算每个条件（week <=2 和 week <=4）的实例数。

期望的输出是：

output  = data.frame(MemID = c('A','B','C','D'),
                 sum2 = c(30,10,5,3),
                 sum4 = c(30,20,35,3),
                 count2 = c(2,1,1,1),
                 count4 = c(2,2,2,1))

我猜这只是 sum 函数的一个小调整，但我很难弄明白。

Answer 1

使用 plyr 包可以做到

ddply(memberorders,.(MemID),
                    summarise, 
                    val1 = sum(value[week<=2]), 
                    val2 = sum(value[week<=4]),
                    val3 = length(value[week<=2]),
                    val4 = length(value[week<=4]))

  MemID val1 val2 val3 val4
1     A   30   30    2    2
2     B   10   20    1    2
3     C    5   35    1    2
4     D    3    3    1    1

Answer 2

尝试

 library(dplyr)
 memberorders %>% 
        group_by(MemID) %>% 
        summarise(sum2= sum(value[week<=2]), sum4= sum(value[week <=4]), 
                  count2=sum(week<=2), count4= sum(week<=4))

Answer 3

使用之前的两个想法并保持一致：

library(tidyverse)

MemberLTV_2 <- memberorders %>%
  group_by(MemID) %>%
    summarize(
      count2 = length(value[week<=2]),
      count4 = length(value[week<=4]),
      sum2 = sum(value[week<=2]),
      sum4 = sum(value[week<=4])
      )

在 dplyr 中有条件地计数

Conditionally Count in dplyr

r

dplyr

使用之前的两个想法并保持一致：