有条件地在dplyr中计数

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这是数据的样子：

memberorders = data.frame（MemID = c（'A'，'A'，'B'，'B'，'B' ，'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 to group_byMemID和总结周的值< = 2和< = 4（以查看在1-2周和1-4周内订购的成员数量。我目前的代码是：

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

我现在正在尝试在总结count2和count4中添加两个字段，这些字段可以计算每个条件的实例数（周< = 2和week< = 4）。

所需的输出是：

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））

我猜这只是一个调和功能的一点调整，

解决方案

尝试

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

I have some member order data that I would like to aggregate by week of order.

This is what the data looks like:

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))

I'm using dplyr to group_by "MemID" and summarize "value" for "week" <=2 and <=4 (to see how much each member ordered in weeks 1-2 and 1-4. The code I currently have is:

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

I'm now trying to add two more fields in summarize, count2 and count4, that would count the number of instances of each condition (week <=2 and week <=4).

The desired output is:

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))

I'm guessing it's just a little tweak of the sum function but I'm having trouble figuring it out.

解决方案

Try

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))