计算一个数据框中的发生次数，将结果输入到另一个数据框中

Question

我有两个数据框： households和individuals。

这是households：

structure(list(ID = 1:5), class = "data.frame", row.names = c(NA, 
-5L))

这是individuals：

structure(list(ID = c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 
3L, 4L, 4L, 4L, 4L, 5L, 5L), Yesno = c(1L, 0L, 1L, 0L, 0L, 0L, 
1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L)), class = "data.frame", row.names = c(NA, 
-17L))

我试图添加一个新列来计算变量等于 1households的次数，并按 分组结果。YesnoID

我努力了

households$Count <- as.numeric(ave(individuals$Yesno[individuals$Yesno == 1], households$ID, FUN = count))

households应该看起来像这样：

ID  Count
1   2
2   3
3   0
4   2
5   1

Answer 1

选项 1：以 R 为基础

使用merge和aggregate

aggregate(Yesno ~ ID, merge(households, individuals), FUN = sum)
#  ID Yesno
#1  1     2
#2  2     3
#3  3     0
#4  4     2
#5  5     1

选项 2：有dplyr

使用left_join和group_by+summarise

library(dplyr)
left_join(households, individuals) %>%
    group_by(ID) %>%
    summarise(Count = sum(Yesno))
#Joining, by = "ID"
## A tibble: 5 x 2
#     ID Count
#  <int> <int>
#1     1     2
#2     2     3
#3     3     0
#4     4     2
#5     5     1

选项 3：带有data.table

library(data.table)
setDT(households)
setDT(individuals)
households[individuals, on = "ID"][, .(Count = sum(Yesno)), by = ID]
#   ID Count
#1:  1     2
#2:  2     3
#3:  3     0
#4:  4     2
#5:  5     1

样本数据

households <- structure(list(ID = 1:5), class = "data.frame", row.names = c(NA,
-5L))

individuals <- structure(list(ID = c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,
3L, 4L, 4L, 4L, 4L, 5L, 5L), Yesno = c(1L, 0L, 1L, 0L, 0L, 0L,
1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L)), class = "data.frame", row.names = c(NA,
-17L))