如何检测数据集中每个ID的多值观测值?

Question

我有一个包含3个不同变量的数据集:

id   gender phase
a1     m      1
a1     m      2
a1     m      3
b2     m      1
b2     f      2
b2     m      3
c3     f      1
c3     f      2
c3     f      3
...

请注意，对于id==b2, phase==2，性别被意外地标记为"f"，它应该与其他阶段一致，性别=="m"因为在研究阶段性别是不能改变的。因此，如果我想运行一个R代码来检测哪些id有这样的问题，我应该如何实现这个目标?非常感谢~~

Answer 1

对于dplyr，您可以使用n_distinct()检测哪些id具有一个以上的性别。

library(dplyr)
df %>%
group_by(id) %>%
filter(n_distinct(gender) > 1) %>%
ungroup()
# # A tibble: 3 × 3
#   id    gender phase
#   <chr> <chr>  <int>
# 1 b2    m          1
# 2 b2    f          2
# 3 b2    m          3

Answer 2

您可以使用lag检查列中的值是否发生了变化，filter检查id是否有这样的变化:

df <- read.table(text="id   gender phase
a1     m      1
a1     m      2
a1     m      3
b2     m      1
b2     f      2
b2     m      3
c3     f      1
c3     f      2
c3     f      3", header = TRUE)
library(dplyr)
df %>%
group_by(id) %>%
filter(any(gender != lag(gender)))
#> # A tibble: 3 × 3
#> # Groups:   id [1]
#>   id    gender phase
#>   <chr> <chr>  <int>
#> 1 b2    m          1
#> 2 b2    f          2
#> 3 b2    m          3

^{由reprex包(v2.0.1)创建于2022-07-13}

Answer 3

id<-c("a1","a1","a1","b2","b2","b2","c3","c3","c3")
gender<-c("m","m","m","m","f","m","f","f","f")
phase<-c(1,2,3,1,2,3,1,2,3)
mydata<-data.frame(id,gender,phase)
mydata[mydata$id%in%c("a1","b2"),"gender"]<-"m"
mydata[mydata$id%in%c("c3"),"gender"]<-"f"
mydata