如何根据另一列删除重复值？

Question

我有一个如下所示的数据集：

   Study_ID       Stage
1       100 Early Stage
2       100      Stable
3       200      Stable
4       300 Early Stage
5       400 Early Stage
6       400      Stable
7       500 Early Stage
8       500      Stable
9       600      Stable
10      700 Early Stage

我想删除任何重复的研究is，但保留条目的病人是“稳定的”。换句话说，我想删除每一个重复的学习ID，病人是‘早期’。

我想要的输出应该如下所示：

  Study_ID       Stage
1      100      Stable
2      200      Stable
3      300 Early Stage
4      400      Stable
5      500      Stable
6      600      Stable
7      700 Early Stage

我该怎么做呢？

可复制的数据：

data<-data.frame(Study_ID=c("100","100","200","300","400","400","500","500","600","700"),Stage=c("Early Stage","Stable","Stable","Early Stage","Early Stage","Stable","Early Stage","Stable","Stable","Early Stage"))

Answer 1

library(dplyr)

data %>% 
  group_by(Study_ID) %>% 
  filter(!(n() > 1 & Stage != "Stable"))
#> # A tibble: 7 × 2
#> # Groups:   Study_ID [7]
#>   Study_ID Stage      
#>   <chr>    <chr>      
#> 1 100      Stable     
#> 2 200      Stable     
#> 3 300      Early Stage
#> 4 400      Stable     
#> 5 500      Stable     
#> 6 600      Stable     
#> 7 700      Early Stage

编辑1

为了确保您没有重复的行(正如@jay.sf所指出的，您可以执行以下操作(混乱))：

library(dplyr)

dat %>% 
  group_by(Study_ID) %>% 
  filter(!(n() > 1 & Stage != "Stable")) %>% 
  summarise(Stage = first(Stage))
#> # A tibble: 7 × 2
#>   Study_ID Stage      
#>      <int> <chr>      
#> 1      100 Stable     
#> 2      200 Stable     
#> 3      300 Early Stage
#> 4      400 Stable     
#> 5      500 Stable     
#> 6      600 Stable     
#> 7      700 Early Stage

Answer 2

使用by。我在数据中添加了一个带有两个“稳定”的案例，作为可能的特例。

by(dat, dat$Study_ID, \(x) {
  if (any(grepl('Stable', x$Stage))) {
    unique(x[x$Stage == 'Stable', ])
  } else {
    unique(x)
  }
}) |> do.call(what=rbind)
#     Study_ID       Stage
# 100      100      Stable
# 200      200      Stable
# 300      300 Early Stage
# 400      400      Stable
# 500      500      Stable
# 600      600      Stable
# 700      700 Early Stage

或者使用舞台as.factor和ave !duplicated max。

transform(dat, x=as.numeric(as.factor(Stage))) |> 
  subset(as.logical(ave(x, Study_ID, FUN=\(x) x == max(x) & !duplicated(x))) , -x)
#    Study_ID       Stage
# 2       100      Stable
# 3       200      Stable
# 4       300 Early Stage
# 6       400      Stable
# 8       500      Stable
# 9       600      Stable
# 11      700 Early Stage

注意，这是因为“早期”在字母表中“稳定”之前，否则使用factor并在参数中定义levels=顺序。

数据：

dat <- structure(list(Study_ID = c(100L, 100L, 200L, 300L, 400L, 400L, 
500L, 500L, 600L, 600L, 700L), Stage = c("Early Stage", "Stable", 
"Stable", "Early Stage", "Early Stage", "Stable", "Early Stage", 
"Stable", "Stable", "Stable", "Early Stage")), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11"))