R确定一列中是否存在多个值,如果为true,则将mutate连接起来 数据

问题描述

找不到某种解决方案,需要一些指导。

这是我拥有的数据集的一个示例:

     ID   Rank    Date       Date2.      Group   Group2
1   5678   1    2000-01-01   2010-05-02    A      A
2   5678   2    2010-05-02   2010-05-02    A      A
3   1234   1    2000-01-01   2015-06-03    B      A&B
4   1234   2    2015-06-03   2015-06-03    A      A&B

我想按ID分组,并在“组”列中确定该ID是否存在多个值。如果是这样,将它们连接在一起。

Group2是基于分组ID并查看Group中是否存在多个值的所需输出。我正在使用dplyr,但不确定从这里去哪里

df <- df %>% group_by(ID) %>% mutate(Group2 = if else(?))

解决方法

我认为最简单的方法是unique函数。此函数创建一个具有给定向量的不同值的向量。

> df %>%
   group_by(ID)%>%
   mutate(Group2=paste(sort(unique(Group)),collapse="&"))

# A tibble: 4 x 3
# Groups:   ID [2]
     ID Group Group2
  <dbl> <chr> <chr> 
1  5678 A     A     
2  5678 A     A     
3  1234 B     A&B   
4  1234 A     A&B   
,

带有data.table

的选项
library(data.table)
setDT(df)[,Group2 := paste(sort(unique(Group)),collapse="&"),ID]

数据

df <- structure(list(ID = c(5678L,5678L,1234L,1234L),Rank = c(1L,2L,1L,2L),Date = c("2000-01-01","2010-05-02","2000-01-01","2015-06-03"),Date2. = c("2010-05-02","2015-06-03",Group = c("A","A","B","A")),row.names = c("1","2","3","4"),class = "data.frame")
,

继续您的代码,我会尝试:

df %>%
    group_by(ID) %>%
    mutate(Group2 = ifelse(n_distinct(Group) == 1,as.character(Group),paste0(sort(Group),collapse = "&")))

# A tibble: 4 x 6
# Groups:   ID [2]
     ID  Rank Date       Date2.     Group Group2
  <int> <int> <fct>      <fct>      <fct> <chr> 
1  5678     1 2000-01-01 2010-05-02 A     A     
2  5678     2 2010-05-02 2010-05-02 A     A     
3  1234     1 2000-01-01 2015-06-03 B     A&B   
4  1234     2 2015-06-03 2015-06-03 A     A&B   
,

我建议采用下一种方法:

library(dplyr)
#Code
df %>% group_by(ID) %>%
  arrange(ID,Group) %>%
  #Identify unique elements
  mutate(NUnique=n_distinct(Group)) %>%
  mutate(Group2=ifelse(NUnique>1,paste0(Group,collapse = '&'),Group))

输出:

# A tibble: 4 x 7
# Groups:   ID [2]
     ID  Rank Date       Date2.     Group NUnique Group2
  <int> <int> <chr>      <chr>      <chr>   <int> <chr> 
1  1234     2 2015-06-03 2015-06-03 A           2 A&B   
2  1234     1 2000-01-01 2015-06-03 B           2 A&B   
3  5678     1 2000-01-01 2010-05-02 A           1 A     
4  5678     2 2010-05-02 2010-05-02 A           1 A  

使用了一些数据:

#Data
df <- structure(list(ID = c(5678L,class = "data.frame")
,

基本R选项

within(df,Group2 <- ave(Group,ID,FUN = function(x) ifelse(length(unique(x))==1,x,paste0(x,collapse = "&"))))

给予

    ID Rank       Date     Date2. Group Group2
1 5678    1 2000-01-01 2010-05-02     A      A
2 5678    2 2010-05-02 2010-05-02     A      A
3 1234    1 2000-01-01 2015-06-03     B    B&A
4 1234    2 2015-06-03 2015-06-03     A    B&A