将多个列与Tidyr'组合；s通过引用相似的列名来联合

下面是一个简单数据帧的代码。我有一些混乱的数据，这些数据是用列因子类别导出的，这些类别分布在不同的列中

library(tidyr)
library(dplyr)
library(tidyverse)

---

Client像这样的东西？如果你有很多列

DF<-DF%>%unite(Sat,Satisfaction_Satisfied,Satisfaction_VerySatisfied,sep=" ")%>%
unite(Sex,Sex_M,Sex_F,sep=" ")

result我们可以使用
unite

result<-with(new.env(),{
  Client<-c("Client1","Client2","Client3","Client4","Client5")
  Sex_M<-c("Male","NA","Male","NA","Male")
  Sex_F<-c(" ","Female"," ","Female"," ")
  Satisfaction_Satisfied<-c("Satisfied"," "," ","Satisfied","Satisfied")
  Satisfaction_VerySatisfied<-c(" ","VerySatisfied","VerySatisfied"," "," ")
  CommunicationType_Email<-c("Email"," "," ","Email","Email")
  CommunicationType_Phone<-c(" ","Phone ","Phone "," "," ")
  x<-ls()
  categories<-unique(sub("(.*)_(.*)", "\\1", x))
  df<-setNames(data.frame( lapply(x, function(y) get(y))), x)
  for(nm in categories){
    df<-unite_(df, nm, x[contains(vars = x, match = nm)])
  }
  return(df)
})

Client CommunicationType    Satisfaction       Sex
1 Client1           Email_      Satisfied_      _Male
2 Client2           _Phone   _VerySatisfied Female_NA
3 Client3           _Phone   _VerySatisfied     _Male
4 Client4           Email_      Satisfied_  Female_NA
5 Client5           Email_      Satisfied_      _Male


对于多个案例，也许是这样

library(tidyverse)
DF %>% 
    unite(Sat, matches("^Sat"))

gather（DF，Var，Val，-Client，na.rm=TRUE）%>%
分离（Var，分为=c（“Var1”、“Var2”））%>%
分组依据（客户，Var1）%>%
摘要（Val=paste（Val[！（is.na（Val）| Val==“”），collapse=“”）%>%
排列（Var1，Val）
#客户沟通类型满意度性别
#*                           
#1名客户1封邮件满意男性
#2个客户2个电话非常满意女性
#3个客户3个电话非常满意男性
#4位客户4封电子邮件满意女性
#5位客户5封邮件满意男性
DF%>%unite（Sat，包含（“Sat”））
？
DF%>%unite（Sat，匹配“^Sat”）
library(tidyverse)
DF %>% 
    unite(Sat, matches("^Sat"))

gather(DF, Var, Val, -Client, na.rm = TRUE) %>%
        separate(Var, into = c("Var1", "Var2")) %>%
        group_by(Client, Var1) %>% 
        summarise(Val = paste(Val[!(is.na(Val)|Val=="")], collapse="_")) %>%
        spread(Var1, Val)
#  Client CommunicationType  Satisfaction    Sex
#*   <chr>             <chr>         <chr>  <chr>
#1 Client1             Email     Satisfied   Male
#2 Client2             Phone VerySatisfied Female
#3 Client3             Phone VerySatisfied   Male
#4 Client4             Email     Satisfied Female
#5 Client5             Email     Satisfied   Male