如何将属性从一个数据帧复制到另一个数据帧或将属性重新分配给新转置的数据帧 - R

Question

转置数据后，我想重新分配已删除的属性。这也适用于将属性从一个数据帧复制到另一个数据帧。或者在变异后复制属性，等等，它们被丢弃的地方。

 library(reshape2)

 df <- data.frame(id = c(1,2,3,4,5), 
                  time = c(11, 22,33,44,55),
                  c  = c(1,2,3,5,5),
                  d = c(4,2,5,4,NA))

attr(df$id,"label")<- "label"
attr(df$time,"label")<- "label2"
attr(df$c,"label")<- "something here"
attr(df$d,"label")<- "count of something"
str(df)

 str(df)
 data.frame':   5 obs. of  4 variables:
 $ id  : num  1 2 3 4 5
  ..- attr(*, "label")= chr "label"
 $ time: num  11 22 33 44 55
  ..- attr(*, "label")= chr "label2"
 $ c   : num  1 2 3 5 5
  ..- attr(*, "label")= chr "something here"
 $ d   : num  4 2 5 4 NA
  ..- attr(*, "label")= chr "count of something"

投射到广角

dfwide<- recast(df,id~variable +time, 
            id.var = c("id","time"))

通常的属性丢失消息：

   Warning message:
     attributes are not identical across measure variables; they will be dropped 

 str(dfwide)
'data.frame':   5 obs. of  11 variables:
 $ id  : num  1 2 3 4 5
 $ c_11: num  1 NA NA NA NA
 $ c_22: num  NA 2 NA NA NA
 $ c_33: num  NA NA 3 NA NA
 $ c_44: num  NA NA NA 5 NA
 $ c_55: num  NA NA NA NA 5
 $ d_11: num  4 NA NA NA NA
 $ d_22: num  NA 2 NA NA NA
 $ d_33: num  NA NA 5 NA NA
 $ d_44: num  NA NA NA 4 NA
 $ d_55: num  NA NA NA NA NA

使用mostattributes 可以在数据帧之间复制属性，但是对于许多列名的迭代，我无法弄清楚或考虑如何以不同的方式有效地映射它，一个一个地保存。

 mostattributes(dfwide$c_11)<-attributes(df$c)
 mostattributes(dfwide$c_22)<-attributes(df$c)
 > str(dfwide)
 'data.frame':  5 obs. of  11 variables:
  $ id  : num  1 2 3 4 5
  $ c_11: num  1 NA NA NA NA
  ..- attr(*, "label")= chr "something here"
  $ c_22: num  NA 2 NA NA NA
  ..- attr(*, "label")= chr "something here"
  $ c_33: num  NA NA 3 NA NA

我试图让它自动化但失败了（所有 c 应该有相同的标签，d 应该有相同的标签）：

#extract arguments
dlist<-enframe(names(df))%>%
   slice(-1,-2)%>%
   pull(., value)
 dlist

 dlistw<-enframe(names(dfwide))%>%
  slice(-1)%>%
  pull(., value)
 dlistw

#function
mostatt<- function(var1, var2) {
  mostattributes(dfwide[[var1]])<<-attributes(df[[var2]])
}

mapply(mostatt,dlistw,dlist)
str(dfwide)

'data.frame':   5 obs. of  11 variables:
 $ id  : num  1 2 3 4 5
 $ c_11: num  1 NA NA NA NA
  ..- attr(*, "label")= chr "something here"
 $ c_22: num  NA 2 NA NA NA
  ..- attr(*, "label")= chr "count of something"
 $ c_33: num  NA NA 3 NA NA
  ..- attr(*, "label")= chr "something here"
 $ c_44: num  NA NA NA 5 NA
  ..- attr(*, "label")= chr "count of something"
 $ c_55: num  NA NA NA NA 5
  ..- attr(*, "label")= chr "something here"
 $ d_11: num  4 NA NA NA NA
  ..- attr(*, "label")= chr "count of something"
 $ d_22: num  NA 2 NA NA NA
  ..- attr(*, "label")= chr "something here"
 $ d_33: num  NA NA 5 NA NA
  ..- attr(*, "label")= chr "count of something"
 $ d_44: num  NA NA NA 4 NA
  ..- attr(*, "label")= chr "something here"
 $ d_55: num  NA NA NA NA NA
  ..- attr(*, "label")= chr "count of something"

我认为使用tidyselect starts_with 可能值得一试，但不确定如何合并它。任何建议，将不胜感激。谢谢！

Answer 1

这是一个选项：

for(i in (setdiff(colnames(df), "id"))){
  for(x in colnames(dfwide)[(grepl(i, colnames(dfwide)))])
      mostattributes(dfwide[[x]]) <- attributes(df[[i]])
}
mostattributes(dfwide$id) <- attributes(df$id) 

因为d 包含在id 中，所以最后需要重写id。 如果将d 更改为e 会更简单：

df <- data.frame(id = c(1,2,3,4,5), 
                 time = c(11, 22,33,44,55),
                 c  = c(1,2,3,5,5),
                 e = c(4,2,5,4,NA))


attr(df$id,"label")<- "label"
attr(df$time,"label")<- "label2"
attr(df$c,"label")<- "something here"
attr(df$e,"label")<- "count of something"
str(df)

dfwide<- recast(df,id~variable +time, 
                id.var = c("id","time"))

for(i in (colnames(df))){
  for(x in colnames(dfwide)[(grepl(i, colnames(dfwide)))])
    mostattributes(dfwide[[x]]) <- attributes(df[[i]])
}