1

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"

投射到宽

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一个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

我试图使其自动化但失败了（所有 c 都应该有相同的标签，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，但不知道如何合并它。任何建议，将不胜感激。谢谢！

4

1 回答 1

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包含在最后id我需要重写id。如果更改d为e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]])
}
于 2019-03-26T10:42:01.707 回答