R-如何跨多个数据帧应用 for 循环？

Question

在 R 中，我有 3 个数据框，它们类似于我在下面提供的示例版本。 第一个Data是主要数据集， TW和UW数据帧具有与Data类似的变量（ MN-mapping_for_N ），然后每个变量（ N48 ）有 1000 个不同的值。我在这里提供了 3 个。

Data<-matrix(c(4720,44.29,"Work or Private Clinic",N48,2659,55.05,"Hospital",N1,1612,59.99,"No Care",N48),ncol = 4,byrow=TRUE)
colnames(Data)<-c("studyid", "Pred_ex", "wherecare", "MN-mapping_for_N")
Data<-data.frame(Data)


TW<-matrix(c("N48",0.07,0.08,0.09,"N1",0.10,0.11,0.12,"N2",0.02,0.03,0.04,"N3",0.04,0.05,0.06),ncol = 4, byrow = TRUE)
colnames(TW)<-c("MN-mapping_for_N","draw1","draw2","draw3")`
TW<-data.frame(TW)

    UW<-matrix(c("N48",0.71,0.81,0.91,"N1",0.11,0.111,0.131,"N2",0.021,0.031,0.041,"N3",0.041,0.051,0.061),ncol = 4, byrow = TRUE)
colnames(UW)<-c("MN-mapping_for_N","draw1","draw2","draw3")`
UW<-data.frame(UW)

我的目标是创建一个新列，其值来自UT和TW数据中随机选择的列，要从中提取的正确列取决于Data$wherecare的值

我一直在使用 dplyr 和 match 函数的组合以及我自己创建的几个函数。 目前这看起来像

drawselect<-function(x) {
samplepick<-sample(2:1001,1)
select(x,1,num_range("draw",samplepick))
 }

DALY_FX_LT_NR<-function(x){
 draw_T_DW<-drawselect(TW)
  draw_UT_DW<-drawselect(UW)
  drawnames.TW<-colnames((draw_T_DW))
  drawnames.UT<-colnames(draw_UT_DW)
  UT.draw<-drawnames.UT[2]
  T.draw<-drawnames.T[2]
  print(UT.draw)       
  print(T.draw)
  newdf<-x %>% mutate(DW=NA)
  for(i in 1:nrow(newdf)){
if(newdf$wherecare[i]!= "No Care"){
  newdf$DW=draw_T_DW[,2][match(newdf$`MN-mapping_for_N`,draw_T_DW$`MN-mapping_for_N`)]
  next
}else if(newdf$wherecare[i]=="No Care"){
  newdf$DW=draw_UT_DW[,2][match(newdf$`MN-mapping_for_N`,draw_UT_DW$`MN-mapping_for_N`[i])]
}
 }
newdf
}

代码运行，但我似乎无法让它实际逐行迭代以使其从正确的数据帧中提取绘制值（即在通过drawselect函数后的UT或TW ）。

所以我得到的看起来像：

-------------------------------------------------------------


studyid   Pred_ex        wherecare         MN-mapping_for_N     DW
--------- --------- ---------------------- ------------------ ------
  4720      44.29   Work or Private Clinic        N48          0.08

  2659      55.05          Hospital                N1          0.11

  1612      59.99          No Care                N48          0.08
--------------------------------------------------------------------

当我应该得到：

     studyid   Pred_ex        wherecare         MN-mapping_for_N    DW
    --------- --------- ---------------------- ------------------ ------
      4720      44.29   Work or Private Clinic        N48          0.08

      2659      55.05          Hospital                N1          0.11

      1612      59.99          No Care                N48          0.81
    --------------------------------------------------------------------

关键的区别是右下角的 0.81，在样本数据中没什么大不了的，但实际数据有几百行长，所以我想让函数“正确决定”从哪个数据集提取。 该值可以是 0.71、0.81 或 0.91， N48任何UT值都可以使用。

最终目标是通过乘以Pred_ex列在计算中使用该值，我可以这样做，然后多次重新运行此函数以引导数据，但直到我能让这些if语句正常工作我不能去做。 我也尝试使用dplyr::left_join来匹配这些，并且在条件语句不起作用时遇到了类似的问题。 我认为按照其编写的match函数会更好地工作，但我当然对任何事情都持开放态度。

任何帮助是极大的赞赏。

此外，感谢堆栈溢出的每个人，阅读您对其他问题的回答是我走到这一步的主要原因。

Answer 1

所以你不需要一个新函数（我保留了drawselect ，你可以执行以下操作：

for (i in 1:nrow(Data)){
    if (Data$wherecare[i] != "No Care"){
        Data$DW[i]<- drawselect(TW)[which(drawselect(TW)$MN.mapping_for_N == as.character(Data$MN.mapping_for_N[i])), 2]
    } else {
        Data$DW[i]<- drawselect(UW)[which(drawselect(UW)$MN.mapping_for_N == as.character(Data$MN.mapping_for_N[i])), 2]
    }
}

> Data
  studyid Pred_ex              wherecare MN.mapping_for_N   DW
1    4720   44.29 Work or Private Clinic              N48 0.08
2    2659   55.05               Hospital               N1 0.11
3    1612   59.99                No Care              N48 0.81

如果您想将所有内容包装在一个函数中（包括drawselect ），请尝试以下方法：

    DALY_FX_LT_NR<-function(x, y, z){ #x would be Data, y would be TW, z would be UW
 samplepick<-sample(2:(ncol(y)-1),1) 
 for (i in 1:nrow(x)){
    if (x$wherecare[i] != "No Care"){
        x$DW[i]<- y[which(y$MN.mapping_for_N==as.character(x$MN.mapping_for_N[i])), paste0("draw", samplepick)]
    } else {
        x$DW[i]<- z[which(z$MN.mapping_for_N==as.character(x$MN.mapping_for_N[i])), paste0("draw", samplepick)]
    }
  }
  return(x)
}

> DALY_FX_LT_NR(x = Data, y = TW, z = UW)
  studyid Pred_ex              wherecare MN.mapping_for_N   DW
1    4720   44.29 Work or Private Clinic              N48 0.09
2    2659   55.05               Hospital               N1 0.12
3    1612   59.99                No Care              N48 0.91