r语言 - 应用以及哪个函数需要操作员错误

Question

我有一个参考表：

ref <- data.frame("Strong"=c("A","A","B","B","C","C","D"),
              "Medium"=c("A","B","B","C","C","D","D"),
              "Moderate"=c("B","C","C","C","D","D","D"),
              "Weak"=c("C","C","D","D","D","D","D"))
rownames(ref) <- c("WS1","WS2","WS3","WS4","WS5","WS6","WS7")

还有一个大dataframe(示例如下(：

df <- data.frame("Rad"=c("Weak","Weak","Weak","Moderate","Moderate"), "Wind"=c("WS4","WS3","WS3","WS2","WS4"))

我需要从参考表中查找Wind值和df Rad值ref。为此，我使用以下代码检索索引，然后使用这些索引值从ref复制值：

df$x <- apply(df,1,function(x){which(colnames(ref) == df[x,"Rad"])})
df$x <- apply(df,1,function(x){which(colnames(ref) == x$Rad)})
df$y <- apply(df,1,function(x){which(rownames(ref) == df[x,"Wind"])})
df$y <- apply(df,1,function(x){which(rownames(ref) == x$Wind)})

预期输出如下所示：

   Rad     Wind  PG
 1 Weak     WS4  D
 2 Weak     WS3  D
 3 Weak     WS3  D
 4 Moderate WS2  C
 5 Moderate WS4  C

上面的代码有效，但存在问题：

• 我不应该写"两次"行，但是如果我只运行第二行，代码将无法运行。
• 第一行没有达到预期的效果(而且不应该这样做，因为语法是错误的(，但是，同样，如果我不先使用"失败"的第二行，第二行将无法运行
• 最后，虽然这有效，但我很确定还有其他更简单的方法可以完成我正在做的事情。任何提示将不胜感激！

Answer 1

另一种

使用 data.table 的方法。应该快速运行，即使在大型数据集上也是如此。通过@IceCreamToucan使用与解决方案相同的逻辑，但保留在data.table .

解释：使用熔融ref表，对df执行更新联接。

library( data.table )
setDT(df)[ melt( setDT( ref, keep.rownames = TRUE ), id.vars = "rn" ), 
           PG := i.value, 
           on = .( Wind == rn, Rad == variable )][]
#         Rad Wind PG
# 1:     Weak  WS4  D
# 2:     Weak  WS3  D
# 3:     Weak  WS3  D
# 4: Moderate  WS2  C
# 5: Moderate  WS4  C

Answer 2

我们可以分别用RAD和WIND列以及ref的子集match rownames和colnames ref。

df$PG <- ref[cbind(match(df$Wind, rownames(ref)), match(df$Rad, colnames(ref)))]
df
#       Rad Wind PG
#1     Weak  WS4  D
#2     Weak  WS3  D
#3     Weak  WS3  D
#4 Moderate  WS2  C
#5 Moderate  WS4  C

Answer 3

library(tidyverse)
library(data.table) # for melt
ref_long <- 
  ref %>% 
    rownames_to_column('row') %>% 
    melt('row')
df %>% 
  left_join(ref_long, by = c('Rad' = 'variable', 'Wind' = 'row'))
#        Rad Wind value
# 1     Weak  WS4     D
# 2     Weak  WS3     D
# 3     Weak  WS3     D
# 4 Moderate  WS2     C
# 5 Moderate  WS4     C