Question

我有一个大数据框，如下例所示。

          df <- data.frame(IND= seq(1:20), S = LETTERS[1:20], FA=c(0,0,133,0,2,2,2,0,0,4,4,4,6,6,0,0,0,4,2,8),
 MO = c(77,0,77,1,3,1,1,1,0,3,1,5,5,3,0,0,100,3,5,5)
 )

当FA和MO等于IND时，我需要创建两个新变量（SFA和SMO）。我需要以下输出

                   out<- df <- data.frame(IND= seq(1:20), 
                   S = LETTERS[1:20], 
                   FA=c(0,0,133,0,2,2,2,0,0,4,4,4,6,6,0,0,0,4,2,8), 
                   MO = c(77,0,77,1,3,1,1,1,0,3,1,5,5,3,0,0,100,3,5,5), 
                               SFA=c(0,0,133,0,"B","B","B",0,0,"D","D","D","F","F",0,0,0,"D","B","H"),
 SMO=c(77,0,77,"A","C","A","A","A",0,"C","A","E","E","C",0,0,100,"C","E","E"))

我尝试匹配变量并在合并后，但效果不佳。

感谢

Answer 1

要从S FA（MO）== IND获取相应的值，您可以使用match函数查找索引和来自S的子集为S[match(FA, IND)]（S[match(MO, IND)]），然后使用coalesce函数将匹配结果中的NA填充为原始向量中的值：

library(dplyr)
df %>% mutate(SFA = coalesce(as.character(S[match(FA, IND)]), as.character(FA)), 
              SMO = coalesce(as.character(S[match(MO, IND)]), as.character(MO)))

#   IND S  FA  MO SFA SMO
#1    1 A   0  77   0  77
#2    2 B   0   0   0   0
#3    3 C 133  77 133  77
#4    4 D   0   1   0   A
#5    5 E   2   3   B   C
#6    6 F   2   1   B   A
#7    7 G   2   1   B   A
#8    8 H   0   1   0   A
# ...

使用条件在数据框架中从现有变量创建新变量

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