在R中拆分字符串并逐列重新配置

在R中拆分字符串并逐列重新配置,r,string,R,String,我在R中有一个复杂的字符串拆分问题。在我的数据帧中,我有一个列,其中包含不同长度的字符串 Site Class A1 D2.13 A2 E1.4 A3 FA.1 A4 H2.14 A5 F AR G1 现在我想添加新的列来逐个字符地重新组合字符串,而点应该逐个字符地“忽略” Site Class1 Class2 Class3 Class4 A1 D D2 D2.1

我在R中有一个复杂的字符串拆分问题。在我的数据帧中,我有一个列,其中包含不同长度的字符串

   Site  Class
   A1    D2.13
   A2     E1.4
   A3     FA.1
   A4    H2.14
   A5        F
   AR       G1
现在我想添加新的列来逐个字符地重新组合字符串,而点应该逐个字符地“忽略”

   Site Class1 Class2 Class3 Class4
   A1      D     D2   D2.1  D2.13
   A2      E     E1   E1.4     NA
   A3      F     FA   FA.1     NA
   A4      H     H2   H2.1  H2.14
   A5      F     NA     NA     NA
   AR      G     G1     NA     NA
测试数据:

structure(list(Site = c("A1", "A2", "A3", "A4", "A5", "AR"), 
           Class = c("D2.13", "E1.4", "FA.1", "H2.14", "F","G1")), 
           class = "data.frame", row.names = c(NA, -6L)) 

轻松使用dplyr

df%>%rowwise()%>%mutate(Class1=substr(Class,1,1),
                        Class2=ifelse(nchar(strsplit(Class,"\\.")[[1]][1])==2,substr(Class,1,2),NA),
                        Class3=ifelse(nchar(strsplit(Class,"\\.")[[1]][2])>0,substr(Class,1,4),NA),
                        Class4=ifelse(nchar(Class)>4,Class,NA)
                        )

Source: local data frame [6 x 6]
Groups: <by row>

# A tibble: 6 x 6
  Site  Class Class1 Class2 Class3 Class4
  <chr> <chr> <chr>  <chr>  <chr>  <chr> 
1 A1    D2.13 D      D2     D2.1   D2.13 
2 A2    E1.4  E      E1     E1.4   NA    
3 A3    FA.1  F      FA     FA.1   NA    
4 A4    H2.14 H      H2     H2.1   H2.14 
5 A5    F     F      NA     NA     NA    
6 AR    G1    G      G1     NA     NA 
df%>%rowwise()%%>%变异(Class1=substr(类,1,1),
Class2=ifelse(nchar(strsplit(Class,“\\”)[[1]][1])==2,substr(Class,1,2),NA),
Class3=ifelse(nchar(strsplit(类“\\”[[1]][2])>0,substr(类,1,4),NA),
类别4=ifelse(nchar(类别)>4,类别,NA)
)
来源:本地数据帧[6 x 6]
组:
#一个tibble:6x6
场地类别1类别2类别3类别4
1 A1 D2.13 D D2.1 D2.13
2 A2 E1.4 E E1.4 NA
3 A3 FA.1 F FA.1 NA
4 A4 H2.14 H H2.1 H2.14
5 A5 F不适用不适用不适用不适用
6 AR G1 G G1 NA NA

一种方法是将
类按每个字符拆分,然后使用
Reduce
acculate=TRUE
将它们逐个粘贴在一起。然后,我们将它们的长度设置为最大长度,
rbind
cbind
返回到原始数据帧,即

l1 <- lapply(strsplit(as.character(df$Class), ''), function(i){i1 <- Reduce(paste0, i, accumulate = TRUE); 
                                                               i1 <- i1[!grepl('\\.$', i1)]; 
                                                               i1})
final_list <- lapply(l1, `length<-`, max(lengths(l1)))
cbind.data.frame(df$Site, do.call(rbind, final_list))

l1与@Sotos的想法类似(关键部分是
Reduce
strsplit
),但配置有所不同:

library(data.table)

df <- setDT(df)[, .(Class = Reduce(paste0, unlist(strsplit(as.character(Class), split = "")), accumulate = T)), 
                by = Site][
                  !grepl("\\.$", Class)][, nr := paste0("Class", rleid(Class)), by = Site]

dcast(df, Site ~ nr, value.var = "Class")
库(data.table)
df
library(data.table)

df <- setDT(df)[, .(Class = Reduce(paste0, unlist(strsplit(as.character(Class), split = "")), accumulate = T)), 
                by = Site][
                  !grepl("\\.$", Class)][, nr := paste0("Class", rleid(Class)), by = Site]

dcast(df, Site ~ nr, value.var = "Class")
   Site Class1 Class2 Class3 Class4
1:   A1      D     D2   D2.1  D2.13
2:   A2      E     E1   E1.4   <NA>
3:   A3      F     FA   FA.1   <NA>
4:   A4      H     H2   H2.1  H2.14
5:   A5      F   <NA>   <NA>   <NA>
6:   AR      G     G1   <NA>   <NA>