使用dplyr折叠重复行值并透视更宽的非重复行

A. dplyr 选项

foo %>%
  pivot_longer(cols = Var3:var4) %>%
  arrange(ID, Var1, Var2, Var5) %>%
  pivot_wider(id_cols = ID:Var2, values_from = value, names_from = Var5:name)

这给了

     ID Var1  Var2  RF_Var3 RF_var4 SJ_Var3 SJ_var4
  <dbl> <chr> <chr> <chr>   <chr>   <chr>   <chr>
1     1 A     B     X       S       Y       T
2     2 C     D     Z       U       <NA>    V

同样地,a data.table 选项与 dcase 可能也有帮助

dcast(
  melt(setDT(foo), id = c("ID", "Var1", "Var2", "Var5"))[order(ID, Var1, Var2, Var5)],
  ID + Var1 + Var2 ~ Var5 + variable,
  value = c("value")
)

这给了

   ID Var1 Var2 RF_Var3 RF_var4 SJ_Var3 SJ_var4
1:  1    A    B       X       S       Y       T
2:  2    C    D       Z       U    <NA>       V

library(tidyverse)

# note that Var4 is capital letter V, which is slightly different from your sample data
foo %>% pivot_wider(id_cols = c(ID:Var2), values_from = Var3:Var4, names_from = Var5, names_glue = "{Var5}_{.value}")

# A tibble: 2 x 7
     ID Var1  Var2  RF_Var3 SJ_Var3 RF_Var4 SJ_Var4
  <dbl> <chr> <chr> <chr>   <chr>   <chr>   <chr>  
1     1 A     B     X       Y       S       T      
2     2 C     D     Z       NA      U       V      

这里有一个多步骤的Base R方法,我相信可以用 reshape() :

# Subset of the unique values we would like to view the transposed data
# by: dimensions => data.frame
dimensions <- unique(foo[,1:3])

# Name of vector thats values we are to transpose: transpose_vec => character scalar
transpose_vec <- "Var5" 
 
# Names of vectors thats values are to be spread by the transposition: 
# vecs_to_spread => character vector
vecs_to_spread <- setdiff(names(foo), c(names(dimensions), transpose_vec))

# Foreach value of the transpose vec, repeat it by the number of vectors 
# we are going to spread it:  tpd_foo_vecs => character vector
tpd_foo_vecs <- unique(paste(rep(foo[,transpose_vec], each = length(vecs_to_spread)), 
                             vecs_to_spread, sep = "_"))

# Transpose the vectors to spread and flatten the values out into a vector: 
# vals => character vector
vals <- c(t(foo[,vecs_to_spread]))

# Name the values using the transposed vector: named_vals => named character vector
named_vals <- setNames(vals, rep(tpd_foo_vecs, length(vals)/length(tpd_foo_vecs)))

# Split the vector into a list, flatten into a data.frame and column bind 
# with the dimensions: res => data.frame
res <- cbind(dimensions, data.frame(split(named_vals, names(named_vals))))