Extract and create columns from character strings separated by "

I'm trying to extract the character string "segments" separated by an "_" and make them their own columns. I know how to combine many columns to a single one, but I'm curious how going backwards works (single column to many).

My data:

structure(list(REF = c("M120", "M70", "M100", "M94", "M74", "M54", 
"M99", "M09", "M111", "M17"), SEAS = c("DRY", "DRY", "DRY", "WET", 
"DRY", "WET", "DRY", "WET", "WET", "WET"), YR = c(2019, 2008, 
2007, 2021, 2019, 2015, 2020, 2017, 2019, 2012)), row.names = c(NA, 
-10L), class = c("tbl_df", "tbl", "data.frame"))

df$REF_YR_SEAS <- paste(df$REF, df$YR, df$SEAS, sep = "_") # Combining many columns to one

I'm aware of:

df$REF2 <- sub("\\_.*", "", df$REF_YR_SEAS) # Extract everything to the left of "_"?

But, don't quite understand how to use the syntax to get the remaining pieces of the character string to make columns "YR" and "SEAS" from "REF_YR_SEAS".

CodePudding user response：

We can use separate() from the tidyr package to do this easily:

library(tidyr)
separate(data = df, 
         col = REF_YR_SEAS, 
         remove = FALSE,
         c("ref_new","yr_new","sea_new"), 
         sep = "_")
#> # A tibble: 10 x 7
#>    REF   SEAS     YR REF_YR_SEAS   ref_new yr_new sea_new
#>    <chr> <chr> <dbl> <chr>         <chr>   <chr>   <chr> 
#>  1 M120  DRY    2019 M120_2019_DRY M120    2019    DRY   
#>  2 M70   DRY    2008 M70_2008_DRY  M70     2008    DRY   
#>  3 M100  DRY    2007 M100_2007_DRY M100    2007    DRY   
#>  4 M94   WET    2021 M94_2021_WET  M94     2021    WET   
#>  5 M74   DRY    2019 M74_2019_DRY  M74     2019    DRY   
#>  6 M54   WET    2015 M54_2015_WET  M54     2015    WET   
#>  7 M99   DRY    2020 M99_2020_DRY  M99     2020    DRY   
#>  8 M09   WET    2017 M09_2017_WET  M09     2017    WET   
#>  9 M111  WET    2019 M111_2019_WET M111    2019    WET   
#> 10 M17   WET    2012 M17_2012_WET  M17     2012    WET