根据R中的分隔符将单列转换为多列

Question

I have the following dataframe:

ID Parts
-- -----
1  A:B::
2  X2:::
3  ::J4:
4  A:C:D:G4:X6

And I would like the convert the Parts column into multiple columns by the : delimiter. so it should look like:

ID A  B  X2  J4  C  D  G4  X6 ........
-- -  -  --  --  -  -  --  -- 
1  A  B  na  na  na na na  na
2  na na X2  na  na na na  na
3  na na na  J4  na na na  na
4  A  na na  na  C  D  G4  X6

where there I would not know the number of potential columns in advance.

I have met my match on this one - strsplit() by delim I can do but only with fixed number of entities in the Parts column

Answer 1

You can use a combination of tidyr::seperate , tidyr::pivot_wider , and tidyr::pivot_longer . First you can still use strsplit to determine the number of columns to split Parts into not the number of unique values ( How it works ):

library(dplyr)
library(tidyr)
library(stringr)

n_col <- max(stringr::str_count(df$Parts, ":")) + 1

df %>% 
  tidyr::separate(Parts, into = paste0("col", 1:n_col), sep = ":") %>% 
  dplyr::mutate(across(everything(), ~dplyr::na_if(., ""))) %>% 
  tidyr::pivot_longer(-ID) %>% 
  dplyr::select(-name) %>% 
  tidyr::drop_na() %>% 
  tidyr::pivot_wider(id_cols = ID,
                     names_from = value)


     ID A     B     X2    J4    C     D     G4    X6   
  <int> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1     1 A     B     NA    NA    NA    NA    NA    NA   
2     2 NA    NA    X2    NA    NA    NA    NA    NA   
3     3 NA    NA    NA    J4    NA    NA    NA    NA   
4     4 A     NA    NA    NA    C     D     G4    X6 

---

How it works

You do not need to know the number of unique values with this code -- the pivots take care of that. What you do need to know is how many new columns Parts will be split into with seperate . That's easy to do by counting the number of delimiters and adding one with str_count . This way you have the appropriate number of columns to seperate Parts into by your delimiter.

This is because pivot_longer will create a two column dataframe with repeated ID and a column with the delimited values of Parts -- an ID , Parts pairing. Then when you use pivot_wider the columns are automatically created for each unique value of Parts and the value is retained within the column. This function automatically fills with NA where an ID and Parts combination is not found.

Try running this pipe by pipe to better understand if need be.

---

Data

lines <- "
ID Parts
1  A:B::
2  X2:::
3  ::J4:
4  A:C:D:G4:X6
"

df <- read.table(text = lines, header = T)

Answer 2

Could the seperate function from tidyr be what you are looking for?

https://tidyr.tidyverse.org/reference/separate.html

It might require some fancy regex implementation, but could potentially work.