Separate field values into columns

[Boboye.x]

# A tibble: 6 × 7
     ID alcohol               germ_aversion time1_determina…¹ time2…² region decis…³
  <dbl> <chr>                         <dbl>             <dbl>   <dbl> <chr>    <dbl>
1     1 Group 2: non-drinkers            16                 5      10 Group…      16
2     2 Group 1: drinkers                22                15      19 Group…      22
3     3 Group 1: drinkers                20                23      27 Group…      20
4     4 Group 2: non-drinkers            11                16      18 Group…      11
5     5 Group 2: non-drinkers            22                21      26 Group…      22
6     6 Group 1: drinkers                14                 8       6 Group…      14

• I want to separate drinkers and non-drinkers in the alcohol column
• I have tried using separate(df, alcohol, into = c("drinkers", and "non-drinkers"), sep = " ") but got an eeror.
• How do i go about it please ?
• After the manipulation, the alcohol column should be drinkers and non drinkers only

[matanhakim]

Could you please add an example of how the data frame should look like after the desired manipulation?

[Flm]

Is this what you want?

df <- tibble(alcohol = c("Group 2: non-drinkers","Group 1: drinkers","Group 1: drinkers", "Group 2: non-drinkers", "Group 2: non-drinkers","Group 1: drinkers"))

df %>% 
  mutate(alcohol2 = case_when(alcohol == "Group 1: drinkers" ~ "drinkers",
                              alcohol == "Group 2: non-drinkers" ~ "non-drinkers"))

Produces:

A tibble: 6 × 2
  alcohol               alcohol2    
  <chr>                 <chr>       
1 Group 2: non-drinkers non-drinkers
2 Group 1: drinkers     drinkers    
3 Group 1: drinkers     drinkers    
4 Group 2: non-drinkers non-drinkers
5 Group 2: non-drinkers non-drinkers
6 Group 1: drinkers     drinkers    

[Boboye.x]

Ah yes Thank you, Thank you!
Alcohol2 column has just drinkers and non-drinkers string values that corresponds with initial alcohol column of group 1 and group 2

[Flm]

@Boboye.x

Alcohol2 column has just drinkers and non-drinkers string values that corresponds with initial alcohol column of group 1 and group 2

That's right, that's it

[FactOREO]

Here are two additional approaches:

Data <- data.frame(
  id = 1:10,
  alcohol = sample(c('Group 1: drinkers','Group 2: non-drinkers'),10,TRUE)
)
# using tidyr::separate() as you already tried
library('tidyr'); library('dplyr')

Data |>
  separate(col = alcohol, sep = "Group [1-2]{1}:", into = c('col1','alcohol'), remove = TRUE) |>
  select(-col1)
#>    id       alcohol
#> 1   1      drinkers
#> 2   2      drinkers
#> 3   3      drinkers
#> 4   4  non-drinkers
#> 5   5      drinkers
#> 6   6  non-drinkers
#> 7   7      drinkers
#> 8   8      drinkers
#> 9   9  non-drinkers
#> 10 10      drinkers
# using stringr::str_remove()
library('stringr')
Data |>
  mutate(
    alcohol = str_remove(alcohol,'^Group [12]: ')
  )
#>    id      alcohol
#> 1   1     drinkers
#> 2   2     drinkers
#> 3   3     drinkers
#> 4   4 non-drinkers
#> 5   5     drinkers
#> 6   6 non-drinkers
#> 7   7     drinkers
#> 8   8     drinkers
#> 9   9 non-drinkers
#> 10 10     drinkers

^{Created on 2022-11-05 with reprex v2.0.2}

Kind regards

[Boboye.x]

Thank you. Both approaches worked just fine!

[FactOREO]

If any of the comments was sufficient to solve your problem, you can accept one of those answers

[Boboye.x]

Yes Dustin. Thank you!

[FactOREO]

I think you misunderstood me. There is a little check mark under every answer. Choose the answer which solved your problem and press the checkmark below that. This will indicate your problem has been solved.