How to add rows in R already grouped?-CodePudding

I have this dataset

 dat=structure(list(A = c("n", 
                                                                     
  "n", "F", "F"), Par = c(1, 
                                                                                                                
   1, 8, 3), var = c(1, 10, 1,5), dat = c("T", 
                                                                                                                                                       
   "T", "T", "T")), row.names = c(NA, 4L                                                                                                                                                    
    ), class = "data.frame")

I want to add by the groups in A , i tried this did not work:

  dat%>%group_by(A)%>% mutate(ye = c( "40-25", "25-200"))

Error: ! Assigned data value must be compatible with existing data. ✖ Existing data has 4 rows. ✖ Assigned data has 2 rows. ℹ Only vectors of size 1 are recycled. Run rlang::last_error() to see where the error occurred.

    A Par var dat     ye
  1 n   1   1   T  "40-25"
  2 n   1  10   T  "40-25"
  3 F   8   1   T  "25-200"
  4 F   3   5   T  "25-200"

CodePudding user response：

In a simple case like this you can use an ifelse() or case_when(). The latter may be preferable as it is easier to add additional values if the logic changes:

dat  |>
    mutate(
        ye = case_when(
            A == "n" ~ "40-25",
            A == "F" ~ "25-200", 
            TRUE ~ "A is neither n nor F"
        )
    )

However, case_when() can also become unwieldy if you have many conditions.

I prefer to join if you are going to do this with a lot of values, as it allows you to edit the data rather than the logic.

values_to_join  <- data.frame(
    A = c("n", "F"),
    ye = c("40-25", "25-200")
)

left_join(dat, values_to_join, by = "A")

#   A Par var dat     ye
# 1 n   1   1   T  40-25
# 2 n   1  10   T  40-25
# 3 F   8   1   T 25-200
# 4 F   3   5   T 25-200

CodePudding user response：

Probably you can try summarise_all unnest

library(dplyr)
library(tidyr)

dat %>%
  group_by(A) %>%
  summarise_all(list) %>%
  mutate(ye = c("40-25", "25-200")) %>%
  unnest(cols = c(Par, var, dat))

which gives

  A       Par   var dat   ye    
  <chr> <dbl> <dbl> <chr> <chr>
1 F         8     1 T     40-25
2 F         3     5 T     40-25
3 n         1     1 T     25-200
4 n         1    10 T     25-200

CodePudding user response：

If I understand your goal, you could split by group and add your ye values sequentially by group:

library(dplyr)
library(purrr)

dat %>%
  group_by(A) %>%
  group_split() %>%
  map2_dfr(
    c("40-25", "25-200"),
    ~ mutate(.x, ye = .y)
  )

# A tibble: 4 × 5
  A       Par   var dat   ye    
  <chr> <dbl> <dbl> <chr> <chr> 
1 F         8     1 T     40-25 
2 F         3     5 T     40-25 
3 n         1     1 T     25-200
4 n         1    10 T     25-200

If instead you want to create ye based on specific values of A, see @SamR’s answer or use dplyr::recode():

dat %>%
  mutate(ye = recode(
    A,
    F = "40-25", 
    n = "25-200"
  ))