how to unwind rows by spliting the column in DF

[pillai]

hi R's
Please someone help me in this situation,

your_list <- list(
    PERSON1 = list(
        group = "A,B,C",
        name = "PersonName1",
        age = 25
    ),
    PERSON2 = list(
        group = "X,Y,Z",
        name = "PersonName2",
        age = 28
    )
)

i would like to unwind the rows based on the column Group

the expected Result is as below
ID | name | group | age

PERSON1 | PersonName1 | A | 25
PERSON1 | PersonName1 | B | 25
PERSON1 | PersonName1 | C | 25
PERSON2 | PersonName2 | X | 28
PERSON2 | PersonName2 | Y | 28
PERSON2 | PersonName2 | Z | 28

Thanks in Advance

[mara]

I'm sure there are other ways to do it, but you could use a combination of purrr::map() and tidyr::separate_rows().

library(tidyverse)
your_list <- list(
  PERSON1 = list(
    group = "A,B,C",
    name = "PersonName1",
    age = 25
  ),
  PERSON2 = list(
    group = "X,Y,Z",
    name = "PersonName2",
    age = 28
  )
)

df <- tibble(
  "id" = names(your_list),
  "name" = map_chr(your_list, "name"),
  "group" = map(your_list, "group"),
  "age" = map_dbl(your_list, "age")
  )

df %>%
  separate_rows(group)
#> # A tibble: 6 x 4
#>   id      name        group   age
#>   <chr>   <chr>       <chr> <dbl>
#> 1 PERSON1 PersonName1 A        25
#> 2 PERSON1 PersonName1 B        25
#> 3 PERSON1 PersonName1 C        25
#> 4 PERSON2 PersonName2 X        28
#> 5 PERSON2 PersonName2 Y        28
#> 6 PERSON2 PersonName2 Z        28

^{Created on 2019-04-03 by the reprex package (v0.2.1)}

[Yarnabrina]

Basically, it's the same solution which Mara did, but a little bit more concise:

library(magrittr)

your_list <- list(PERSON1 = list(group = "A,B,C",
                                 name = "PersonName1",
                                 age = 25),
                  PERSON2 = list(group = "X,Y,Z",
                                 name = "PersonName2",
                                 age = 28))

your_list %>%
  do.call(rbind,.) %>%
  as.data.frame() %>%
  tibble::rownames_to_column() %>%
  tidyr::separate_rows(group)
#>   rowname group        name age
#> 1 PERSON1     A PersonName1  25
#> 2 PERSON1     B PersonName1  25
#> 3 PERSON1     C PersonName1  25
#> 4 PERSON2     X PersonName2  28
#> 5 PERSON2     Y PersonName2  28
#> 6 PERSON2     Z PersonName2  28

^{Created on 2019-04-03 by the reprex package (v0.2.1)}

[pillai]

@mara @Yarnabrina

Wonderful guys, Thanks for your quick support..