How do I split a “data.frame” type column while preserving other column types?

Question

I have a dataframe df where one of the columns user is itself a data.frame .

df <- data.frame(
  user = data.frame(
    id = numeric(),
    name = character()
  ),
  color = character()
)

df[nrow(df)+1,] <- c(1,"joe","green")

How do I split the user column into the id and name columns so that df has the id and name columns instead of the user column, while keeping the color column?

Answer 1

The data.frame structure showed in the OP's post is not reproducible. So, constructed a tibble

library(tibble)
library(tidyr)
library(dplyr)
df1 <- df %>%
            mutate(user = list(user)) %>%
            unnest_wider(c(user)) 

str(df1)
#tibble [1 × 3] (S3: tbl_df/tbl/data.frame)
# $ id   : num 1
# $ name : chr "joe"
# $ color: chr "green"

---

NOTE: when we adding a new row with assignment, if we choose a vector ( c(...) ), there is a limitation in having different types as vector allows only a single type. Instead use a list

data

df <- tibble(user = tibble(id = 1, name = "joe"), color = "green")