Subassignment • tibble

This vignette is an attempt to provide a comprehensive overview over all subassignment operations, highlighting where the tibble implementation differs from the data frame implementation.

library(tibble)
new_df <- function() {
  df <- data.frame(a = 1:4)
  df$b <- letters[5:8]
  df$cd <- list(9, 10:11, 12:14, "text")
  df
}
new_tbl <- function() {
  as_tibble(new_df())
}

Results of the same code for data frames and tibbles are presented side by side:

new_df()
#>   a b         cd
#> 1 1 e          9
#> 2 2 f     10, 11
#> 3 3 g 12, 13, 14
#> 4 4 h       text

new_tbl()
#> # A tibble: 4 × 3
#>       a b     cd       
#>   <int> <chr> <list>   
#> 1     1 e     <dbl [1]>
#> 2     2 f     <int [2]>
#> 3     3 g     <int [3]>
#> 4     4 h     <chr [1]>

In the following, if the results are identical (after converting to a data frame if necessary), only the tibble result is shown, as in the example below. This allows to spot differences easier.

new_tbl()
#> # A tibble: 4 × 3
#>       a b     cd       
#>   <int> <chr> <list>   
#> 1     1 e     <dbl [1]>
#> 2     2 f     <int [2]>
#> 3     3 g     <int [3]>
#> 4     4 h     <chr [1]>

For subassignment, we need a fresh copy of the data for each test. The with_*() functions allow for a more concise notation (with_tbl() omitted here for brevity):

with_df <- function(code, verbose = FALSE) {
  code <- rlang::enexpr(code)

  full_code <- rlang::quo({
    df <- new_df()
    !!code
    df
  })
  if (verbose) rlang::expr_print(rlang::quo_get_expr(full_code))
  rlang::eval_tidy(full_code)
}

This function takes an assignment expression and executes it on a fresh copy of the data. The first example prints what’s really executed, further examples omit this output.

with_df(df$a <- rev(df$a), verbose = TRUE)
#> {
#>   df <- new_df()
#>   df$a <- rev(df$a)
#>   df
#> }
#>   a b         cd
#> 1 4 e          9
#> 2 3 f     10, 11
#> 3 2 g 12, 13, 14
#> 4 1 h       text

with_tbl(tbl$a <- rev(tbl$a), verbose = TRUE)
#> {
#>   tbl <- new_tbl()
#>   tbl$a <- rev(tbl$a)
#>   tbl
#> }
#> # A tibble: 4 × 3
#>       a b     cd       
#>   <int> <chr> <list>   
#> 1     4 e     <dbl [1]>
#> 2     3 f     <int [2]>
#> 3     2 g     <int [3]>
#> 4     1 h     <chr [1]>

$<-

Scalars and full length

Assigning a scalar or a full-length vector to a column consistently overwrites existing data or appends a new column at the end. Partial matching doesn’t happen:

	`with_tbl(tbl$a <- 1) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 f <int [2]> #> 3 1 g <int [3]> #> 4 1 h <chr [1]>`
	`with_tbl(tbl$b <- 1) #> # A tibble: 4 × 3 #> a b cd #> <int> <dbl> <list> #> 1 1 1 <dbl [1]> #> 2 2 1 <int [2]> #> 3 3 1 <int [3]> #> 4 4 1 <chr [1]>`
	`with_tbl(tbl$c <- 1) #> # A tibble: 4 × 4 #> a b cd c #> <int> <chr> <list> <dbl> #> 1 1 e <dbl [1]> 1 #> 2 2 f <int [2]> 1 #> 3 3 g <int [3]> 1 #> 4 4 h <chr [1]> 1`
	`with_tbl(tbl$cd <- 1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <dbl> #> 1 1 e 1 #> 2 2 f 1 #> 3 3 g 1 #> 4 4 h 1`

	`with_tbl(tbl$a <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 e <dbl [1]> #> 2 3 f <int [2]> #> 3 2 g <int [3]> #> 4 1 h <chr [1]>`
	`with_tbl(tbl$b <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <int> <list> #> 1 1 4 <dbl [1]> #> 2 2 3 <int [2]> #> 3 3 2 <int [3]> #> 4 4 1 <chr [1]>`
	`with_tbl(tbl$c <- 4:1) #> # A tibble: 4 × 4 #> a b cd c #> <int> <chr> <list> <int> #> 1 1 e <dbl [1]> 4 #> 2 2 f <int [2]> 3 #> 3 3 g <int [3]> 2 #> 4 4 h <chr [1]> 1`
	`with_tbl(tbl$cd <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <int> #> 1 1 e 4 #> 2 2 f 3 #> 3 3 g 2 #> 4 4 h 1`

Recycling

Tibbles allow recycling only for vectors of length 1 or of the same length as the data.

`with_df(df$a <- 1:2) #> a b cd #> 1 1 e 9 #> 2 2 f 10, 11 #> 3 1 g 12, 13, 14 #> 4 2 h text`	with_tbl(tbl$a <- 1:2) #> Error in `$<-`: #> ! Assigned data `1:2` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 2 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 2 to size 4.
with_df(df$a <- 1:3) #> Error in `$<-.data.frame`(`tmp`, a, value = 1:3): replacement has 3 rows, data has 4	with_tbl(tbl$a <- 1:3) #> Error in `$<-`: #> ! Assigned data `1:3` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 3 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 3 to size 4.
with_df(df$a <- 1:5) #> Error in `$<-.data.frame`(`tmp`, a, value = 1:5): replacement has 5 rows, data has 4	with_tbl(tbl$a <- 1:5) #> Error in `$<-`: #> ! Assigned data `1:5` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 5 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 5 to size 4.
`with_df(df$c <- 1:2) #> a b cd c #> 1 1 e 9 1 #> 2 2 f 10, 11 2 #> 3 3 g 12, 13, 14 1 #> 4 4 h text 2`	with_tbl(tbl$c <- 1:2) #> Error in `$<-`: #> ! Assigned data `1:2` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 2 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 2 to size 4.

Subset assignment

Updating parts of a column extracted by $ is the responsibility of the column vector. Tibbles can’t control what happens after $ has returned.

	`with_tbl(tbl$a[1:2] <- 4:3) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 e <dbl [1]> #> 2 3 f <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
	`with_tbl(tbl$b[1:2] <- 4:3) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 4 <dbl [1]> #> 2 2 3 <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
`with_df(df$c[1:2] <- 4:3) #> a b cd c #> 1 1 e 9 4 #> 2 2 f 10, 11 3 #> 3 3 g 12, 13, 14 12, 13, 14 #> 4 4 h text text`	with_tbl(tbl$c[1:2] <- 4:3) #> Warning: Unknown or uninitialised #> column: `c`. #> Error in `$<-`: #> ! Assigned data `<int>` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 2 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 2 to size 4.
	`with_tbl(tbl$cd[1:2] <- 4:3) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <int [1]> #> 2 2 f <int [1]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
`with_df(df$a[1:3] <- 4:3) #> Warning in df$a[1:3] <- 4:3: number #> of items to replace is not a #> multiple of replacement length #> a b cd #> 1 4 e 9 #> 2 3 f 10, 11 #> 3 4 g 12, 13, 14 #> 4 4 h text`	`with_tbl(tbl$a[1:3] <- 4:3) #> Warning in tbl$a[1:3] <- 4:3: #> number of items to replace is not a #> multiple of replacement length #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 e <dbl [1]> #> 2 3 f <int [2]> #> 3 4 g <int [3]> #> 4 4 h <chr [1]>`
	`with_tbl(tbl$a[1:4] <- 4:3) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 e <dbl [1]> #> 2 3 f <int [2]> #> 3 4 g <int [3]> #> 4 3 h <chr [1]>`

For columns of the stricter "vctrs_vctr" class, this class implements the check, which then works identically for data frames and tibbles:

with_df({ df$v = vctrs::new_vctr(1:4); df$v[1:2] <- vctrs::new_vctr(4:3)})
#>   a b         cd v
#> 1 1 e          9 4
#> 2 2 f     10, 11 3
#> 3 3 g 12, 13, 14 3
#> 4 4 h       text 4
with_df({ df$v = vctrs::new_vctr(1:4); df$v[1:2] <- vctrs::new_vctr(letters[4:3])})
#> Error in `[<-`:
#> ! Can't convert `value` <vctrs_vctr> to <vctrs_vctr>.

[[<-

Scalars and full length

As with $ subsetting, columns are consistently overwritten, and partial matching doesn’t occur. Numeric indexing is supported, but tibbles don’t support creation of new numbered columns for a good reason.

	`with_tbl(tbl[["a"]] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 f <int [2]> #> 3 1 g <int [3]> #> 4 1 h <chr [1]>`
	`with_tbl(tbl[["a"]] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <chr> <chr> <list> #> 1 x e <dbl [1]> #> 2 x f <int [2]> #> 3 x g <int [3]> #> 4 x h <chr [1]>`
	`with_tbl(tbl[["b"]] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 x <dbl [1]> #> 2 2 x <int [2]> #> 3 3 x <int [3]> #> 4 4 x <chr [1]>`
	`with_tbl(tbl[["c"]] <- "x") #> # A tibble: 4 × 4 #> a b cd c #> <int> <chr> <list> <chr> #> 1 1 e <dbl [1]> x #> 2 2 f <int [2]> x #> 3 3 g <int [3]> x #> 4 4 h <chr [1]> x`
	`with_tbl(tbl[["cd"]] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <chr> #> 1 1 e x #> 2 2 f x #> 3 3 g x #> 4 4 h x`
	`with_tbl(tbl[[1]] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <chr> <chr> <list> #> 1 x e <dbl [1]> #> 2 x f <int [2]> #> 3 x g <int [3]> #> 4 x h <chr [1]>`
	`with_tbl(tbl[[2]] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 x <dbl [1]> #> 2 2 x <int [2]> #> 3 3 x <int [3]> #> 4 4 x <chr [1]>`
`with_df(df[[4]] <- "x") #> a b cd V4 #> 1 1 e 9 x #> 2 2 f 10, 11 x #> 3 3 g 12, 13, 14 x #> 4 4 h text x`	`with_tbl(tbl[[4]] <- "x") #> # A tibble: 4 × 4 #> a b cd ...4 #> <int> <chr> <list> <chr> #> 1 1 e <dbl [1]> x #> 2 2 f <int [2]> x #> 3 3 g <int [3]> x #> 4 4 h <chr [1]> x`
`with_df(df[[5]] <- "x") #> Warning in format.data.frame(if #> (omit) x[seq_len(n0), , drop = #> FALSE] else x, : corrupt data #> frame: columns will be truncated or #> padded with NAs #> a b cd V5 #> 1 1 e 9 NULL x #> 2 2 f 10, 11 <NA> x #> 3 3 g 12, 13, 14 <NA> x #> 4 4 h text <NA> x`	with_tbl(tbl[[5]] <- "x") #> Error in `[[<-`: #> ! Can't assign to columns beyond the end with non-consecutive locations. #> ℹ Input has size 3. #> ✖ Subscript `5` contains non-consecutive location 5.

	`with_tbl(tbl[["a"]] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 e <dbl [1]> #> 2 3 f <int [2]> #> 3 2 g <int [3]> #> 4 1 h <chr [1]>`
	`with_tbl(tbl[["a"]] <- letters[4:1]) #> # A tibble: 4 × 3 #> a b cd #> <chr> <chr> <list> #> 1 d e <dbl [1]> #> 2 c f <int [2]> #> 3 b g <int [3]> #> 4 a h <chr [1]>`
	`with_tbl(tbl[["b"]] <- letters[4:1]) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 d <dbl [1]> #> 2 2 c <int [2]> #> 3 3 b <int [3]> #> 4 4 a <chr [1]>`
	`with_tbl(tbl[["c"]] <- letters[4:1]) #> # A tibble: 4 × 4 #> a b cd c #> <int> <chr> <list> <chr> #> 1 1 e <dbl [1]> d #> 2 2 f <int [2]> c #> 3 3 g <int [3]> b #> 4 4 h <chr [1]> a`
	`with_tbl(tbl[["cd"]] <- letters[4:1]) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <chr> #> 1 1 e d #> 2 2 f c #> 3 3 g b #> 4 4 h a`

Cells

Tibbles are stricter when updating single cells, the value must be coercible to the existing contents. Updating a list column requires the contents to be wrapped in a list, consistently with [[ subsetting which returns a list if a cell in a list column is accessed:

`with_df(df[[2, "a"]] <- 1) #> a b cd #> 1 1 e 9 #> 2 1 f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text`	`with_tbl(tbl[[2, "a"]] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 f <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
`with_df(df[[2, "a"]] <- 1.5) #> a b cd #> 1 1.0 e 9 #> 2 1.5 f 10, 11 #> 3 3.0 g 12, 13, 14 #> 4 4.0 h text`	with_tbl(tbl[[2, "a"]] <- 1.5) #> Error in `[[<-`: #> ! Assigned data `1.5` must #> be compatible with existing data. #> ℹ Error occurred for column `a`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert from <double> to <integer> due to loss of precision. #> • Locations: 1
`with_df(df[[2, "a"]] <- "x") #> a b cd #> 1 1 e 9 #> 2 x f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[[2, "a"]] <- "x") #> Error in `[[<-`: #> ! Assigned data `"x"` must #> be compatible with existing data. #> ℹ Error occurred for column `a`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <integer>.
	`with_tbl(tbl[[2, "b"]] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 x <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
`with_df(df[[2, 1]] <- "x") #> a b cd #> 1 1 e 9 #> 2 x f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[[2, 1]] <- "x") #> Error in `[[<-`: #> ! Assigned data `"x"` must #> be compatible with existing data. #> ℹ Error occurred for column `a`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <integer>.
	`with_tbl(tbl[[2, 2]] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 x <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
`with_df(df[[2, "cd"]] <- "x") #> a b cd #> 1 1 e 9 #> 2 2 f x #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[[2, "cd"]] <- "x") #> Error in `[[<-`: #> ! Assigned data `"x"` must #> be compatible with existing data. #> ℹ Error occurred for column `cd`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <list>.
`with_df(df[[2, "cd"]] <- list("x")) #> a b cd #> 1 1 e 9 #> 2 2 f x #> 3 3 g 12, 13, 14 #> 4 4 h text`	`with_tbl(tbl[[2, "cd"]] <- list("x")) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 f <chr [1]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
with_df(df[[2, "c"]] <- "x") #> Error in `[[<-.data.frame`(`tmp`, 2, "c", value = "x"): replacing element in non-existent column: c	`with_tbl(tbl[[2, "c"]] <- "x") #> # A tibble: 4 × 4 #> a b cd c #> <int> <chr> <list> <chr> #> 1 1 e <dbl [1]> NA #> 2 2 f <int [2]> x #> 3 3 g <int [3]> NA #> 4 4 h <chr [1]> NA`
with_df(df[[1:2, "cd"]] <- "x") #> Error in `[[<-.data.frame`(`tmp`, 1:2, "cd", value = "x"): only a single element should be replaced	with_tbl(tbl[[1:2, "cd"]] <- "x") #> Error in `[[<-`: #> ! Can't assign row with `1:2`. #> ✖ Subscript `1:2` must be size 1, not 2.
with_df(df[[1:2, "c"]] <- "x") #> Error in `[[<-.data.frame`(`tmp`, 1:2, "c", value = "x"): replacing element in non-existent column: c	with_tbl(tbl[[1:2, "c"]] <- "x") #> Error in `[[<-`: #> ! Can't assign row with `1:2`. #> ✖ Subscript `1:2` must be size 1, not 2.
with_df(df[[2, c("cd", "d")]] <- "x") #> Error in `[[<-.data.frame`(`tmp`, 2, c("cd", "d"), value = "x"): replacing element in non-existent column: d	with_tbl(tbl[[2, c("cd", "d")]] <- "x") #> Error in `[[<-`: #> ! Can't assign column with `c("cd", "d")`. #> ✖ Subscript `c("cd", "d")` must be size 1, not 2.

[<-

Scalars

`with_df(df[2, "a"] <- 1) #> a b cd #> 1 1 e 9 #> 2 1 f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text`	`with_tbl(tbl[2, "a"] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 f <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
`with_df(df[2, "a"] <- 1.5) #> a b cd #> 1 1.0 e 9 #> 2 1.5 f 10, 11 #> 3 3.0 g 12, 13, 14 #> 4 4.0 h text`	with_tbl(tbl[2, "a"] <- 1.5) #> Error in `[<-`: #> ! Assigned data `1.5` must #> be compatible with existing data. #> ℹ Error occurred for column `a`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert from <double> to <integer> due to loss of precision. #> • Locations: 1
`with_df(df[2, "a"] <- "x") #> a b cd #> 1 1 e 9 #> 2 x f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[2, "a"] <- "x") #> Error in `[<-`: #> ! Assigned data `"x"` must #> be compatible with existing data. #> ℹ Error occurred for column `a`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <integer>.
	`with_tbl(tbl[2, "b"] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 x <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
`with_df(df[2, "cd"] <- "x") #> a b cd #> 1 1 e 9 #> 2 2 f x #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[2, "cd"] <- "x") #> Error in `[<-`: #> ! Assigned data `"x"` must #> be compatible with existing data. #> ℹ Error occurred for column `cd`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <list>.
`with_df(df[2, "cd"] <- list("x")) #> a b cd #> 1 1 e 9 #> 2 2 f x #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[2, "cd"] <- list("x")) #> Error in `[<-`: #> ! Assigned data `list("x")` #> must be compatible with existing #> data. #> ℹ Error occurred for column `cd`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <list>.
	`with_tbl(tbl[2, "c"] <- "x") #> # A tibble: 4 × 4 #> a b cd c #> <int> <chr> <list> <chr> #> 1 1 e <dbl [1]> NA #> 2 2 f <int [2]> x #> 3 3 g <int [3]> NA #> 4 4 h <chr [1]> NA`
`with_df(df[2, 1] <- "x") #> a b cd #> 1 1 e 9 #> 2 x f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[2, 1] <- "x") #> Error in `[<-`: #> ! Assigned data `"x"` must #> be compatible with existing data. #> ℹ Error occurred for column `a`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <integer>.
	`with_tbl(tbl[2, 2] <- "x") #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 x <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
`with_df(df[2, 3] <- "x") #> a b cd #> 1 1 e 9 #> 2 2 f x #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[2, 3] <- "x") #> Error in `[<-`: #> ! Assigned data `"x"` must #> be compatible with existing data. #> ℹ Error occurred for column `cd`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <list>.
`with_df(df[2, 4] <- "x") #> a b cd V4 #> 1 1 e 9 <NA> #> 2 2 f 10, 11 x #> 3 3 g 12, 13, 14 <NA> #> 4 4 h text <NA>`	`with_tbl(tbl[2, 4] <- "x") #> # A tibble: 4 × 4 #> a b cd ...4 #> <int> <chr> <list> <chr> #> 1 1 e <dbl [1]> NA #> 2 2 f <int [2]> x #> 3 3 g <int [3]> NA #> 4 4 h <chr [1]> NA`

Full length columns

	`with_tbl(tbl[, "a"] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 e <dbl [1]> #> 2 3 f <int [2]> #> 3 2 g <int [3]> #> 4 1 h <chr [1]>`
	`with_tbl(tbl[, "b"] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <int> <list> #> 1 1 4 <dbl [1]> #> 2 2 3 <int [2]> #> 3 3 2 <int [3]> #> 4 4 1 <chr [1]>`
	`with_tbl(tbl[, "c"] <- 4:1) #> # A tibble: 4 × 4 #> a b cd c #> <int> <chr> <list> <int> #> 1 1 e <dbl [1]> 4 #> 2 2 f <int [2]> 3 #> 3 3 g <int [3]> 2 #> 4 4 h <chr [1]> 1`
	`with_tbl(tbl[, "cd"] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <int> #> 1 1 e 4 #> 2 2 f 3 #> 3 3 g 2 #> 4 4 h 1`
	`with_tbl(tbl[, 1] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 e <dbl [1]> #> 2 3 f <int [2]> #> 3 2 g <int [3]> #> 4 1 h <chr [1]>`
	`with_tbl(tbl[, 2] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <int> <list> #> 1 1 4 <dbl [1]> #> 2 2 3 <int [2]> #> 3 3 2 <int [3]> #> 4 4 1 <chr [1]>`
	`with_tbl(tbl[, 3] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <int> #> 1 1 e 4 #> 2 2 f 3 #> 3 3 g 2 #> 4 4 h 1`
`with_df(df[, 4] <- 4:1) #> a b cd V4 #> 1 1 e 9 4 #> 2 2 f 10, 11 3 #> 3 3 g 12, 13, 14 2 #> 4 4 h text 1`	`with_tbl(tbl[, 4] <- 4:1) #> # A tibble: 4 × 4 #> a b cd ...4 #> <int> <chr> <list> <int> #> 1 1 e <dbl [1]> 4 #> 2 2 f <int [2]> 3 #> 3 3 g <int [3]> 2 #> 4 4 h <chr [1]> 1`
	`with_tbl(tbl[, "a"] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 f <int [2]> #> 3 1 g <int [3]> #> 4 1 h <chr [1]>`
	`with_tbl(tbl[, "b"] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <int> <dbl> <list> #> 1 1 1 <dbl [1]> #> 2 2 1 <int [2]> #> 3 3 1 <int [3]> #> 4 4 1 <chr [1]>`
	`with_tbl(tbl[, "c"] <- 1) #> # A tibble: 4 × 4 #> a b cd c #> <int> <chr> <list> <dbl> #> 1 1 e <dbl [1]> 1 #> 2 2 f <int [2]> 1 #> 3 3 g <int [3]> 1 #> 4 4 h <chr [1]> 1`
	`with_tbl(tbl[, "cd"] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <dbl> #> 1 1 e 1 #> 2 2 f 1 #> 3 3 g 1 #> 4 4 h 1`
	`with_tbl(tbl[, 1] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 f <int [2]> #> 3 1 g <int [3]> #> 4 1 h <chr [1]>`
	`with_tbl(tbl[, 2] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <int> <dbl> <list> #> 1 1 1 <dbl [1]> #> 2 2 1 <int [2]> #> 3 3 1 <int [3]> #> 4 4 1 <chr [1]>`
	`with_tbl(tbl[, 3] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <dbl> #> 1 1 e 1 #> 2 2 f 1 #> 3 3 g 1 #> 4 4 h 1`
`with_df(df[, 4] <- 1) #> a b cd V4 #> 1 1 e 9 1 #> 2 2 f 10, 11 1 #> 3 3 g 12, 13, 14 1 #> 4 4 h text 1`	`with_tbl(tbl[, 4] <- 1) #> # A tibble: 4 × 4 #> a b cd ...4 #> <int> <chr> <list> <dbl> #> 1 1 e <dbl [1]> 1 #> 2 2 f <int [2]> 1 #> 3 3 g <int [3]> 1 #> 4 4 h <chr [1]> 1`

Multiple full length columns

	`with_tbl(tbl[, c("a", "b")] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <int> <list> #> 1 4 4 <dbl [1]> #> 2 3 3 <int [2]> #> 3 2 2 <int [3]> #> 4 1 1 <chr [1]>`
	`with_tbl(tbl[, c("a", "b")] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <dbl> <list> #> 1 1 1 <dbl [1]> #> 2 1 1 <int [2]> #> 3 1 1 <int [3]> #> 4 1 1 <chr [1]>`
	`with_tbl(tbl[, c("a", "b")] <- data.frame(a = 4:1, b = letters[4:1])) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 d <dbl [1]> #> 2 3 c <int [2]> #> 3 2 b <int [3]> #> 4 1 a <chr [1]>`
	`with_tbl(tbl[, c("a", "b")] <- data.frame(b = 4:1, a = letters[4:1])) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 d <dbl [1]> #> 2 3 c <int [2]> #> 3 2 b <int [3]> #> 4 1 a <chr [1]>`
	`with_tbl(tbl[, c("a", "b")] <- data.frame(c = 4:1, d = letters[4:1])) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 4 d <dbl [1]> #> 2 3 c <int [2]> #> 3 2 b <int [3]> #> 4 1 a <chr [1]>`
	`with_tbl(tbl[, c("a", "b")] <- data.frame(a = 4:1)) #> # A tibble: 4 × 3 #> a b cd #> <int> <int> <list> #> 1 4 4 <dbl [1]> #> 2 3 3 <int [2]> #> 3 2 2 <int [3]> #> 4 1 1 <chr [1]>`
with_df(df[, c("a", "b")] <- data.frame(a = 4:1, b = letters[4:1], c = 1:4)) #> Warning in #> `[<-.data.frame`(`tmp`, , c("a", #> "b"), value = structure(list(: #> provided 3 variables to replace 2 #> variables #> a b cd #> 1 4 d 9 #> 2 3 c 10, 11 #> 3 2 b 12, 13, 14 #> 4 1 a text	with_tbl(tbl[, c("a", "b")] <- data.frame(a = 4:1, b = letters[4:1], c = 1:4)) #> Error in `[<-`: #> ! Can't recycle input of size 3 to size 2.
	`with_tbl(tbl[, c("a", "b")] <- data.frame(4:1, 1)) #> # A tibble: 4 × 3 #> a b cd #> <int> <dbl> <list> #> 1 4 1 <dbl [1]> #> 2 3 1 <int [2]> #> 3 2 1 <int [3]> #> 4 1 1 <chr [1]>`
`with_df(df[, c("a", "b", "c")] <- data.frame(4:1, letters[4:1])) #> a b cd c #> 1 4 d 9 4 #> 2 3 c 10, 11 3 #> 3 2 b 12, 13, 14 2 #> 4 1 a text 1`	with_tbl(tbl[, c("a", "b", "c")] <- data.frame(4:1, letters[4:1])) #> Error in `[<-`: #> ! Can't recycle input of size 2 to size 3.
`with_df(df[, c("a", "b", "cd")] <- data.frame(4:1, letters[4:1])) #> a b cd #> 1 4 d 4 #> 2 3 c 3 #> 3 2 b 2 #> 4 1 a 1`	with_tbl(tbl[, c("a", "b", "cd")] <- data.frame(4:1, letters[4:1])) #> Error in `[<-`: #> ! Can't recycle input of size 2 to size 3.

Full length rows

`with_df(df[2, ] <- 1) #> a b cd #> 1 1 e 9 #> 2 1 1 1 #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[2, ] <- 1) #> Error in `[<-`: #> ! Assigned data `1` must be #> compatible with existing data. #> ℹ Error occurred for column `b`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <double> to <character>.
`with_df(df[2, ] <- "x") #> a b cd #> 1 1 e 9 #> 2 x x x #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[2, ] <- "x") #> Error in `[<-`: #> ! Assigned data `"x"` must #> be compatible with existing data. #> ℹ Error occurred for column `a`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <integer>.
`with_df(df[2, ] <- tibble(a = 1, b = "x")) #> a b cd #> 1 1 e 9 #> 2 1 x 1 #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[2, ] <- tibble(a = 1, b = "x")) #> Error in `[<-`: #> ! Can't recycle input of size 2 to size 3.
`with_df(df[2, ] <- tibble(a = 1, b = "x", c = list("y"))) #> a b cd #> 1 1 e 9 #> 2 1 x y #> 3 3 g 12, 13, 14 #> 4 4 h text`	`with_tbl(tbl[2, ] <- tibble(a = 1, b = "x", c = list("y"))) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 x <chr [1]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
with_df(df[2, ] <- tibble(a = 1, b = "x", c = list("y"), d = "z")) #> Warning in #> `[<-.data.frame`(`tmp`, 2, , #> value = structure(list(a = 1, : #> provided 4 variables to replace 3 #> variables #> a b cd #> 1 1 e 9 #> 2 1 x y #> 3 3 g 12, 13, 14 #> 4 4 h text	with_tbl(tbl[2, ] <- tibble(a = 1, b = "x", c = list("y"), d = "z")) #> Error in `[<-`: #> ! Can't recycle input of size 4 to size 3.
`with_df(df[0, ] <- tibble(a = 1, b = "x", c = list("y"))) #> a b cd #> 1 1 e 9 #> 2 2 f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text`	with_tbl(tbl[0, ] <- tibble(a = 1, b = "x", c = list("y"))) #> Error in `[<-`: #> ! Can't assign rows with `0`. #> ✖ Subscript `0` can't contain `0` values. #> ℹ It has a `0` value at location 1.
`with_df(df[5, ] <- tibble(a = 1, b = "x", c = list("y"))) #> a b cd #> 1 1 e 9 #> 2 2 f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text #> 5 1 x y`	`with_tbl(tbl[5, ] <- tibble(a = 1, b = "x", c = list("y"))) #> # A tibble: 5 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 f <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]> #> 5 1 x <chr [1]>`

Multiple full length rows

`with_df(df[2:3, ] <- 1) #> a b cd #> 1 1 e 9 #> 2 1 1 1 #> 3 1 1 1 #> 4 4 h text`	with_tbl(tbl[2:3, ] <- 1) #> Error in `[<-`: #> ! Assigned data `1` must be #> compatible with existing data. #> ℹ Error occurred for column `b`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <double> to <character>.
`with_df(df[2:3, ] <- 1:2) #> a b cd #> 1 1 e 9 #> 2 1 1 1 #> 3 2 2 2 #> 4 4 h text`	with_tbl(tbl[2:3, ] <- 1:2) #> Error in `[<-`: #> ! Assigned data `1:2` must #> be compatible with existing data. #> ℹ Error occurred for column `b`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <integer> to <character>.
`with_df(df[2:3, ] <- c("x", "y")) #> a b cd #> 1 1 e 9 #> 2 x x x #> 3 y y y #> 4 4 h text`	with_tbl(tbl[2:3, ] <- c("x", "y")) #> Error in `[<-`: #> ! Assigned data `c("x", #> "y")` must be compatible with #> existing data. #> ℹ Error occurred for column `a`. #> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3: #> ! Can't convert <character> to <integer>.
`with_df(df[2:3, ] <- tibble(a = 1:2, b = c("x", "y"))) #> a b cd #> 1 1 e 9 #> 2 1 x 1 #> 3 2 y 2 #> 4 4 h text`	with_tbl(tbl[2:3, ] <- tibble(a = 1:2, b = c("x", "y"))) #> Error in `[<-`: #> ! Can't recycle input of size 2 to size 3.
`with_df(df[2:3, ] <- tibble(a = 1, b = "x", c = list("y"))) #> a b cd #> 1 1 e 9 #> 2 1 x y #> 3 1 x y #> 4 4 h text`	`with_tbl(tbl[2:3, ] <- tibble(a = 1, b = "x", c = list("y"))) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 x <chr [1]> #> 3 1 x <chr [1]> #> 4 4 h <chr [1]>`
	`with_tbl(tbl[2:3, ] <- tibble(a = 1:2, b = "x", c = list("y"))) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 1 x <chr [1]> #> 3 2 x <chr [1]> #> 4 4 h <chr [1]>`
with_df(df[2:3, ] <- tibble(a = 1, b = "x", c = list("y"), d = "z")) #> Warning in #> `[<-.data.frame`(`tmp`, 2:3, , #> value = structure(list(a = 1, : #> provided 4 variables to replace 3 #> variables #> a b cd #> 1 1 e 9 #> 2 1 x y #> 3 1 x y #> 4 4 h text	with_tbl(tbl[2:3, ] <- tibble(a = 1, b = "x", c = list("y"), d = "z")) #> Error in `[<-`: #> ! Can't recycle input of size 4 to size 3.
	`with_tbl(tbl[-(1:2), ] <- tibble(a = 1:2, b = "x", c = list("y"))) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 f <int [2]> #> 3 1 x <chr [1]> #> 4 2 x <chr [1]>`
with_df(df[0:1, ] <- tibble(a = 1:2, b = "x", c = list("y"))) #> Warning in #> `[<-.data.frame`(`tmp`, 0:1, , #> value = structure(list(a = 1:2, : #> replacement element 1 has 2 rows to #> replace 1 rows #> Warning in #> `[<-.data.frame`(`tmp`, 0:1, , #> value = structure(list(a = 1:2, : #> replacement element 2 has 2 rows to #> replace 1 rows #> Warning in #> `[<-.data.frame`(`tmp`, 0:1, , #> value = structure(list(a = 1:2, : #> replacement element 3 has 2 rows to #> replace 1 rows #> a b cd #> 1 1 x y #> 2 2 f 10, 11 #> 3 3 g 12, 13, 14 #> 4 4 h text	with_tbl(tbl[0:1, ] <- tibble(a = 1:2, b = "x", c = list("y"))) #> Error in `[<-`: #> ! Can't assign rows with `0:1`. #> ✖ Subscript `0:1` can't contain `0` values. #> ℹ It has a `0` value at location 1.
	`with_tbl(tbl[4:5, ] <- tibble(a = 1:2, b = "x", c = list("y"))) #> # A tibble: 5 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 f <int [2]> #> 3 3 g <int [3]> #> 4 1 x <chr [1]> #> 5 2 x <chr [1]>`

Unspecified

	`with_tbl(tbl[] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <dbl> <dbl> #> 1 1 1 1 #> 2 1 1 1 #> 3 1 1 1 #> 4 1 1 1`
	`with_tbl(tbl[] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <int> <int> #> 1 4 4 4 #> 2 3 3 3 #> 3 2 2 2 #> 4 1 1 1`
`with_df(df[] <- 3:1) #> a b cd #> 1 3 2 1 #> 2 2 1 3 #> 3 1 3 2 #> 4 3 2 1`	with_tbl(tbl[] <- 3:1) #> Error in `[<-`: #> ! Assigned data `3:1` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 3 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 3 to size 4.
with_df(df[] <- 5:1) #> Error in `[<-.data.frame`(`tmp`, , value = 5:1): replacement has 5 items, need 12	with_tbl(tbl[] <- 5:1) #> Error in `[<-`: #> ! Assigned data `5:1` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 5 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 5 to size 4.
`with_df(df[] <- data.frame(1, "x")) #> a b cd #> 1 1 x 1 #> 2 1 x 1 #> 3 1 x 1 #> 4 1 x 1`	with_tbl(tbl[] <- data.frame(1, "x")) #> Error in `[<-`: #> ! Can't recycle input of size 2 to size 3.
	`with_tbl(tbl[] <- data.frame(4:1, "x", 2)) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <dbl> #> 1 4 x 2 #> 2 3 x 2 #> 3 2 x 2 #> 4 1 x 2`
	`with_tbl(tbl[] <- data.frame(1, "x", 2)) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <chr> <dbl> #> 1 1 x 2 #> 2 1 x 2 #> 3 1 x 2 #> 4 1 x 2`
with_df(df[] <- data.frame(1, "x", 2, 3)) #> Warning in #> `[<-.data.frame`(`tmp`, , value = #> structure(list(X1 = 1, X.x. = "x", #> : provided 4 variables to replace 3 #> variables #> a b cd #> 1 1 x 2 #> 2 1 x 2 #> 3 1 x 2 #> 4 1 x 2	with_tbl(tbl[] <- data.frame(1, "x", 2, 3)) #> Error in `[<-`: #> ! Can't recycle input of size 4 to size 3.
	`with_tbl(tbl[] <- tbl) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 f <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`
	`with_tbl(tbl[,] <- 1) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <dbl> <dbl> #> 1 1 1 1 #> 2 1 1 1 #> 3 1 1 1 #> 4 1 1 1`
	`with_tbl(tbl[,] <- 4:1) #> # A tibble: 4 × 3 #> a b cd #> <int> <int> <int> #> 1 4 4 4 #> 2 3 3 3 #> 3 2 2 2 #> 4 1 1 1`
`with_df(df[,] <- 3:1) #> a b cd #> 1 3 2 1 #> 2 2 1 3 #> 3 1 3 2 #> 4 3 2 1`	with_tbl(tbl[,] <- 3:1) #> Error in `[<-`: #> ! Assigned data `3:1` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 3 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 3 to size 4.
with_df(df[,] <- 5:1) #> Error in `[<-.data.frame`(`tmp`, , , value = 5:1): replacement has 5 items, need 12	with_tbl(tbl[,] <- 5:1) #> Error in `[<-`: #> ! Assigned data `5:1` must #> be compatible with existing data. #> ✖ Existing data has 4 rows. #> ✖ Assigned data has 5 rows. #> ℹ Only vectors of size 1 are #> recycled. #> Caused by error in `vectbl_recycle_rhs_rows()` at tibble/R/subassign-backend.R:51:5: #> ! Can't recycle input of size 5 to size 4.
`with_df(df[,] <- data.frame(1, "x")) #> a b cd #> 1 1 x 1 #> 2 1 x 1 #> 3 1 x 1 #> 4 1 x 1`	with_tbl(tbl[,] <- data.frame(1, "x")) #> Error in `[<-`: #> ! Can't recycle input of size 2 to size 3.
	`with_tbl(tbl[,] <- data.frame(4:1, "x", 2)) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <dbl> #> 1 4 x 2 #> 2 3 x 2 #> 3 2 x 2 #> 4 1 x 2`
	`with_tbl(tbl[,] <- data.frame(1, "x", 2)) #> # A tibble: 4 × 3 #> a b cd #> <dbl> <chr> <dbl> #> 1 1 x 2 #> 2 1 x 2 #> 3 1 x 2 #> 4 1 x 2`
with_df(df[,] <- data.frame(1, "x", 2, 3)) #> Warning in #> `[<-.data.frame`(`tmp`, , , value #> = structure(list(X1 = 1, : provided #> 4 variables to replace 3 variables #> a b cd #> 1 1 x 2 #> 2 1 x 2 #> 3 1 x 2 #> 4 1 x 2	with_tbl(tbl[,] <- data.frame(1, "x", 2, 3)) #> Error in `[<-`: #> ! Can't recycle input of size 4 to size 3.
	`with_tbl(tbl[,] <- tbl) #> # A tibble: 4 × 3 #> a b cd #> <int> <chr> <list> #> 1 1 e <dbl [1]> #> 2 2 f <int [2]> #> 3 3 g <int [3]> #> 4 4 h <chr [1]>`

Subset assignment

Due to tibble’s default of drop = FALSE, updating a portion of a [ subset is still safe, because tibble is still in control. Only one example is given here.

with_df(df["a"][1, ] <- "b")
#>   a b         cd
#> 1 b e          9
#> 2 2 f     10, 11
#> 3 3 g 12, 13, 14
#> 4 4 h       text

with_tbl(tbl["a"][1, ] <- "b")
#> Error in `[<-`:
#> ! Assigned data `"b"` must
#>   be compatible with existing data.
#> ℹ Error occurred for column `a`.
#> Caused by error in `vec_assign()` at tibble/R/subassign-backend.R:237:3:
#> ! Can't convert <character> to <integer>.