tests/testthat/_snaps/filter.md

In dplyr: A Grammar of Data Manipulation

filter() and filter_out() allow matrices with 1 column with a deprecation warning (#6091)

Code
  out <- filter(df, matrix(c(TRUE, FALSE), nrow = 2))
Condition
  Warning:
  Using one column matrices in `filter()` or `filter_out()` was deprecated in dplyr 1.1.0.
  i Please use one dimensional logical vectors instead.

Code
  out <- filter_out(df, matrix(c(TRUE, FALSE), nrow = 2))
Condition
  Warning:
  Using one column matrices in `filter()` or `filter_out()` was deprecated in dplyr 1.1.0.
  i Please use one dimensional logical vectors instead.

Code
  out <- filter(gdf, matrix(c(TRUE, FALSE), nrow = 2))
Condition
  Warning:
  Using one column matrices in `filter()` or `filter_out()` was deprecated in dplyr 1.1.0.
  i Please use one dimensional logical vectors instead.

Code
  out <- filter_out(gdf, matrix(c(TRUE, FALSE), nrow = 2))
Condition
  Warning:
  Using one column matrices in `filter()` or `filter_out()` was deprecated in dplyr 1.1.0.
  i Please use one dimensional logical vectors instead.

filter() and filter_out() disallow matrices with >1 column

Code
  filter(df, matrix(TRUE, nrow = 3, ncol = 2))
Condition
  Error in `filter()`:
  i In argument: `matrix(TRUE, nrow = 3, ncol = 2)`.
  Caused by error:
  ! `..1` must be a logical vector, not a logical matrix.

Code
  filter_out(df, matrix(TRUE, nrow = 3, ncol = 2))
Condition
  Error in `filter_out()`:
  i In argument: `matrix(TRUE, nrow = 3, ncol = 2)`.
  Caused by error:
  ! `..1` must be a logical vector, not a logical matrix.

filter() and filter_out() disallow arrays with >2 dimensions

Code
  filter(df, array(TRUE, dim = c(3, 1, 1)))
Condition
  Error in `filter()`:
  i In argument: `array(TRUE, dim = c(3, 1, 1))`.
  Caused by error:
  ! `..1` must be a logical vector, not a logical array.

Code
  filter_out(df, array(TRUE, dim = c(3, 1, 1)))
Condition
  Error in `filter_out()`:
  i In argument: `array(TRUE, dim = c(3, 1, 1))`.
  Caused by error:
  ! `..1` must be a logical vector, not a logical array.

filter() gives useful error messages

Code
  (expect_error(filter(group_by(iris, Species), 1:n())))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `1:n()`.
  i In group 1: `Species = setosa`.
  Caused by error:
  ! `..1` must be a logical vector, not an integer vector.
Code
  (expect_error(filter(iris, 1:n())))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `1:n()`.
  Caused by error:
  ! `..1` must be a logical vector, not an integer vector.
Code
  (expect_error(filter(data.frame(x = 1:2), matrix(c(TRUE, FALSE, TRUE, FALSE),
  nrow = 2))))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `matrix(c(TRUE, FALSE, TRUE, FALSE), nrow = 2)`.
  Caused by error:
  ! `..1` must be a logical vector, not a logical matrix.
Code
  (expect_error(filter(group_by(iris, Species), c(TRUE, FALSE))))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `c(TRUE, FALSE)`.
  i In group 1: `Species = setosa`.
  Caused by error:
  ! `..1` must be of size 50 or 1, not size 2.
Code
  (expect_error(filter(rowwise(iris, Species), c(TRUE, FALSE))))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `c(TRUE, FALSE)`.
  i In row 1.
  Caused by error:
  ! `..1` must be of size 1, not size 2.
Code
  (expect_error(filter(iris, c(TRUE, FALSE))))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `c(TRUE, FALSE)`.
  Caused by error:
  ! `..1` must be of size 150 or 1, not size 2.
Code
  (expect_error(filter(mtcars, `_x`)))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `_x`.
  Caused by error:
  ! object '_x' not found
Code
  (expect_error(filter(group_by(mtcars, cyl), `_x`)))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `_x`.
  i In group 1: `cyl = 4`.
  Caused by error:
  ! object '_x' not found
Code
  (expect_error(filter(mtcars, x = 1)))
Output
  <error/rlang_error>
  Error in `filter()`:
  ! We detected a named input.
  i This usually means that you've used `=` instead of `==`.
  i Did you mean `x == 1`?
Code
  (expect_error(filter(mtcars, y > 2, z = 3)))
Output
  <error/rlang_error>
  Error in `filter()`:
  ! We detected a named input.
  i This usually means that you've used `=` instead of `==`.
  i Did you mean `z == 3`?
Code
  (expect_error(filter(mtcars, TRUE, x = 1)))
Output
  <error/rlang_error>
  Error in `filter()`:
  ! We detected a named input.
  i This usually means that you've used `=` instead of `==`.
  i Did you mean `x == 1`?
Code
  (expect_error(filter(ts(1:10))))
Output
  <error/rlang_error>
  Error in `filter()`:
  ! Incompatible data source.
  x `.data` is a <ts> object, not a data source.
  i Did you want to use `stats::filter()`?
Code
  (expect_error(filter(tibble(), stop("{"))))
Output
  <error/rlang_error>
  Error in `filter()`:
  i In argument: `stop("{")`.
  Caused by error:
  ! {

Using data frames in filter() is defunct (#7758)

Code
  filter(df, across(everything(), ~ .x > 0))
Condition
  Error in `filter()`:
  i In argument: `across(everything(), ~.x > 0)`.
  Caused by error:
  ! `..1` must be a logical vector, not a <tbl_df/tbl/data.frame> object.
  i If you used `across()` to generate this data frame, please use `if_any()` or `if_all()` instead.

Code
  filter(gdf, across(everything(), ~ .x > 0))
Condition
  Error in `filter()`:
  i In argument: `across(everything(), ~.x > 0)`.
  i In group 1: `x = 1`.
  Caused by error:
  ! `..1` must be a logical vector, not a <tbl_df/tbl/data.frame> object.
  i If you used `across()` to generate this data frame, please use `if_any()` or `if_all()` instead.

Code
  filter(rdf, across(everything(), ~ .x > 0))
Condition
  Error in `filter()`:
  i In argument: `across(everything(), ~.x > 0)`.
  i In row 1.
  Caused by error:
  ! `..1` must be a logical vector, not a <tbl_df/tbl/data.frame> object.
  i If you used `across()` to generate this data frame, please use `if_any()` or `if_all()` instead.

Code
  filter(df, tibble(x > 0, y > 0))
Condition
  Error in `filter()`:
  i In argument: `tibble(x > 0, y > 0)`.
  Caused by error:
  ! `..1` must be a logical vector, not a <tbl_df/tbl/data.frame> object.
  i If you used `across()` to generate this data frame, please use `if_any()` or `if_all()` instead.

Code
  filter(gdf, tibble(x > 0, y > 0))
Condition
  Error in `filter()`:
  i In argument: `tibble(x > 0, y > 0)`.
  i In group 1: `x = 1`.
  Caused by error:
  ! `..1` must be a logical vector, not a <tbl_df/tbl/data.frame> object.
  i If you used `across()` to generate this data frame, please use `if_any()` or `if_all()` instead.

Code
  filter(rdf, tibble(x > 0, y > 0))
Condition
  Error in `filter()`:
  i In argument: `tibble(x > 0, y > 0)`.
  i In row 1.
  Caused by error:
  ! `..1` must be a logical vector, not a <tbl_df/tbl/data.frame> object.
  i If you used `across()` to generate this data frame, please use `if_any()` or `if_all()` instead.

filter() doesn't allow data frames with missing or empty names (#6758)

Code
  filter(df1)
Condition
  Error in `filter()`:
  ! Can't transform a data frame with `NA` or `""` names.

Code
  filter_out(df1)
Condition
  Error in `filter_out()`:
  ! Can't transform a data frame with `NA` or `""` names.

Code
  filter(df2)
Condition
  Error in `filter()`:
  ! Can't transform a data frame with missing names.

Code
  filter_out(df2)
Condition
  Error in `filter_out()`:
  ! Can't transform a data frame with missing names.

can't use .by with .preserve

Code
  filter(df, .by = x, .preserve = TRUE)
Condition
  Error in `filter()`:
  ! Can't supply both `.by` and `.preserve`.

Code
  filter_out(df, .by = x, .preserve = TRUE)
Condition
  Error in `filter_out()`:
  ! Can't supply both `.by` and `.preserve`.

catches .by with grouped-df

Code
  filter(gdf, .by = x)
Condition
  Error in `filter()`:
  ! Can't supply `.by` when `.data` is a grouped data frame.

Code
  filter_out(gdf, .by = x)
Condition
  Error in `filter_out()`:
  ! Can't supply `.by` when `.data` is a grouped data frame.

catches .by with rowwise-df

Code
  filter(rdf, .by = x)
Condition
  Error in `filter()`:
  ! Can't supply `.by` when `.data` is a rowwise data frame.

Code
  filter_out(rdf, .by = x)
Condition
  Error in `filter_out()`:
  ! Can't supply `.by` when `.data` is a rowwise data frame.

catches by typo (#6647)

Code
  filter(df, by = x)
Condition
  Error in `filter()`:
  ! Can't specify an argument named `by` in this verb.
  i Did you mean to use `.by` instead?

Code
  filter_out(df, by = x)
Condition
  Error in `filter_out()`:
  ! Can't specify an argument named `by` in this verb.
  i Did you mean to use `.by` instead?

dplyr documentation built on Feb. 3, 2026, 9:08 a.m.