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# across() captures anonymous functions
Code
(expect_error(capture_across(lf, across(a, function(x) {
x <- x + 2
log(x)
}))))
Output
<error/rlang_error>
Error in `across()`:
! Cannot translate functions consisting of more than one statement.
# across() gives informative errors
Code
capture_across(lf, across(a, 1))
Condition
Error in `across()`:
! `.fns` must be a function, a formula, or list of functions/formulas.
Code
capture_across(lf, across(a, list(1)))
Condition
Error in `across()`:
! `.fns` must contain a function or a formula.
x Problem with 1
Code
capture_across(lf, across(a:b, "log"))
Condition
Error in `across()`:
! `.fns` must be a function, a formula, or list of functions/formulas.
Code
capture_across(lf, across(c, mean))
Condition
Error in `across()`:
! Can't subset columns that don't exist.
x Column `c` doesn't exist.
# across() defaults to everything()
Code
lazy_frame(x = 1, y = 1) %>% summarise(across(.fns = ~ . + 1))
Output
<SQL>
SELECT `x` + 1.0 AS `x`, `y` + 1.0 AS `y`
FROM `df`
# untranslatable functions are preserved
Code
lf %>% summarise(across(a:b, SQL_LOG))
Output
<SQL>
SELECT SQL_LOG(`a`) AS `a`, SQL_LOG(`b`) AS `b`
FROM `df`
# old _at functions continue to work
Code
lf %>% dplyr::summarise_at(dplyr::vars(a:b), "sum")
Condition
Warning:
Missing values are always removed in SQL aggregation functions.
Use `na.rm = TRUE` to silence this warning
This warning is displayed once every 8 hours.
Output
<SQL>
SELECT SUM(`a`) AS `a`, SUM(`b`) AS `b`
FROM `df`
---
Code
lf %>% dplyr::summarise_at(dplyr::vars(a:b), sum)
Output
<SQL>
SELECT SUM(`a`) AS `a`, SUM(`b`) AS `b`
FROM `df`
---
Code
lf %>% dplyr::summarise_at(dplyr::vars(a:b), ~ sum(.))
Output
<SQL>
SELECT SUM(`a`) AS `a`, SUM(`b`) AS `b`
FROM `df`
# across() errors if named
Code
(expect_error(mutate(lf, x = across())))
Output
<error/rlang_error>
Error in `mutate()`:
! In dbplyr, the result of `across()` must be unnamed.
i `x = across()` is named.
Code
(expect_error(group_by(lf, x = across())))
Output
<error/rlang_error>
Error in `group_by()`:
! In dbplyr, the result of `across()` must be unnamed.
i `x = across()` is named.
# across() throws error if unpack = TRUE
Code
(expect_error(lf %>% mutate(across(x, .unpack = TRUE))))
Output
<error/rlang_error>
Error in `mutate()`:
i In argument: `across(x, .unpack = TRUE)`
Caused by error in `mutate()`:
! `.unpack = TRUE` is not supported in SQL translations.
# if_all() gives informative errors
Code
capture_if_all(lf, if_all(a, 1))
Condition
Error in `if_all()`:
! `.fns` must be a function, a formula, or list of functions/formulas.
Code
capture_if_all(lf, if_all(a, list(1)))
Condition
Error in `if_all()`:
! `.fns` must contain a function or a formula.
x Problem with 1
# if_all/any works in filter()
Code
lf %>% filter(if_all(a:b, ~ . > 0))
Output
<SQL>
SELECT *
FROM `df`
WHERE (`a` > 0.0 AND `b` > 0.0)
---
Code
lf %>% filter(if_any(a:b, ~ . > 0))
Output
<SQL>
SELECT *
FROM `df`
WHERE (`a` > 0.0 OR `b` > 0.0)
# if_all/any works in mutate()
Code
lf %>% mutate(c = if_all(a:b, ~ . > 0))
Output
<SQL>
SELECT *, `a` > 0.0 AND `b` > 0.0 AS `c`
FROM `df`
---
Code
lf %>% mutate(c = if_any(a:b, ~ . > 0))
Output
<SQL>
SELECT *, `a` > 0.0 OR `b` > 0.0 AS `c`
FROM `df`
# if_all/any uses every colum as default
Code
lf %>% filter(if_all(.fns = ~ . > 0))
Output
<SQL>
SELECT *
FROM `df`
WHERE (`a` > 0.0 AND `b` > 0.0)
---
Code
lf %>% filter(if_any(.fns = ~ . > 0))
Output
<SQL>
SELECT *
FROM `df`
WHERE (`a` > 0.0 OR `b` > 0.0)
# if_all/any works without `.fns` argument
Code
lf %>% filter(if_all(a:b))
Output
<SQL>
SELECT *
FROM `df`
WHERE (`a` AND `b`)
---
Code
lf %>% filter(if_any(a:b))
Output
<SQL>
SELECT *
FROM `df`
WHERE (`a` OR `b`)
# if_all() cannot rename variables
Code
(expect_error(capture_if_all(lf, if_all(c(a = x, b = y)))))
Output
<error/tidyselect:::error_disallowed_rename>
Error in `if_all()`:
! Can't rename variables in this context.
# across(...) is deprecated
Code
summarise(lf, across(everything(), mean, na.rm = TRUE))
Condition
Warning:
The `...` argument of `across()` is deprecated as of dbplyr 2.3.0.
i Supply arguments directly to `.fns` through a lambda instead.
# Previously across(a:b, mean, na.rm = TRUE)
# Now across(a:b, ~mean(.x, na.rm = TRUE))
Output
<SQL>
SELECT AVG(`x`) AS `x`
FROM `df`
# across() does not support formulas with dots
Code
(expect_error(capture_across(lf, across(a:b, ~ log(.x, base = .y), base = 2))))
Output
<error/rlang_error>
Error in `across()`:
! Can't use `...` when a purrr-style lambda is used in `.fns`.
i Use a lambda instead.
i Or inline them via a purrr-style lambda.
Code
(expect_error(capture_across(lf, across(a:b, list(~ log(.x, base = .y)), base = 2)))
)
Output
<error/rlang_error>
Error in `across()`:
! Can't use `...` when a purrr-style lambda is used in `.fns`.
i Use a lambda instead.
i Or inline them via a purrr-style lambda.
# `pick()` errors in `arrange()` are useful
Code
arrange(df, pick(y))
Condition
Error in `arrange()`:
i In argument: `pick(y)`
Caused by error in `pick()`:
! Can't subset columns that don't exist.
x Column `y` doesn't exist.
# doesn't allow renaming
Code
arrange(lazy_frame(x = 1), pick(y = x))
Condition
Error in `arrange()`:
i In argument: `pick(y = x)`
Caused by error in `pick()`:
! Can't rename variables in this context.
# requires at least one input
Code
arrange(lazy_frame(x = 1), pick())
Condition
Error in `arrange()`:
i In argument: `pick()`
Caused by error in `partial_eval_pick()`:
! Must supply at least one input to `pick()`.
# `filter()` with `pick()` that uses invalid tidy-selection errors
Code
filter(df, pick(x, a))
Condition
Error in `filter()`:
i In argument: `pick(x, a)`
Caused by error in `pick()`:
! Can't subset columns that don't exist.
x Column `a` doesn't exist.
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