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More generic functions #1101

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More generic functions #1101

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01e33be
make `pivot_wider_spec()` and `build_wider_spec()` generic
mgirlich Mar 3, 2021
e1a8e48
make `pivot_longer_spec()` and `build_longer_spec()` generic
mgirlich Mar 3, 2021
f0f9ab0
add missing dots to `build_wider_spec.data.frame()`
mgirlich Mar 3, 2021
adbf9bc
make `uncount()` generic
mgirlich Mar 3, 2021
5682209
make `unnest_longer()` and `unnest_wider()` generic
mgirlich Mar 3, 2021
91c07da
make `hoist()` generic
mgirlich Mar 3, 2021
72e09c8
document()
mgirlich Mar 3, 2021
636926c
make `chop()` generic
mgirlich Mar 3, 2021
95da02c
make `pack()` and `unpack()` generic
mgirlich Mar 3, 2021
245a1c1
document dots in `chop()` and `uncount()`
mgirlich Mar 3, 2021
0e96cf6
move dots in `pivot_*()` functions family
mgirlich Mar 3, 2021
9e3c5cd
move dots in other generics
mgirlich Mar 3, 2021
995fe39
document()
mgirlich Mar 3, 2021
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12 changes: 12 additions & 0 deletions NAMESPACE
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Original file line number Diff line number Diff line change
@@ -1,5 +1,8 @@
# Generated by roxygen2: do not edit by hand

S3method(build_longer_spec,data.frame)
S3method(build_wider_spec,data.frame)
S3method(chop,data.frame)
S3method(complete,data.frame)
S3method(complete_,data.frame)
S3method(drop_na,data.frame)
Expand All @@ -16,13 +19,17 @@ S3method(full_seq,POSIXct)
S3method(full_seq,numeric)
S3method(gather,data.frame)
S3method(gather_,data.frame)
S3method(hoist,data.frame)
S3method(nest,data.frame)
S3method(nest,grouped_df)
S3method(nest,tbl_df)
S3method(nest_legacy,data.frame)
S3method(nest_legacy,tbl_df)
S3method(pack,data.frame)
S3method(pivot_longer,data.frame)
S3method(pivot_longer_spec,data.frame)
S3method(pivot_wider,data.frame)
S3method(pivot_wider_spec,data.frame)
S3method(replace_na,data.frame)
S3method(replace_na,default)
S3method(separate,data.frame)
Expand All @@ -31,11 +38,16 @@ S3method(separate_rows,data.frame)
S3method(separate_rows_,data.frame)
S3method(spread,data.frame)
S3method(spread_,data.frame)
S3method(unchop,data.frame)
S3method(uncount,data.frame)
S3method(unite,data.frame)
S3method(unite_,data.frame)
S3method(unnest,data.frame)
S3method(unnest,rowwise_df)
S3method(unnest_legacy,data.frame)
S3method(unnest_longer,data.frame)
S3method(unnest_wider,data.frame)
S3method(unpack,data.frame)
export("%>%")
export(as_tibble)
export(build_longer_spec)
Expand Down
17 changes: 15 additions & 2 deletions R/chop.R
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Expand Up @@ -40,6 +40,7 @@
#' @param ptype Optionally, supply a data frame prototype for the output `cols`,
#' overriding the default that will be guessed from the combination of
#' individual values.
#' @param ... Additional arguments passed on to methods.
#' @export
#' @examples
#' # Chop ==============================================================
Expand All @@ -66,7 +67,13 @@
#' df <- tibble(x = 1:3, y = list(NULL, tibble(x = 1), tibble(y = 1:2)))
#' df %>% unchop(y)
#' df %>% unchop(y, keep_empty = TRUE)
chop <- function(data, cols) {
chop <- function(data, cols, ...) {
ellipsis::check_dots_used()
UseMethod("chop")
}

#' @export
chop.data.frame <- function(data, cols, ...) {
if (missing(cols)) {
return(data)
}
Expand All @@ -89,7 +96,13 @@ chop <- function(data, cols) {

#' @export
#' @rdname chop
unchop <- function(data, cols, keep_empty = FALSE, ptype = NULL) {
unchop <- function(data, cols, keep_empty = FALSE, ptype = NULL, ...) {
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In general, I think it's better to put the dots before the first optional argument. It's possible that a few people might have relied on partial or position based matching, but check_dots_used() will catch that.

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https://design.tidyverse.org/dots-position.html

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In build_wider_spec() I put the dots after names_from and values_from as they felt like main arguments and that's also how they were used in the test names_glue affects output names

ellipsis::check_dots_used()
UseMethod("unchop")
}

#' @export
unchop.data.frame <- function(data, cols, keep_empty = FALSE, ptype = NULL, ...) {
cols <- tidyselect::eval_select(enquo(cols), data)
if (length(cols) == 0) {
return(data)
Expand Down
13 changes: 12 additions & 1 deletion R/pack.R
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Expand Up @@ -60,6 +60,11 @@
#' df %>% unpack(c(y, z))
#' df %>% unpack(c(y, z), names_sep = "_")
pack <- function(.data, ..., .names_sep = NULL) {
UseMethod("pack")
}

#' @export
pack.data.frame <- function(.data, ..., .names_sep = NULL) {
cols <- enquos(...)
if (any(names2(cols) == "")) {
abort("All elements of `...` must be named")
Expand Down Expand Up @@ -94,7 +99,13 @@ pack <- function(.data, ..., .names_sep = NULL) {
#'
#' See [vctrs::vec_as_names()] for more details on these terms and the
#' strategies used to enforce them.
unpack <- function(data, cols, names_sep = NULL, names_repair = "check_unique") {
unpack <- function(data, cols, names_sep = NULL, names_repair = "check_unique", ...) {
ellipsis::check_dots_used()
UseMethod("unpack")
}

#' @export
unpack.data.frame <- function(data, cols, names_sep = NULL, names_repair = "check_unique", ...) {
check_present(cols)
cols <- tidyselect::eval_select(enquo(cols), data)

Expand Down
33 changes: 31 additions & 2 deletions R/pivot-long.R
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Expand Up @@ -207,8 +207,22 @@ pivot_longer_spec <- function(data,
names_repair = "check_unique",
values_drop_na = FALSE,
values_ptypes = list(),
values_transform = list()
values_transform = list(),
...
) {
ellipsis::check_dots_used()
UseMethod("pivot_longer_spec")
}

#' @export
pivot_longer_spec.data.frame <- function(data,
spec,
names_repair = "check_unique",
values_drop_na = FALSE,
values_ptypes = list(),
values_transform = list(),
...
) {
spec <- check_spec(spec)
spec <- deduplicate_spec(spec, data)

Expand Down Expand Up @@ -271,7 +285,22 @@ build_longer_spec <- function(data, cols,
names_sep = NULL,
names_pattern = NULL,
names_ptypes = NULL,
names_transform = NULL) {
names_transform = NULL,
...) {
ellipsis::check_dots_used()
UseMethod("build_longer_spec")
}

#' @export
build_longer_spec.data.frame <- function(data, cols,
names_to = "name",
values_to = "value",
names_prefix = NULL,
names_sep = NULL,
names_pattern = NULL,
names_ptypes = NULL,
names_transform = NULL,
...) {
cols <- tidyselect::eval_select(enquo(cols), data[unique(names(data))])

if (length(cols) == 0) {
Expand Down
40 changes: 34 additions & 6 deletions R/pivot-wide.R
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Expand Up @@ -186,11 +186,24 @@ pivot_wider.data.frame <- function(data,
#' us_rent_income %>%
#' pivot_wider_spec(spec2)
pivot_wider_spec <- function(data,
spec,
names_repair = "check_unique",
id_cols = NULL,
values_fill = NULL,
values_fn = NULL) {
spec,
names_repair = "check_unique",
id_cols = NULL,
values_fill = NULL,
values_fn = NULL,
...) {
ellipsis::check_dots_used()
UseMethod("pivot_wider_spec")
}

#' @export
pivot_wider_spec.data.frame <- function(data,
spec,
names_repair = "check_unique",
id_cols = NULL,
values_fill = NULL,
values_fn = NULL,
...) {
spec <- check_spec(spec)

if (is.function(values_fn)) {
Expand Down Expand Up @@ -289,8 +302,23 @@ build_wider_spec <- function(data,
names_prefix = "",
names_sep = "_",
names_glue = NULL,
names_sort = FALSE
names_sort = FALSE,
...
) {
ellipsis::check_dots_used()
UseMethod("build_wider_spec")
}

#' @export
build_wider_spec.data.frame <- function(data,
names_from = name,
values_from = value,
names_prefix = "",
names_sep = "_",
names_glue = NULL,
names_sort = FALSE,
...
) {
names_from <- tidyselect::eval_select(enquo(names_from), data)
values_from <- tidyselect::eval_select(enquo(values_from), data)

Expand Down
39 changes: 37 additions & 2 deletions R/rectangle.R
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Expand Up @@ -115,6 +115,11 @@
#'
#' @export hoist
hoist <- function(.data, .col, ..., .remove = TRUE, .simplify = TRUE, .ptype = list(), .transform = list()) {
UseMethod("hoist")
}

#' @export
hoist.data.frame <- function(.data, .col, ..., .remove = TRUE, .simplify = TRUE, .ptype = list(), .transform = list()) {
check_present(.col)
.col <- tidyselect::vars_pull(names(.data), !!enquo(.col))
x <- .data[[.col]]
Expand Down Expand Up @@ -201,8 +206,24 @@ unnest_longer <- function(data, col,
names_repair = "check_unique",
simplify = TRUE,
ptype = list(),
transform = list()
transform = list(),
...
) {
ellipsis::check_dots_used()
UseMethod("unnest_longer")
}

#' @export
unnest_longer.data.frame <- function(data, col,
values_to = NULL,
indices_to = NULL,
indices_include = NULL,
names_repair = "check_unique",
simplify = TRUE,
ptype = list(),
transform = list(),
...
) {

check_present(col)
col <- tidyselect::vars_pull(names(data), !!enquo(col))
Expand Down Expand Up @@ -247,8 +268,22 @@ unnest_wider <- function(data, col,
simplify = TRUE,
names_repair = "check_unique",
ptype = list(),
transform = list()
transform = list(),
...
) {
ellipsis::check_dots_used()
UseMethod("unnest_wider")
}

#' @export
unnest_wider.data.frame <- function(data, col,
names_sep = NULL,
simplify = TRUE,
names_repair = "check_unique",
ptype = list(),
transform = list(),
...
) {
check_present(col)
col <- tidyselect::vars_pull(tbl_vars(data), !!enquo(col))

Expand Down
9 changes: 8 additions & 1 deletion R/uncount.R
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Expand Up @@ -10,6 +10,7 @@
#' identifier for each created row.
#' @param .remove If `TRUE`, and `weights` is the name of a column in `data`,
#' then this column is removed.
#' @param ... Additional arguments passed on to methods.
#' @export
#' @examples
#' df <- tibble(x = c("a", "b"), n = c(1, 2))
Expand All @@ -21,7 +22,13 @@
#'
#' # Or expressions
#' uncount(df, 2 / n)
uncount <- function(data, weights, .remove = TRUE, .id = NULL) {
uncount <- function(data, weights, .remove = TRUE, .id = NULL, ...) {
ellipsis::check_dots_used()
UseMethod("uncount")
}

#' @export
uncount.data.frame <- function(data, weights, .remove = TRUE, .id = NULL, ...) {
weights_quo <- enquo(weights)
w <- dplyr::pull(dplyr::mutate(data, `_weight` = !! weights_quo))
# NOTE `vec_cast()` and check for positive weights can be removed
Expand Down
6 changes: 4 additions & 2 deletions man/chop.Rd
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6 changes: 4 additions & 2 deletions man/hoist.Rd
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2 changes: 1 addition & 1 deletion man/pack.Rd
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8 changes: 6 additions & 2 deletions man/pivot_longer_spec.Rd
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