# Grouping methods ------------------------------------------------------------
#' Convert row names to an explicit variable.
#'
#' Deprecated, use [tibble::rownames_to_column()] instead.
#'
#' @param df Input data frame with rownames.
#' @param var Name of variable to use
#' @keywords internal
#' @export
#' @examples
#' mtcars %>% tbl_df()
#'
#' mtcars %>% add_rownames()
add_rownames <- function(df, var = "rowname") {
warning(
"Deprecated, use tibble::rownames_to_column() instead.",
call. = FALSE
)
stopifnot(is.data.frame(df))
rn <- as_data_frame(setNames(list(rownames(df)), var))
rownames(df) <- NULL
bind_cols(rn, df)
}
# Grouping methods ------------------------------------------------------------
#' @export
group_by.data.frame <- function(.data, ..., add = FALSE) {
groups <- group_by_prepare(.data, ..., add = add)
grouped_df(groups$data, groups$group_names)
}
#' @export
group_by_.data.frame <- function(.data, ..., .dots = list(), add = FALSE) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
group_by(.data, !!!dots, add = add)
}
#' @export
groups.data.frame <- function(x) NULL
#' @export
ungroup.data.frame <- function(x, ...) x
#' @export
group_size.data.frame <- function(x) nrow(x)
#' @export
n_groups.data.frame <- function(x) 1L
# Manipulation functions ------------------------------------------------------
# These could potentially be rewritten to avoid any copies, but since this
# is just a convenience layer, I didn't bother. They should still be fast.
#' @export
filter.data.frame <- function(.data, ..., .preserve = TRUE) {
as.data.frame(filter(tbl_df(.data), ..., .preserve = .preserve))
}
#' @export
filter_.data.frame <- function(.data, ..., .dots = list(), .preserve = TRUE) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
filter(.data, !!!dots, .preserve = .preserve)
}
#' @export
slice.data.frame <- function(.data, ...) {
slice_impl(.data, quos(...)[[1L]])
}
#' @export
slice_.data.frame <- function(.data, ..., .dots = list()) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
slice_impl(.data, dots[[1L]])
}
#' @export
summarise.data.frame <- function(.data, ...) {
as.data.frame(summarise(tbl_df(.data), ...))
}
#' @export
summarise_.data.frame <- function(.data, ..., .dots = list()) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
summarise(.data, !!!dots)
}
#' @export
mutate.data.frame <- function(.data, ...) {
as.data.frame(mutate(tbl_df(.data), ...))
}
#' @export
mutate_.data.frame <- function(.data, ..., .dots = list()) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
mutate(.data, !!!dots)
}
#' @export
arrange.data.frame <- function(.data, ..., .by_group = FALSE) {
as.data.frame(arrange(tbl_df(.data), ..., .by_group = .by_group))
}
#' @export
arrange_.data.frame <- function(.data, ..., .dots = list(), .by_group = FALSE) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
arrange(.data, !!!dots, .by_group = .by_group)
}
#' @export
select.data.frame <- function(.data, ...) {
# Pass via splicing to avoid matching vars_select() arguments
vars <- tidyselect::vars_select(names(.data), !!!quos(...))
select_impl(.data, vars)
}
#' @export
select_.data.frame <- function(.data, ..., .dots = list()) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
select(.data, !!!dots)
}
#' @export
rename.data.frame <- function(.data, ...) {
vars <- tidyselect::vars_rename(names(.data), !!!quos(...))
select_impl(.data, vars)
}
#' @export
rename_.data.frame <- function(.data, ..., .dots = list()) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
rename(.data, !!!dots)
}
# Joins ------------------------------------------------------------------------
#' @export
inner_join.data.frame <- function(x, y, by = NULL, copy = FALSE, ...) {
as.data.frame(inner_join(tbl_df(x), y, by = by, copy = copy, ...))
}
#' @export
left_join.data.frame <- function(x, y, by = NULL, copy = FALSE, ...) {
as.data.frame(left_join(tbl_df(x), y, by = by, copy = copy, ...))
}
#' @export
#' @rdname join.tbl_df
nest_join.data.frame <- function(x, y, by = NULL, copy = FALSE, keep = FALSE, name = NULL, ... ) {
as.data.frame(nest_join(tbl_df(x), y, by = by, copy = copy, ..., keep = keep, name = name))
}
#' @export
right_join.data.frame <- function(x, y, by = NULL, copy = FALSE, ...) {
as.data.frame(right_join(tbl_df(x), y, by = by, copy = copy, ...))
}
#' @export
full_join.data.frame <- function(x, y, by = NULL, copy = FALSE, ...) {
as.data.frame(full_join(tbl_df(x), y, by = by, copy = copy, ...))
}
#' @export
semi_join.data.frame <- function(x, y, by = NULL, copy = FALSE, ...) {
as.data.frame(semi_join(tbl_df(x), y, by = by, copy = copy, ...))
}
#' @export
anti_join.data.frame <- function(x, y, by = NULL, copy = FALSE, ...) {
as.data.frame(anti_join(tbl_df(x), y, by = by, copy = copy, ...))
}
# Set operations ---------------------------------------------------------------
#' @export
intersect.data.frame <- function(x, y, ...) {
out <- intersect_data_frame(x, y)
reconstruct_set(out, x)
}
#' @export
union.data.frame <- function(x, y, ...) {
out <- union_data_frame(x, y)
reconstruct_set(out, x)
}
#' @export
union_all.data.frame <- function(x, y, ...) {
out <- bind_rows(x, y)
reconstruct_set(out, x)
}
#' @export
setdiff.data.frame <- function(x, y, ...) {
out <- setdiff_data_frame(x, y)
reconstruct_set(out, x)
}
#' @export
setequal.data.frame <- function(x, y, ...) {
out <- equal_data_frame(x, y)
as.logical(out)
}
reconstruct_set <- function(out, x) {
if (is_grouped_df(x)) {
out <- grouped_df_impl(out, group_vars(x))
}
out
}
#' @export
distinct.data.frame <- function(.data, ..., .keep_all = FALSE) {
dist <- distinct_vars(.data, quos(...), .keep_all = .keep_all)
vars <- match_vars(dist$vars, dist$data)
keep <- match_vars(dist$keep, dist$data)
distinct_impl(dist$data, vars, keep)
}
#' @export
distinct_.data.frame <- function(.data, ..., .dots = list(), .keep_all = FALSE) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
distinct(.data, !!!dots, .keep_all = .keep_all)
}
# Do ---------------------------------------------------------------------------
#' @export
do.data.frame <- function(.data, ...) {
args <- quos(...)
named <- named_args(args)
# Create custom data mask with `.` pronoun
mask <- new_data_mask(new_environment())
env_bind_do_pronouns(mask, .data)
if (!named) {
out <- eval_tidy(args[[1]], mask)
if (!inherits(out, "data.frame")) {
bad("Result must be a data frame, not {fmt_classes(out)}")
}
} else {
out <- map(args, function(arg) list(eval_tidy(arg, mask)))
names(out) <- names(args)
out <- tibble::as_tibble(out, validate = FALSE)
}
out
}
#' @export
do_.data.frame <- function(.data, ..., .dots = list()) {
dots <- compat_lazy_dots(.dots, caller_env(), ...)
do(.data, !!!dots)
}
# Random samples ---------------------------------------------------------------
#' @export
sample_n.data.frame <- function(tbl, size, replace = FALSE,
weight = NULL, .env = NULL) {
if (!is_null(.env)) {
inform("`.env` is deprecated and no longer has any effect")
}
size <- enquo(size)
weight <- enquo(weight)
slice(tbl, sample.int(n(), check_size(!!size, n(), replace = replace), replace = replace, prob = !!weight))
}
#' @export
sample_frac.data.frame <- function(tbl, size = 1, replace = FALSE,
weight = NULL, .env = NULL) {
if (!is_null(.env)) {
inform("`.env` is deprecated and no longer has any effect")
}
size <- enquo(size)
weight <- enquo(weight)
slice(tbl, sample.int(n(), round(n() * check_frac(!!size, replace = replace)), replace = replace, prob = !!weight))
}
# Misc -------------------------------------------------------------------------
#' @export
collect.data.frame <- function(x, ...) x
#' @export
compute.data.frame <- function(x, ...) x
#' @export
collapse.data.frame <- function(x, ...) x
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