Jordan Mark Barbone jmbarbone

fooReferenceClass <- setRefClass(
  "fooReferenceClass",
  fields = list(
    private = "environment",
    n = "integer"
  )
)

# create a list of values that will be transfered to private.  alternatively,

df <- palmerpenguins::penguins

bench::mark(
  rowwise = df |> 
    dplyr::rowwise() |> 
    dplyr::mutate(sum = sum(dplyr::c_across(c(bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g)))) |> 
    dplyr::ungroup(),
  rowSums = df |>

do.call(rbind, lapply(
  list(
    integer      = 1L,
    integerish   = 1.0,
    double       = 1.1,
    factor       = factor("a"),
    date_double  = structure(19486, class = "Date"),
    date_integer = structure(19486L, class = "Date"),
    time_double  = structure(1683663687, class = c("POSIXct", "POSIXt")),

	text <- {
	"
	Line 1 \n info
	Line 2 \n info
	Line 3
	Line 4
	"
	}
	print(text)
	#> [1] "\n Line 1 \n info\n Line 2 \n info\n Line 3\n Line 4\n "

	spearman_ci <- function(x, y, alpha = 0.95, method = c("norm", "t")) {
	# modified from https://stats.stackexchange.com/questions/18887/how-to-calculate-a-confidence-interval-for-spearmans-rank-correlation/506367#506367
	method <- mark::match_param(method)
	ok <- stats::complete.cases(x, y)
	x <- x[ok]
	y <- y[ok]
	r <- cor(x, y, method = "spearman")
	n <- sum(ok)
	q <- switch(
	method,


	x <- psych::sat.act$ACT
	y <- psych::sat.act$SATQ + psych::sat.act$SATV

	ft <- equate::freqtab(data.frame(x, y))


	eq0 <- equate::equate(
	x = ft,
	type = "equipercentile",

	# function has been repurposed
	# a few edits from the original have been made without testing

	#' Run length encode
	#'
	#' Encodes a run length and returns the start and stop
	#'
	#' @param x A vector of values for compute the length of the run
	#' @param times If `NULL` will use the position of the start and stop runs,
	#' otherwise will return the values returned; if not `NULL`, must be equal

	datarows <- function(...) {
	ls <- list(...)
	w <- which(vapply(ls, inherits, NA, "formula"))
	n <- length(w)
	cols <- as.character(ls[w])
	cols <- substr(cols, 2, nchar(cols))
	ls <- ls[-w]
	sa <- seq_along(ls)
	sa <- (sa - 1) %% n
	res <- lapply(split(ls, sa), unlist)

	x <- c("apple", "banana", "orange", "pear", "grape")
	p <- "[aeoiu][^(aeiou)]"

	regexpr(p, x) # integer vector
	#> [1] 1 2 1 3 3
	#> attr(,"match.length")
	#> [1] 2 2 2 2 2
	#> attr(,"index.type")
	#> [1] "chars"
	#> attr(,"useBytes")

	do_call <- function(fun, ...) {
	fun <- match.fun(fun)
	forms <- as.list(formals(fun))
	params <- list(...)
	nms <- names(params)

	o <- order(match(nms, names(forms)))
	params <- params[o]
	nms <- nms[o]