mrdwab

upper_left <- function(n, diag = TRUE, byrow = FALSE) {
  x <- seq.int(n)
  tmp1 <- sequence(rev(x))
  tmp2 <- rep(x, rev(x))
  out <- if (byrow) {
    cbind(row = tmp2, col = tmp1)
  } else {
    cbind(row = tmp1, col = tmp2)
  }
  if (diag) out else out[rowSums(out) != n + 1, ]

mrdwab

fun_for <- function(x, target, n) {
  if (!n %in% c(2, 3)) stop("The accounting Elves are crazy!")
  if (n == 2) {
    out <- x[(target - x) %in% x]
  } else if (n == 3) {
    out <- numeric(0)
    for (i in seq_along(x)) {
      s1 <- x + x[i]
      for (j in seq_along(s1)) {
        s2 <- s1 + x[j]

mrdwab

# Using `fread` and `fwrite` to paste together columns like `do.call(paste, ...)`
fpaste <- function(dt, sep = ",") {
  x <- tempfile()
  if (sep == "") {
    data.table(V1 = do.call(stringi::stri_join, c(dt, sep = "")))
  } else {
    fwrite(dt, file = x, sep = sep, col.names = FALSE)
    fread(x, sep = "\n", header = FALSE)
  }
}

mrdwab

## If your replacement is just a sequence of integers the length of the unique values being factored,
##   you can create a function like this which should be quite fast.
fac2int <- function(x, levels, labels = levels, exclude = NA, ordered = is.ordered(x), nmax = NA) {
  as.integer(factor(x, levels, labels, exclude, ordered, nmax))
}

### DIFFERENT APPROACHES TO TEST

fun_datamatrix <- function() {
  df[] <- data.matrix(as.data.frame(lapply(df, factor, levels = df2$Group)))

mrdwab

## SETUP: Sample data and packages

library(data.table)
library(readr)
library(dplyr)
library(iotools)

n <- 5000
set.seed(1)
vals_row <- sample(2000, n, TRUE)

mrdwab

row_wrap <- function(input, ...) {
  UseMethod("row_wrap")
}

row_wrap.data.frame <- function(input, ncols, row_ind = FALSE) {
  if (ncol(input) %% ncols != 0) stop("Number of columns not divisible by desired output")
  data.frame(row_wrap.matrix(input, ncols, row_ind))
}

row_wrap.matrix <- function(input, ncols, row_ind = FALSE) {

mrdwab

#' Calculate the Mean of Already Grouped Data
#'
#' Calculates the mean of already grouped data given the interval ranges and
#' the frequencies of each group.
#'
#' @param frequencies A vector of frequencies.
#' @param intervals A 2-column `matrix` with the same number of rows as
#' the length of frequencies, with the first column being the lower class
#' boundary, and the second column being the upper class boundary. 
#' Alternatively, `intervals` may be a character vector, and you may 

mrdwab

#' All Factors of a Number
#'
#' @param x The number that you want to find the factors of.
#' @examples 
#' factors_of(8)
#' @export
factors_of <- function(x) which(!x %% seq_len(x))

#' Common Factors of Multiple Numbers
#' 

mrdwab

lengthen <- function(vec, length) {
  vec[sort(rep(seq_along(vec), length.out = length))]
}

lengthen(a2, length(a1))
# [1] 1 1 1 3 3 3 4 4 5 5
lengthen(a3, length(a1))
# [1] 1 1 2 2 5 5 6 6 9 9
lengthen(a4, length(a1))
# [1] 5 5 5 1 1 1 3 3 4 4

mrdwab

library(data.table)

## Sample data
L <- list(A = 1:2, B = NULL, C = 3:4)
DF <- data.frame(ID = 1:3, V1 = I(L), V2 = I(unname(L)), V3 = I(setNames(L, c("X", "Y", "Z"))))
DF2 <- data.frame(ID = 1:3, V1 = letters[1:3], V2 = letters[4:6], V3 = letters[7:9])
DF3 <- do.call(rbind, replicate(1000, DF, FALSE))

set.seed(1)
DF4 <- data.frame(ID = 1:300000, V1 = I(rep(L, 100000)), V2 = I(rep(unname(L), 100000)),