mrdwab

cSplit <- function(indt, splitCols, sep = ",", direction = "wide", 
                   makeEqual = NULL, fixed = TRUE, drop = TRUE, 
                   stripWhite = FALSE) {
  message("`cSplit` is now part of the 'splitstackshape' package (V1.4.0)")
  ## requires data.table >= 1.8.11
  require(data.table)
  if (!is.data.table(indt)) setDT(indt)
  if (is.numeric(splitCols)) splitCols <- names(indt)[splitCols]
  if (any(!vapply(indt[, splitCols, with = FALSE],
                  is.character, logical(1L)))) {

mrdwab

stratified <- function(df, group, size, select = NULL, 
                       replace = FALSE, bothSets = FALSE) {
  if (is.null(select)) {
    df <- df
  } else {
    if (is.null(names(select))) stop("'select' must be a named list")
    if (!all(names(select) %in% names(df)))
      stop("Please verify your 'select' argument")
    temp <- sapply(names(select),
                   function(x) df[[x]] %in% select[[x]])

mrdwab

@echo off
if [%1]==[] goto :eof
:loop
pdftk %1 stamp back.pdf output "%~dpn1_new%~x1" owner_pw somepasswordyouwant
shift
if not [%1]==[] goto loop

mrdwab

###############################################################################
#                           Sample Size  and Confidence Interval Calculation  #
#                           v 1.3 by "Ananda Mahto"/mrdwab/ananda@mahto.info  #
#  2011 May 17                                                                #
# --------------------------------------------------------------------------- #
#                                                                             #
#  Example usage:                                                             #
#    * sample.size.table(c.lev = c(90, 95, 98, 99), population = 378)         #
#    * sample.size(c.lev = 98, population = 200)                              #
#    * confidence.interval(c.lev = 95, p.ss = 80, population = 100)           #

mrdwab

REM  *****  BASIC  ***** 
Function CELL_NOTE(vSheet,lRowIndex&,iColIndex%) 
Dim v 
   v = getSheetCell(vSheet,lRowIndex&,iColIndex%) 
   if vartype(v) = 9 then 
      CELL_NOTE = v.Annotation.getText.getString 
   else 
      CELL_NOTE = v 
   endif 
End Function 

mrdwab

LinearizeNestedList <- function(NList, LinearizeDataFrames=FALSE,
                                NameSep="/", ForceNames=FALSE) {
    # LinearizeNestedList:
    #
    # https://sites.google.com/site/akhilsbehl/geekspace/
    #         articles/r/linearize_nested_lists_in_r
    #
    # Akhil S Bhel
    # 
    # Implements a recursive algorithm to linearize nested lists upto any

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)))