gregorp

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": "s3:ListBucket",
            "Resource": "arn:aws:s3:::project-evident-cnmi",
            "Condition": {
                "StringEquals": {

gregorp

while(working) {
  drink(coffee)
  do(work)
  if(is_empty(coffee)) {
    if(is_empty(cofeepot)) {
       coffeepot <- brew(coffeepot)
    }
    coffee <- refill(coffee)
  }
}

gregorp

get_license_info = function() {
  lic_info = available.packages(filters = c("CRAN", "duplicates"),
                                fields = "License")[, c("Package", "License")]
  lic_info = as.data.frame(lic_info, stringsAsFactors = FALSE)
  
  # take a stab at identifying GPL 3 packages without other license options
  lic_info$GPL3 = grepl("GPL.*3", lic_info$License) & !grepl("\\|", lic_info$License)
  return(lic_info)
}

gregorp

library(lmer)
library(lmerTest)

# Comparing the `lmer` output on identical data frames, one in a list, one not.
# This example uses data built in to the `lme4` package, and the model in the `?lmer` help examples.

## split data into two groups by subject
subject_sample = sample(unique(sleepstudy$Subject), size = length(unique(sleepstudy$Subject)) / 2)

sleep_split = split(sleepstudy, f = sleepstudy$Subject %in% subject_sample)

gregorp

# p1 (1-10) is attribute - determines d: number of sides of dice
# p2 (1-10) is skill - determines k: number of dice to keep
# p1 + p2 determines n: the number of dice to roll

pp = expand.grid(p1 = 1:10, p2 = 1:10)

library(dplyr)
library(tidyr)

pp = pp %>% mutate(

gregorp

#' Sample of an object.
#' 
#' Shortcut for checking on data.
#' @rdname samp
#' @param x data.frame (or matrix) to sample from
#' @param n number of rows to sample (default is 10)
#' @return n random rows of x
#' @export
samp <- function(x, n) {
    UseMethod("samp")