Enchufa2

# remotes::install_github("coolbutuseless/eventloop")

Pong <- R6::R6Class(
  "pong",
  
  public = list(
    initialize = function(width=10, height=7, speed=0.02) {
      require(grid)
      private$width <- width
      private$height <- height

moodymudskipper

makeActiveBinding("v", local({
  e <- NULL
  count <- 1
  
  function(value) {
    # increment or reinitialize counter
    exec_env <- sys.frame(-1)
    if(identical(e, exec_env)) {
      count <<- count + 1
    } else {

mrecos

library(shiny)
library(shinydashboard)
# devtools::install_github("nik01010/dashboardthemes")
library(dashboardthemes)
library(tidyverse)
library(sf)
library(leaflet)
library(usmap) # us counties and states as table
library(leaflet)

mpjdem

library(data.table)
library(keypress)

## Create the universe. Well, sort of.
dims <- c(49, 49)
universe <- CJ(x = seq(dims[1]), y = seq(dims[2]), k = 1, cell = FALSE)
universe[, cell := sample(c(FALSE, TRUE), prod(dims), TRUE)]

## Neighbourhood to consider for each cell
neighbours <- CJ(xd = -1:1, yd = -1:1, k = 1)[xd != 0 | yd != 0]

batpigandme

library(tidyverse)

family <- list(
  list(
    "name" = "Bob",
    "age" = 46,
    "mother" = NA,
    "father" = "Big Bob",
    "siblings" = list(NA),
    "children" = list("Tina", "Gene", "Louise"),

emitanaka

<script>
(function() {
  var divHTML = document.querySelectorAll(".details-open");
  divHTML.forEach(function (el) {
    var preNodes = el.getElementsByTagName("pre");
    var outputNode = preNodes[1];
    outputNode.outerHTML = "<details open class='output'><summary>Output</summary>" + outputNode.outerHTML + "</details>";
  })
})();
(function() {

padpadpadpad

# load package
library(ggplot2)

# write function
label_facets <- function(string){
  len <- length(string)
  string = paste('(', letters[1:len], ') ', string, sep = '')
  return(string)
}

dublado

<i>{{.ReadingTime}}{{if gt (mul .ReadingTime 60) 60}}minutes{{else}}minutes or less{{end}} reading</i>

formula
(add .WordCount 212) 213

.ReadingTime

ColinFay

library(tidyverse)
files <- list.files("../open-data/", pattern = "^2017", full.names = TRUE)
full <- map_df(files, read_csv)
dplyr::glimpse(full)

# With names 

files <- list.files("../open-data/", pattern = "^2017", full.names = TRUE) %>% 
  set_names(basename(.))
full <- map_df(files, read_csv, .id = "file")

niw

#!/usr/bin/env bash

# fetch_nike_puls_all_activities.bash
# A simple bash script to fetch all activities and metrics from NikePlus.
# See `nike_plus_api.md` for the API details.

readonly bearer_token="$1"
if [[ -z "$bearer_token" ]]; then
  echo "Usage: $0 bearer_token"
  exit