yannabraham

## reproduce the figures from http://www.jstatsoft.org/v28/c01/paper using ggplot2

library(ggplot2)

## parameters
set.seed(2710)

## Figure 1
d <- rnorm(50)

dergachev

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

Chaser324

Whether you're trying to give back to the open source community or collaborating on your own projects, knowing how to properly fork and generate pull requests is essential. Unfortunately, it's quite easy to make mistakes or not know what you should do when you're initially learning the process. I know that I certainly had considerable initial trouble with it, and I found a lot of the information on GitHub and around the internet to be rather piecemeal and incomplete - part of the process described here, another there, common hangups in a different place, and so on.

In an attempt to coallate this information for myself and others, this short tutorial is what I've found to be fairly standard procedure for creating a fork, doing your work, issuing a pull request, and merging that pull request back into the original project.

Creating a Fork

Just head over to the GitHub page and click the "Fork" button. It's just that simple. Once you've done that, you can use your favorite git client to clone your repo or j

jennybc

---
title: "twee demo"
author: "Jenny Bryan"
date: "17 August, 2014"
output:
  html_document:
    toc: TRUE
    keep_md: TRUE
---

zross

library(knitr)
opts_chunk$set(collapse=TRUE, echo=TRUE, 
               error=FALSE, message=FALSE, 
               warning=FALSE, cache=FALSE)

s0 <- knitr::knit_hooks$get('source')
o0 <- knitr::knit_hooks$get('output')
p0 <- knitr::knit_hooks$get('plot')

knitr::knit_hooks$set(

apreshill

aschleg

games.howell <- function(grp, obs) {
  
  #Create combinations
  combs <- combn(unique(grp), 2)
  
  # Statistics that will be used throughout the calculations:
  # n = sample size of each group
  # groups = number of groups in data
  # Mean = means of each group sample
  # std = variance of each group sample

jeroen

library(magick)
library(magrittr)

# Convert to 'ico' format
image_read("https://www.r-project.org/logo/Rlogo.png") %>%
	image_scale("32x32!") %>% # remove the "!" after 32x32 to scale proportionally
	image_write("favicon.ico", format = "ico")


# Favicon can also be png/gif

bearloga

# WMF only:
if (file.exists("/etc/wikimedia-cluster")) {
  message('Detected that this script is being run on a WMF machine ("', Sys.info()["nodename"], '"). Setting proxies...')
  Sys.setenv("http_proxy" = "http://webproxy.eqiad.wmnet:8080")
  Sys.setenv("https_proxy" = "http://webproxy.eqiad.wmnet:8080")
}

# General use:
message("Checking for a personal library...")
if (!dir.exists(Sys.getenv("R_LIBS_USER"))) {

trestletech

download.file("https://ndownloader.figshare.com/articles/5170705/versions/1", "kd.zip")
unzip("kd.zip")

library(readr)

words <- readr::read_csv("KSP-Word.csv")
users <- readr::read_csv("KSP-User.csv")
entries <- readr::read_csv("KSP-Entry.csv")
keypress <- readr::read_csv("KSP-KeyPress.csv")
pressure <- readr::read_csv("KSP-Pressure.csv")