Mara Averick batpigandme

See http://animation.r-forge.r-project.org/knitr/ for a preview of all knitr themes in HTML, and http://rclickhandbuch.files.wordpress.com/2014/09/knitrthemesoverview.pdf for a preview in LaTeX (credit to Berry Boessenkool).

The knitr themes manual can be found at (Rnw source).

There are packages for this now!

2017-08-03: Since I wrote this in 2014, the universe, specifically Kirill Müller (https://github.com/krlmlr), has provided better solutions to this problem. I now recommend that you use one of these two packages:

rprojroot: This is the main package with functions to help you express paths in a way that will "just work" when developing interactively in an RStudio Project and when you render your file.
here: A lightweight wrapper around rprojroot that anticipates the most likely scenario: you want to write paths relative to the top-level directory, defined as an RStudio project or Git repo. TRY THIS FIRST.

I love these packages so much I wrote an ode to here.

I use these packages now instead of what I describe below. I'll leave this gist up for historical interest. 😆

This gist shows how to convert a nested JSON file to an R data.frame. To do this, it uses jsonlite and data.tree.

The gist contains two examples: one is a bit simpler, the second one a bit more advanced.

Example 1

In the first example, we download all the repos from Hadley Wickham's Github account from https://api.github.com/users/hadley/repos . This JSON contains a nested owner object. The code shows how to convert that in a flat data.frame in three statements:

line 5: download
line 8: convert to data.tree

About

Updated the queryAPI and created a new function, stattle that wraps it and makes walking easier. jsonlite is great, but I started to bump into some issues with dplyr::bind_rows. Right now these two functions play nice together, but needs to be further tested.

Load/Install

## source the functions
devtools::source_url('https://gist.githubusercontent.com/tcash21/44667f7b8578cc8e061e/raw/fdac84a0a445e448427cc3557e8c9393ce1fa470/queryAPI.r')

	This post examines the features of [R Markdown](http://www.rstudio.org/docs/authoring/using_markdown)
	using [knitr](http://yihui.name/knitr/) in Rstudio 0.96.
	This combination of tools provides an exciting improvement in usability for
	[reproducible analysis](http://stats.stackexchange.com/a/15006/183).
	Specifically, this post
	(1) discusses getting started with R Markdown and `knitr` in Rstudio 0.96;
	(2) provides a basic example of producing console output and plots using R Markdown;
	(3) highlights several code chunk options such as caching and controlling how input and output is displayed;
	(4) demonstrates use of standard Markdown notation as well as the extended features of formulas and tables; and
	(5) discusses the implications of R Markdown.

	## Corey Chivers, 2012 ##
	sim_bayes<-function(p=0.5,N=100,y_lim=20,a_a=2,a_b=10,b_a=8,b_b=3)
	{
	## Simulate outcomes in advance
	outcomes<-sample(1:0,N,prob=c(p,1-p),replace=TRUE)
	success<-cumsum(outcomes)

	for(frame in 1:N)
	{
	png(paste("plots/",1000+frame,".png",sep=""))

	git rebase --interactive HEAD~2

	# we are going to squash c into b
	pick b76d157 b
	pick a931ac7 c

	# squash c into b
	pick b76d157 b
	s a931ac7 c

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

	.tufteize(@gutter, @gap) {
	> p { margin-right: @gutter + @gap; }

	.newthought { font-variant: small-caps; }

	p>strong,
	p>a:not([href^='#'])::before,
	p>a[href^='#'] + * {
	width: @gutter;
	margin-right: -(@gutter + @gap);

	# Twitter Topic Modeling Using R
	# Author: Bryan Goodrich
	# Date Created: February 13, 2015
	# Last Modified: April 3, 2015
	#
	# Use twitteR API to query Twitter, parse the search result, and
	# perform a series of topic models for identifying potentially
	# useful topics from your query content. This has applications for
	# social media, research, or general curiosity
	#