jeromyanglim/rmarkdown-rmeetup-2012

Reproducible analysis with knitr, R Markdown, and RStudio: Slides and example R Markdown files from the presentation

rmarkdown-rmeetup-2012's Issues

Controlling image size in a simple way in Markdown

I've found that using the default image option,

 ![my image](My_image.png)

that the image was way too large.

What is a good strategy for incorporating images into slides at the appropriate size?

What are the benefits of knitr over Sweave?

Setting up a knitr analysis on a fresh Windows install

I run Linux, but I sometimes need to give an R script to someone to run an automated production process involving knitr that is going to run on Windows. The user of the script does not necessarily no much about R and their machine does not come pre-configured for R or knitr.

What steps need to be taken?

...

What is a good workflow for taking screenshots and incorporating them into presentation on Ubuntu for latex/markdown/etc.?

On Windows, I used to press print screen then select the region and then paste into the document.

For markdown, beamer, latex, etc. I need to save the file in a particular location with a relevant name and then incorporate the name into the source file.

What's a quick way of doing that?

What are useful pandoc commands for someone working with knitr and R Markdown?

Diagnosing pandoc error messages and combining latex with pandoc

I issue this command:

$ pandoc -o talk.tex talk.md  

and I get this error message

pandoc: 
Error:
"source" (line 112, column 1):
unexpected end of input
expecting "\\" or "$"

It seems to emerge once I add

\begin{document}

to my pandoc file. How can this be fixed?

What is the decision process that leads to R Markdown or some other document creation strategy?

What are the most important things to know about knitr R code chunk options for a beginner?

How to incorporate notes into pandoc markdown for beamer that don't display on slide pdfs but can be used for other purposes?

How to show images in Markdown generated from R Markdown on github?

I have a few github repositories that have multiple R Markdown files with each R Markdown file in a separate folder.

I want to be able upload these repositories and I want the images to display when someone clicks on a Markdown file.

At the moment, it's accessing the blob version and not the raw version, which is causing issues.

I asked about a general solution to the problem on Stack Overflow.

A general solution is to change the base.url setting

opts_knit$set(base.url='https://github.com/.../raw/.../')

For one particular file I wrote the following:

```{r echo = FALSE}
github_baseurl <- 'https://github.com/jeromyanglim/gelman-bayesian-data-analysis/raw/master/'

filepath <- strsplit(getwd(), '/')[[1]]
# assumes that markdown file is stored in a folder below master
markdown_folder <- filepath[length(filepath)]
image_base_url <- paste0(github_baseurl, markdown_folder, '/')

opts_knit$set(base.url=image_base_url)
```

However, this needs to be done at the very end otherwise preliminary compilations will not display properly on the local computer because the images are not available on github.

Thus, I'm looking for a general solution to this problem.

This also links into my general need to have a single makefile that will convert rmd files to md files in all folders of a repo with github friendly images.

What are the degrees of reproducible data analysis?

I was wanting to conceptualise reproducible data analysis in a broader context.

• What are the different ways that reproducible data analysis can be achieved?
• How do such degrees relate to achieving the aims of reproducible analysis?
• What are the different aspects of reproducible data analysis?

markdown to beamer-pdf or markdown to latex to post processing to beamer-pdf

I really like the minimum fuss of markdown to beamer-pdf. However, there is the tension that sooner or later you don't like the default choices made or you want to take advantage of powerful features.

Thus,

• What is the best way to override default features?
• What is the best way to use non-standard options?

To a certain extent latex will be just passed through, but sometimes you want to override the default behaviour of Markdon to LaTeX.
Also, sometimes I want to add header information.

What are the main sources that discuss making Beamer presentations with markdown and pandoc?

...

How to prevent latex from corrupting syntax highlighting for Markdown documents in Vim?

An argument for not using reproducible data analysis tools like knitr, Sweave, etc.?

Clearly most researchers don't anlayse their data with reproducible data analysis tools like knitr and Sweave.

• Are there good reasons for not using fully reproducible data analysis tools?
• What are the counter-arguments?
• What can an analysis of not using such tools tell us about the obstacles?

For practical purposes I operationalise reproducible analysis as:

• a one-click build
• code performs all data transformations and analyses
• all data and necessary metadata is provided
• statistical output is automatically incorporated into the final report

knitr or sweave with R and LaTeX and a build script such as a makefile shared as a self-contained archive file is one way of satisfying the above criteria.

What are the main use cases for using the markdown package?

How can I stop github asking me for my password every time I push to github?