Skip to main content

Create Beamer/knitr Lecture Slideshow with Bash, Explain the Script with knitr

Setting up a beamer slideshow is tedious. Creating new slideshows with the same header/footer/style files every week for your course lectures is very very tedious.

To solve this problem I created a simple bash shell script. When you run the script in your terminal it asks whether you want to create a "Lecture" or "Seminar" and what number you want it to have. Then it does the rest.

You can find the script and all of the necessary files here.

To create the README file I used knitr version 0.8's new engine='bash' option. This allows you to knit bash code into your Markdown file the same what you would R code. It's pretty simple. See the R Markdown file for more details.

Please feel free to take and modify the files. Also, if you can help streamline them that would be great.

Oh kind of related tip: If you want a bash command to show up over more than one line in your knitted document place a backslash (\) at the end of the line.


The beamer theme I use is based on something I hammered together awhile ago. See this post for more details.

Comments

jkeirstead said…
Hi Christopher,

I had the same problem too and created a Python-based solution which I called Lectures. It's reasonably similar to your approach and I hope to add some new features in the coming term.

James
James

Nice, I like your solution to the problem too.

Popular posts from this blog

Slide: one function for lag/lead variables in data frames, including time-series cross-sectional data

I often want to quickly create a lag or lead variable in an R data frame. Sometimes I also want to create the lag or lead variable for different groups in a data frame, for example, if I want to lag GDP for each country in a data frame.I've found the various R methods for doing this hard to remember and usually need to look at old blogposts. Any time we find ourselves using the same series of codes over and over, it's probably time to put them into a function. So, I added a new command–slide–to the DataCombine R package (v0.1.5).Building on the shift function TszKin Julian posted on his blog, slide allows you to slide a variable up by any time unit to create a lead or down to create a lag. It returns the lag/lead variable to a new column in your data frame. It works with both data that has one observed unit and with time-series cross-sectional data.Note: your data needs to be in ascending time order with equally spaced time increments. For example 1995, 1996, 1997. ExamplesNot…

A Link Between topicmodels LDA and LDAvis

Carson Sievert and Kenny Shirley have put together the really nice LDAvis R package. It provides a Shiny-based interactive interface for exploring the output from Latent Dirichlet Allocation topic models. If you've never used it, I highly recommend checking out their XKCD example (this paper also has some nice background).LDAvis doesn't fit topic models, it just visualises the output. As such it is agnostic about what package you use to fit your LDA topic model. They have a useful example of how to use output from the lda package.I wanted to use LDAvis with output from the topicmodels package. It works really nicely with texts preprocessed using the tm package. The trick is extracting the information LDAvis requires from the model and placing it into a specifically structured JSON formatted object.To make the conversion from topicmodels output to LDAvis JSON input easier, I created a linking function called topicmodels_json_ldavis. The full function is below. To use it follow …

Dropbox & R Data

I'm always looking for ways to download data from the internet into R. Though I prefer to host and access plain-text data sets (CSV is my personal favourite) from GitHub (see my short paper on the topic) sometimes it's convenient to get data stored on Dropbox. There has been a change in the way Dropbox URLs work and I just added some functionality to the repmis R package. So I though that I'ld write a quick post on how to directly download data from Dropbox into R. The download method is different depending on whether or not your plain-text data is in a Dropbox Public folder or not.Dropbox Public FolderDropbox is trying to do away with its public folders. New users need to actively create a Public folder. Regardless, sometimes you may want to download data from one. It used to be that files in Public folders were accessible through non-secure (http) URLs. It's easy to download these into R, just use the read.table command, where the URL is the file name. Dropbox recent…