HW01 and associated peer review has been processed; expect feedback in next ~day
You’ve seen and done all the mechanics now: Git(Hub), R Markdown, HW submission, peer review, Discussion, etc.
- Questions? Comments?
- FYI: We have our own apps working now, on our own server, so peer marks will be submitted that way from now on (instead of via Google form).
Complete our introduction to ggplot2
What’s next?
- Wed we’ll begin data wrangling and aggregation with dplyr
- HW 3 due before class Monday 2014-09-29. It will be making more figures, more sophisticated than last week, and more explorations/summaries of data. Probably Gapminder, though you can ask for approval to use something else. Will cover ggplot2 and dplyr.

there were no slides

Links about things we talked about during open Q and A

Yes, maybe you will want to make truly interactive, web-native graphs instead of embedding PNGs. Course will probably cover ggvis in second half.

ggvis: a “pure R/RStudio” solution (though it is most certainly wrapping Javascript; it’s just shielding the user from that)
rCharts: a package from Ramnath Vaidyanathan providing access to a much richer set of Javascript visualization libraries from R
d3.js: probably the most powerful, most beautiful way to make web native figures
- http://bl.ocks.org/mbostock just stand back and admire

R Markdown is not the only way to get a pretty report. You can also get one from an R script.

When editing a .r file, RStudio offers a button for this is the spiral bound notebook icon, near where the “Knit HTML” button appears for .rmd. Click and you get “Compile Notebook”.
Under the hood, you are using a function called spin() from the knitr package.
Jenny’s ggplot2 demos from her May 2014 tutorial were all made this way
- look at source vs. rendered to get a feel for this
- download the source and render yourself!
Basically, the special comment prefix #' becomes very important
R Markdown: prose is queen, R code is sequestered in special chunks
R script: code is queen, prose is sequestered in special comments
You can get virtually same HTML report either way. Which to choose? Depends whether the report is primary goal (choose .rmd) or a by-product (choose .r).

I passed around hard copies of these 5 books (note: some links to eBooks and repositories are tuned to UBC users):

R Graphics Cookbook by Winston Chang, O’Reilly (2013). The graphs section of his Cookbook for R website will give you a good sense of the book, which contains more material in greater detail.
ggplot2: Elegant Graphics for Data Analysis available via SpringerLink by Hadley Wickham, Springer (2009) | online docs (nice!) | author’s website for the book, including all the code | author’s landing page for the package
R Graphics, 2nd edition available via StatsNetbase by Paul Murrell, Chapman & Hall/CRC Press (2011) | author’s webpage for the book | GoogleBooks search | companion R package, RGraphics, on CRAN
Dynamic documents with R and knitr by Yihui Xie, part of the CRC Press / Chapman & Hall R Series (2013). ISBN: 9781482203530. No online access (yet?).
Reproducible Research with R & RStudio by Christopher Gandrud, part of the CRC Press / Chapman & Hall R Series (2013). ISBN: 978-1466572843. Book website | Examples and code | Book source. No online access (yet?).