2015-02-23_bryan-fields-talk
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jennybc
Talk at Workshop on Visualization for Big Data: Strategies and Principles, Fields Institute http://www.fields.utoronto.ca/programs/scientific/14-15/bigdata/visualization/
2015-02-23_bryan-fields-talk
Talk at Workshop on Visualization for Big Data: Strategies and Principles, Fields Institute
http://www.fields.utoronto.ca/programs/scientific/14-15/bigdata/visualization/
Want to see the slides?
- PDF is in this repo: 2015-02_bryan-fields-talk.pdf
- View same over on SpeakerDeck
Want to see a video of the talk?
Links
The Big Data Brain Drain: Why Science is in Trouble: http://jakevdp.github.io/blog/2013/10/26/big-data-brain-drain/
RStudio IDE: http://www.rstudio.com/products/rstudio/
GitHub: https://github.com
The R Project: http://www.r-project.org
STAT 545: http://stat545-ubc.github.io
Slides from Hadley Wickham's talk in the Simply Statistics Unconference
2014-08-17 NYT article For Big-Data Scientists:, 'Janitor Work' Is Key Hurdle to Insights by Steve Lohr
Data carpentry blog post by David Mimno (response to NYT article re: janitor work)
Daring Fireball's markdown page. Kind of where it all begins, but other references that are more recent and specific to our context are more relevant.
Carson Sievert's talk Reproducible web documents with R, knitr & Markdown
MathJax is an open source JavaScript display engine for mathematics that works in all browsers ... It just works.
MathJax + RStudio specifics:
- RStudio documentation page about Equations in R Markdown
Pandoc: If you need to convert files from one markup format into another, pandoc is your swiss-army knife.
R Markdown: http://rmarkdown.rstudio.com
knitr: http://yihui.name/knitr/
Simple Markdown and R Markdown example files are here: https://github.com/jennybc/2013-11_sfu
Baumer, B., Cetinkaya-Rundel, M., Bray, A., Loi, L., & Horton, N. J. (2014). R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics. Technology Innovations in Statistics Education, 8(1). link
RPubs: http://rpubs.com
RStudio + R Markdown specifics:
- http://www.rstudio.com/ide/docs/authoring/using_markdown
- http://www.rstudio.com/ide/docs/r_markdown
- http://www.rstudio.com/ide/docs/authoring/markdown_notebooks
"FINAL".doc from PHDCOMICS: http://www.phdcomics.com/comics/archive.php?comicid=1531
Jeromy Anglim's blog post Getting Started with R Markdown, knitr, and Rstudio 0.96 and a Gist containing the source
Yihui Xie blog post about when to use Markdown and when to use LaTeX
Git: http://git-scm.com
GitHub: https://github.com
Ram, K 2013. Git can facilitate greater reproducibility and increased transparency in science. Source Code for Biology and Medicine 2013 8:7. Go to the associated github repo to get the PDF (link at bottom of README) and to see a great example of how someone managed the process of writing a manuscript with git(hub).
Karl Broman's tutorial, aimed at stats / data science types: An introduction to Git/Github.
SourceTree Git client, with a GUI. Available for Windows or Mac.
RStudio + Git(Hub)
- http://www.rstudio.com/ide/docs/version_control/overview
- Blog post from The Molecular Ecologist on using GitHub with R and RStudio
xkcd on Git commit messages: http://xkcd.com/1296/
A few R packages on GitHub:
-
dplyr: https://github.com/hadley/dplyr -
broom: https://github.com/dgrtwo/broom -
cats: https://github.com/hilaryparker/cats
GitHub repos from government, media, and more
- https://github.com/WhiteHouse
- https://github.com/chicago
- https://github.com/fivethirtyeight
- https://github.com/TheUpshot
- https://github.com/propublica/
- http://ncip.github.io (NCI’s informatics program)
- https://github.com/LSST (Large Synoptic Survey Telescope)
- https://github.com/ged-lab/ (Titus Brown lab)
- https://github.com/lh3 (Heng Li lab)
- https://github.com/cms-sw/cmssw
- https://github.com/18f
- https://github.com/alphagov
- https://github.com/uwescience
- https://github.com/amplab
- https://github.com/UCL
- https://github.com/USGS-R
- https://github.com/USEPA
- https://github.com/nzherald
- https://github.com/showcases/government
Rough notes on GitHub usage in STAT 545: http://stat545-ubc.github.io/bit004_stat545-use-of-github.html
R Graph Catalog: http://shinyapps.stat.ubc.ca/r-graph-catalog/
A few Shiny apps by STAT 545 students:
- http://shinyapps.stat.ubc.ca/daattali/cancer-data/
- https://github.com/STAT545-UBC/zz_dean_attali-coursework/tree/master/hw/hw11_shiny-app
- https://justinchu.shinyapps.io/MovieLens-app/
- https://github.com/STAT545-UBC/zz_justin_chu-coursework/tree/master/HW11_ShinyApp
- https://dustin21.shinyapps.io/MarketApp
- https://github.com/STAT545-UBC/zz_dustin_johnson-coursework/tree/master/HW11_Shiny-App
- https://jordanbrace.shinyapps.io/Gapminder-Appybara/
- https://github.com/STAT545-UBC/zz_jordan_brace-coursework/tree/master/Shiny-apps/Gapminder-app/Gapminder-Project
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