Data Science Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface Data Science Introducing R R Constructs R Tasks R Strings R Read, Write, and Create Data Template Data Exploration Data Wrangling Data Visualisation Statistics ML Template ML Scenarios ML Activities ML Applications ML Algorithms Cluster Analysis Decision Trees Computer Vision Graph Data Privacy Literate Data Science Coding with Style Resources Bibliography Index

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Knitr Resources

We list below other resources that augment the material we have presented in this chapter.

• Xie (2014) delves much further into knitr and LaTeX and other document formats supported by knitr.
• Gandrud (2014) delves not only into knitr, LaTeX, R and , but also the suite of tools available for the professional data scientist, including utilities such as make, git, and shell.
• http://yihui.name/knitr/ is knitr's home. This includes documentation on knitr and useful discussion forums.
• The knitr author's presentation on knitr http://yihui.name/slides/2012-knitr-RStudio.html. The presentation provides a basic introduction to knitr.
• http://bcb.dfci.harvard.edu/~aedin/courses/ReproducibleResearch/ReproducibleResearch.pdf This lecture provides some insights into literate programming in R.
• LaTeX supports many characters and symbols but finding the right incantation is difficult. This web site, http://detexify.kirelabs.org/classify.html, does a great job. Draw the character you want and it will show you how to get it .