Statistical programming in R

These notes cover some aspects of:

1. Downloading data in R
2. Managing large desktop-sized files (a few GB in size)
3. Assessing parsing errors from readr
4. Manipulating data quickly with dplyr and data.table (draft)
5. Implementing the split, apply, combine approach with dplyr, and reshaping and plotting with reshape2 and ggplot2
6. Plotting with ggvis

I might also put together notes on visualizing missing data with pheatmap and mi.

To run tutorials 1-4, you’ll either need to replicate the directory structure on your computer or change dataPath (at the top of each tutorial) to wherever you downloaded the data. One way to replicate the directory structure is to clone the repository. If you clone the repository, you can run the code directly from the markdown files.

Thanks, and happy computing!