Introduction to this project
This project contains files and code used to write up a short assignment for NFS484-1484.
This README details how this research directory is structured, how files should be run, and what the different files do. The layout and setup of this project was designed for using RStudio and devtools. It is set up this way to make it easy for others to run your code and analyses for themselves and to skaffold onto devtools (used for R package development) because it is well documented and actively maintained. See the excellent R for Data Science online book for more details on how to work with this directory format.
Typical commands used in this workflow include:
- Ctrl-Shift-L (
- Ctrl-Shift-D (
- Ctrl-Shift-K (
devtools::use_package('packagename')(when using another R package)
Using and installing other packages
There is no need to use
library() functions when using a package. Use
devtools::use_package('packagename'), followed by
when using the functions. This approach allows you to make use of devtools features
of using and installing the necessary packages.
To install the dependency packages for this project, simply use:
devtools::install(dependencies = TRUE)
General folder details
The project directory is generally structured with the following folders:
- Base folder (
Base (parent) folder
Contains a few files:
.gitignoretells Git to ignore certain files from being tracked and prevents them from entering the version control history.
.Rbuildignoretells devtools which files to not include when running functions such as
DESCRIPTIONis a standard file included that allows devtools to run it's functions, which in turn make your life easier for running analyses and writing up your results. It provides a description of what the project does and most importantly what R packages your project relies on.
NAMESPACEis also standard for devtools and is used more for others when they view your code and analyses.
.Rprojis the file to dictate that the directory is a RStudio project.
Contains functions and code used by all subsequent
.Rmd files and can
be accessed by documents in the
vignettes/ by using
There are at least four files (probably more):
fetch_data.Rto get, process, and save the dataset.
load_data.Rloads or updates (if
fetch_data.Rhas been changed) the dataset in the
setup.Rto run options for the packages.
functions.Rto hold all custom functions used for the analysis.
zzz.Rholds functions or code that will run automatically after using
Contains the main product of the project: the slides, manuscripts, or other final products.
Contains (at minimum) the main document file that will present the results of the analysis and likely also other files that may supplement the main document.
data/ folder (optional):
data folder contains the analysis-specific dataset. Meaning this dataset
may be a subset of an original dataset, keeping the data relevant to the
research question without keeping the (potentially) larger dataset around.
Since this layout is based on R package development, check out the online book on R package development to learn more about how to make the most use out of this project layout (and why prodigenr structures it this way).