Last updated: 2019-04-10
Checks: 5 1
Knit directory: rrresearch/
This reproducible R Markdown analysis was created with workflowr (version 1.2.0). The Report tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
The R Markdown is untracked by Git. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
The command set.seed(20190216) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: .DS_Store
Ignored: .Rhistory
Ignored: .Rproj.user/
Ignored: analysis/.DS_Store
Ignored: analysis/assets/
Ignored: assets/
Ignored: data/metadata/
Ignored: data/raw/
Ignored: demos/demo-rmd-0_files/
Ignored: demos/demo-rmd-1_files/
Ignored: demos/demo-rmd_files/
Ignored: docs/.DS_Store
Ignored: docs/assets/.DS_Store
Ignored: docs/assets/img/.DS_Store
Ignored: docs/demo-rmd-0_files/
Ignored: docs/demo-rmd-1_files/
Ignored: docs/demo-rmd-2_files/
Ignored: docs/demo-rmd-3_files/
Ignored: docs/demo-rmd_files/
Ignored: docs/index-demo-pre_files/
Ignored: figure/
Ignored: install.R
Ignored: rmd/
Ignored: slides/libs/
Untracked files:
Untracked: analysis/setup.Rmd
Unstaged changes:
Modified: analysis/_site.yml
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
There are no past versions. Publish this analysis with wflow_publish() to start tracking its development.
This workshop assumes you have the R, RStudio and Git and Bash Shell software installed on your computer and a personal GitHub account.
R can be downloaded here.
RStudio is an environment for developing using R.
It can be downloaded here. You will need the Desktop version (> 1.0) for your computer.
Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.
cmd and press [Enter])
setx HOME “%USERPROFILE%”
SUCCESS: Specified value was saved.
exit then pressing [Enter]
This will provide you with both Git and Bash in the Git Bash program.
The default shell in all versions of Mac OS X is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal.
The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.
Required for the Version Control part of the the course
Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com. You will need a supported web browser (current versions of Chrome, Firefox or Safari, or Internet Explorer version 9 or above).
You will also need an account at github.com.
Basic GitHub accounts are free. We encourage you to create a GitHub account if you don’t have one already. Please consider what personal information you’d like to reveal. For example, you may want to review these instructions for keeping your email address private provided at GitHub.
Git should be installed on your computer as part of your Bash install (described above).
For OS X 10.9 and higher, install Git for Mac by downloading and running the most recent “mavericks” installer from this list. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program. For older versions of OS X (10.5-10.8) use the most recent available installer labelled “snow-leopard” available here.
If Git is not already available on your machine you can try to install it via your distro’s package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo yum install git.
For the final practical sessions, we will need to use LaTeX. If you don’t have LaTeX installed, consider installing TinyTeX, a custom LaTeX distribution based on TeX Live that is small in size but functions well in most cases, especially for R users.
Check docs before before installing.
devtools requirementsYou might also need a set of development tools to install and run devtools. On Windows, download and install Rtools, and devtools takes care of the rest. On Mac, install the Xcode command line tools. On Linux, install the R development package, usually called r-devel or r-base-dev.
I personally prefer to use a non-institutional email for registering accounts to platforms I want smooth access to regardless of affiliation. However, there are advantages associated with affiliation with an academic institution on GitHub, namely that you get a free developer account. The most important benefit of that is that it gives you unlimited public AND private repositories.
You can however add your academic email as a secondary email which will allow you to benefit from this academic research discount. You can also just use your academic address from the start and just change it once you move on.
Find out more about claiming an academic discount here.
R version 3.5.2 (2018-12-20)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.3
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] workflowr_1.2.0 Rcpp_1.0.1 digest_0.6.18
[4] rprojroot_1.3-2 backports_1.1.3 git2r_0.24.0.9001
[7] magrittr_1.5 evaluate_0.13 stringi_1.3.1
[10] fs_1.2.7 rmarkdown_1.12 tools_3.5.2
[13] stringr_1.4.0 glue_1.3.1 xfun_0.5
[16] yaml_2.2.0 compiler_3.5.2 htmltools_0.3.6
[19] knitr_1.22