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<h1 class="title toc-ignore">Week 6</h1>
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<div id="intro-to-r-packages" class="section level2">
<h2>Intro to R packages</h2>
<ul>
<li><a href="https://youtu.be/mIGIRzMxSG0">Lecture Video</a></li>
<li><a href="week6-packages.html">The lecture notes</a></li>
</ul>
</div>
<div id="notes-from-qa" class="section level2">
<h2>Notes from Q&A</h2>
<ul>
<li><a href="https://docs.github.com/en/github/managing-large-files/working-with-large-files/conditions-for-large-files">GitHub info on large files</a></li>
</ul>
</div>
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<h2>Helpful FIT/NOAA resources</h2>
<ul>
<li><a href="https://github.com/nmfs-fish-tools/Resources">FIT Resources</a> License, disclaimer and NOAA footer for your packages here.</li>
<li><a href="https://noaa-fisheries-integrated-toolbox.github.io/resources/">FIT Resources blog</a> Scroll down the navbar on left to see coding resources.</li>
<li><a href="https://github.com/nmfs-general-modeling-tools/nmfs-general-modeling-tools.github.io/blob/master/.github/ISSUE_TEMPLATE/r-package-code-review.md">Package review template</a></li>
<li><a href="https://noaa-fisheries-integrated-toolbox.github.io/resources/workshops/NOAA-pkgdown/">FIT NOAA Themed pkgdown</a></li>
<li><a href="https://noaa-fisheries-integrated-toolbox.github.io/resources/best-practices/code-testing/">Code Testing</a></li>
<li><a href="https://noaa-fisheries-integrated-toolbox.github.io/resources/best-practices/code-review/">Code review</a></li>
<li><a href="https://emilymarkowitz-noaa.github.io/NMFSReports/">NMFS Reports</a> Check out this package by Emily Markowitz at AFSC for making NMFS Reports with proper branding and structure.</li>
</ul>
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<h2>Example R packages</h2>
<ul>
<li><a href="https://github.com/RWorkflow-Workshop-2021/MyNewPackage">MyNewPackage</a> The package I made during class. You can also open on <a href="https://rstudio.cloud/project/2574138">RStudio Cloud</a> and build it from there.</li>
<li><a href="https://nwfsc-math-bio.github.io/VRData/">VRData</a> This is the data package that I spent the most time on in lecture.</li>
<li><a href="https://github.com/eeholmes/SardineForecast">SardineForecast</a> Data package for a recent paper of mine.
<ul>
<li>This one had a lot of preprocessing which is in the <code>inst/extdata</code> folder. The data documentation is in <a href="https://github.com/eeholmes/SardineForecast/blob/master/R/data.R"><code>R/data.R</code></a>. I don’t recommend putting all the data background into one R file. It drove me nuts.</li>
<li>For my paper, I had an appendix with the data information. To write that, I wrote a script to process the Rd files in the <code>man</code> folder into a Rmd document. So although writing the data documentation was time-consuming, it saved me a lot of time when writing the paper.</li>
<li>The paper also included the data used in the analyses in a table in an appendix. I wrote a script to make that table using this data library.<br />
</li>
<li>For the paper tables and figures, I used <code>library(SardineForecast)</code>. That ensured that all figures and tables used the same and most recent data. There were a number of big data changes that happened in revision, and not having a data package would have made updating the paper much harder.</li>
</ul></li>
</ul>
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<hr>
<div style="text-align: center">
<i class="fas fa-cubes"></i> NWFSC Math Bio Program <i class="fas fa-cubes"></i>
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