week6.Rmd

---
title: "Week 6"
output:
  html_document:
    toc: true
    toc_depth: 3
    include:
      after_body: footer.html
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, error=TRUE)
```

## Intro to R packages

* [Lecture Video](https://youtu.be/mIGIRzMxSG0)
* [The lecture notes](week6-packages.html)

## Notes from Q&A

* [GitHub info on large files](https://docs.github.com/en/github/managing-large-files/working-with-large-files/conditions-for-large-files)

## Helpful FIT/NOAA resources

* [FIT Resources](https://github.com/nmfs-fish-tools/Resources) License, disclaimer and NOAA footer for your packages here.
* [FIT Resources blog](https://noaa-fisheries-integrated-toolbox.github.io/resources/) Scroll down the navbar on left to see coding resources.
* [Package review template](https://github.com/nmfs-general-modeling-tools/nmfs-general-modeling-tools.github.io/blob/master/.github/ISSUE_TEMPLATE/r-package-code-review.md) 
* [FIT NOAA Themed pkgdown](https://noaa-fisheries-integrated-toolbox.github.io/resources/workshops/NOAA-pkgdown/)
* [Code Testing](https://noaa-fisheries-integrated-toolbox.github.io/resources/best-practices/code-testing/)
* [Code review](https://noaa-fisheries-integrated-toolbox.github.io/resources/best-practices/code-review/)
* [NMFS Reports](https://emilymarkowitz-noaa.github.io/NMFSReports/) Check out this package by Emily Markowitz at AFSC for making NMFS Reports with proper branding and structure.

## Example R packages

* [MyNewPackage](https://github.com/RWorkflow-Workshop-2021/MyNewPackage) The package I made during class. You can also open on [RStudio Cloud](https://rstudio.cloud/project/2574138) and build it from there.
* [VRData](https://nwfsc-math-bio.github.io/VRData/) This is the data package that I spent the most time on in lecture.
* [SardineForecast](https://github.com/eeholmes/SardineForecast) Data package for a recent paper of mine. 
  * This one had a lot of preprocessing which is in the `inst/extdata` folder. The data documentation is in [`R/data.R`](https://github.com/eeholmes/SardineForecast/blob/master/R/data.R). I don't recommend putting all the data background into one R file. It drove me nuts.
  * 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 `man` 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.
  * 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.\
  * For the paper tables and figures, I used `library(SardineForecast)`. 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.