Welcome to NIVArrr!

This page gathers together useful links and tutorials to help NIVA staff perform data analysis using the R programming language. Whether you’re an experienced R user or just getting to grips with programming for the first time, we hope you’ll find something here to help/interest you.

Contributing

If you know of useful links or tutorials that you think should be added here, please either submit a pull request or contact one of the project administrators (Dag Hjermann, Ciarán Murray or James Sample).

Contents

1. Getting started with R
2. R for biologists and oceanographers

---

1. Getting started with R

1.1. Beginner’s guides

• What is R? - The R-Project home page. Probably not the best place to start, but the official place to start
• R for cats · and cat lovers - A classic, unintimidating guide
• ComputerWorld’s R guide (pdf) - 40-page illustrated pdf, quite nice
• RYouWithMe - Nice, tidyverse-centric (ggplot2 and the like)
• Introduction to R (Univ. of Melbourne) - Again, both Australian and tidyverse-centric

1.2. Installing R and R-Studio at NIVA. Raoul’s Faglunsj guide to installing R and R studio locally on a NIVA computer

1.3. Using NIVA’s Data Science Toolkit. (Only accessible to members of the NIVA-Norge GitHub organisation). A cloud-based platform for data science built around JupyterLab, Python, R and Julia

1.4 Problem solving

• RSeek - Google tailored for R searches. Searches in StackOverflow, R packages etc. Brilliant.
• Stack overflow - Include [r] when you search, in order to avoid answers about Python, Javascript etc.
• CRAN packages - select “Packages” in the left margin. Search using Ctrl+F
• Dag’s Googledocs - If I google something and I find an answer, I usually note it down here. And I google a lot.

2. R for biologists and oceanographers

2.1 Overviews of resources

• [Packages for environmental science (R Task View)](http://cran.r-project.org/web/views/Environmetrics.html
• Fishy packages

2.2 Packages

• oce - Oceanographic analysis - includes for instance tidem() for harmonic analysis of tides, read.ctd() for reading CTD in different formats (Seabird, WOCE, ODF, ODV), and ctdTrim() for locating the descent phase, and trimming data recovered before and after
• pastecs - Analysis of Space-Time Ecological Series - In particular for marine plankton/benthic biology

2.3 Tools/scripts

• Cleaning latin names with errors - R function, with examples