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.
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).
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.
2.1 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), andctdTrim()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