The R language is becoming the Lingua franca both in data science in general as well as within the ICES community. Recent advancements within R have resulted in that R can no longer be considered as a specific statistical programming language but as a general scientific working environment. This broader environment has resulted in the R has become a natural component of reproducible data analysis and document writing.
Various R packages have often been the backbone of ICES training course and/or workshops. These packages as well as courses are geared towards solving specific pending tasks that tend to come with requirements that the participants are reasonable profi-cient in basic R and that the input data are correctly formatted and available. Any of these requirements have been seen to pose problems.
The course is aimed at covering the fundamental/generic basis of the grammar of data and graphics as well reproducible document writing where R is used as the sole working medium. Recent developments in the R community that are of interest to fisheries science will also be described.
Objective
The objective of the course is to provide participants with a solid foundation in efficient use of the R environment using various typical and familiar fisheries datasets (landings data, catch data, survey data and tagging data) as case examples or by use of “own” data. Emphasis will be put on data munging and literate programming starting with “raw” data (individual stations, individual measurements…) and culminating with deliverance of publishable output produced from a single coded document file.
By the end of the course, the participants:
- Will be able to import data from multitude of sources including the users computer (i.e. own text files, Excel files, Access and sql databases) and via the web.
- Will be able to clean, manipulate, explore, summarize and graph data. This includes being able to:
- Apply best practices in data preparation
- Merge, slice and dice various datasets
- Present results in a summarized form either via tables or graphs
- Will be able to apply the principle of reproducible analysis and report writing from A through Z which are then deliverable through any of the current three common deliverable formats: .html, .pdf and .docx.
- Will be able to produce own functions and understand the principles of creating R packages and social version control coding (through www.github.com).
Level
The course is targeted at fisheries scientist with already have some basic experience in R but are yet not proficient enough to write fluently code for data manipulation, exploration and writing own functions. We believe that some part of the course would also be beneficial to those that are currently productively using R in fisheries science but may along the way have skipped some of the basics and/or are unaware of recent advancements in the R environment when it comes to efficient data handling and processing.
Registration
Registration opens once the course timing has been set.
