R course: Advanced modules

Category: Skill course
Credit points: 0.2 per day


1.  Concept

This modular seminar addresses everybody who is interested in improving existing R skills.

There will be

  • a little theory
  • focus on technical aspects (not on interpretation)
  • time for questions and answers
  • hands-on training based on the requests you write in the comment field of the registration form. Feel free to approach us with your data

Prerequisites: Basic knowledge of a language of scientific computing: R, Matlab (exercises will be in R) which are taught in the course 'R - The basics'

Lecturer: Thomas Wutzler


2.  Place and time

  • When? June 18-20, 2018, start: 9:30 am and 13:30 pm
  • Where? MPI for Biogeochemistry, Seminar room B0.004

3.  Registration

Register here by June 4, 2018.



More R… Here is a list of useful online resources to accelerate your progress.


4.  What you need to prepare

Please make sure that a recent version of R is running on your laptop.
You can download the most recent version here: http://www.r-project.org/
RStudio is a new open-source integrated development environment that runs on all platforms. It nicely combines console, script editor, working directory, plots etc. into a an uncluttered layout that you can easily navigate. You need to have R installed before you can use RStudio as a development environment.

Please also make sure that you can access the internet via WLAN (BGC-users, if you have a BGC-account; BGC-guests, if you don't have an account)

Course material on owncloud (pw international MP research school)


5.  Agenda

5.1  The Tidyverse

  • get data in the right shape using tidyr (90 min)
  • data science using dplyr (85 min)
  • working with subsets of data using nest and map (30min)
  • graphically explore datasets using ggplot (110 min)

5.2  Programming

  • Organizing your code (100 min)
    • Writing R-packages
    • Documentation using inlinedocs
    • Locating bugs: Debugging

5.3  Concepts

  • Under the hood of R (100 min)
    • Environments
    • Frames
    • Copy-Reference Semantics
  • Intro to Object Orientation in R (95 min)

5.4  Speeding up your computation

  • locating bottlenecks
  • vectorizing
  • linking to low level code (examples C and C++)
  • parallel computing with the parallel package

5.5  Selected applications

  • selected by interest of the students alternatively,
    • optimization: finding parameters with optim
    • dynamic modelling using the deSolve package
    • Intro to the git revision control system
    • ... open for requests if issued early enough

6.  Feedback

The survey gives feedback of 6 (out of 12) participants. Statistics and statements should not be taken as an exhaustive or exclusive list.

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