Getting the most out of R


ONLINE, 3-6 October 2022 


Due to the COVID-19 outbreak, this course will be held online


Course overview

Many scientists start using R for very specific purposes with little training in computer science, data organization, and software development. Even advanced users may bypass important tools and abstractions which can ultimately lead to bad habits and wasting time. Get the most of R by exploring topics that usually fall outside of data analysis and visualization curricula.
This course will cover blind spots in existing materials by working through the intermediate steps in various pairs of problems and solutions that often get overlooked because of assumed knowledge.

Target audience

R users in scientific fields with a moderate amount of R and RStudio experience, for the most part self-taught, overwhelmed by the amount of resources, and interested in becoming more efficient.



Monday– Classes from 2-8 PM Berlin time

Syntax quirks and idiosyncrasies

Navigating R ‘dialects’

Major changes and milestones in R through time (tidyverse, pipes, native pipes, stringsAsFactors)

Project and workflow organization

Directory structures, file paths and names (storing files in a particular location, with intentional and meaningful names)

Using the {fs} package to work with the file system

Using projects and the {here} package and relative paths

Project templates and organization


Tuesday– Classes from 2-8 PM Berlin time -

Organizing data in spreadsheets

Principles of rectangular data

Tools for data rectangling (tidyverse-oriented)

Data types and missing values


Wednesday– Classes from 2-8 PM Berlin time


Increasing efficiency

Iteration, writing loops and using {purrr} and {furrr}

Apply functions to many things at once

Reading many files at once

Modifying and exporting multiple objects

Useful RStudio (and VSCode) addins and helpers

Regular expressions for working with text strings

Thursday– Classes from 2-8 PM Berlin time


Overcoming errors, understanding what’s wrong and getting unstuck

Friendly online resources

Building web searches to solve common problems

Identifying the best solutions

Creating reproducible examples with the {reprex} package



Cost overview

Package 1







Should you have any further questions, please send an email to

Cancellation Policy:


> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.


Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.