Getting the most out of R
Physalia-Courses
https://www.physalia-courses.org/
Instructor:
Luis D. Verde Arregoitia (https://liomys.mx)
7–10th February, 2022
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.
Program and materials
All slides are available as downloadable html slide decks (go to each link, right-click on the Download button and save link). Rmd files for creating the slides with xaringan are also available in this repository. These course materials are released under a CC-BY-4.0 License.
Day 1 - Introduction
💽 slides
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Syntax quirks and idiosyncrasies
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Milestones and changes in R through time
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R ‘dialects’
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The file system
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Directory structures, file paths and names
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Project and workflow organization
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Projects, 📦 {
here} and relative paths
Day 2 - Usable data
💽 slides
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Organizing data in spreadsheets
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Principles of rectangular data
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Tools for data rectangling (tidyverse-oriented)
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Data types and missing values
Day 3 - Increasing efficiency
💽 slides
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Iteration, writing loops and using 📦 {
purrr}-
Apply functions to many things at once
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Reading many files at once
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Modifying and exporting multiple objects
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Regular expressions for working with text strings
Day 4 - Overcoming errors and getting unstuck
💽 slides
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Useful addins and helpers
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Friendly online resources
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Building web searches to solve common problems
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Identifying the best solutions
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Creating reproducible examples with the 📦 {
reprex} package
Not part of this course
- Making plots & maps
- Making nice-looking tables
- Statistical analyses
- Package development
- RMarkdown
Contact me if you are interested in hosting a similar version of this course for your team or institution.