Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
A Scientist's Guide to R: Step 2.4 - forcats for factors
This post is part of a series called A Scientist's Guide to R and focuses on how to work with factors in R using the forcats package.
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resouRces
This content encompasses a comprehensive list of R-related educational materials, packages, tutorials, and datasets with projected dates ranging up to the year 2025. It includes various titles that focus on learning R programming, data analysis, data visualization, geospatial mapping, and statistical methods. Significant emphasis is placed on resources for learning R, such as introductions to R, books, courses, and video tutorials. Additionally, specific packages for data wrangling, statistical modeling, and visualization are mentioned, indicating the evolution and specialization of R's ecosystem to cater to diverse data science needs.
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Working with categorical data in R without losing your mind
Working with categorical data in R without losing your mind - This talk outlines common problems arising from categorical variable transformations in R, and shows strategies to avoid them, using both base R and the Tidyverse.
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Wrangling categorical data in R
This tutorial is a comprehensive guide on how to wrangle categorical data in R. It covers various techniques and functions to manipulate and analyze categorical data, including recoding, reordering, and summarizing categorical variables. The tutorial also provides step-by-step examples and case studies to illustrate the concepts.
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