Replace loops with purrr. Covers map, map2, pmap, walk, reduce, safely, and other functional programming tools in the tidyverse.
Tutorial series
Tidyverse Workflow
12 tutorials — follow in order for the best learning path.
- Functional Programming with purrr
- Pivoting Data with tidyr
Convert data between wide and long formats using tidyr's pivot_longer and pivot_wider functions, with practical examples.
- Introduction to the Tidyverse
Learn the fundamentals of the Tidyverse—a collection of R packages for data science. Discover how dplyr, ggplot2, tidyr, and more transform data analysis.
- Data Manipulation with dplyr
Transform, filter, and summarize data with dplyr — the core tidyverse package. Covers filter, select, mutate, arrange, and group_by.
- Importing Data with readr
Learn to import CSV, TSV, and delimited files into R using readr. Covers column types, locale settings, and common pitfalls.
- Reshaping Data with tidyr
A complete guide to pivoting data between wide and long formats using tidyr's pivot_longer() and pivot_wider() functions.
- Fast File Import with readr
Learn how to efficiently import flat files into R using the readr package. Covers CSV, TSV, delimited files, column types, and performance tips.
- Text Manipulation with stringr
Manipulate text in R with stringr. Covers concatenation, pattern matching, regex, case conversion, trimming, padding, and interpolation inside dplyr pipelines.
- String Manipulation with stringr
Master string manipulation in R with the stringr package. Learn pattern matching, string extraction, replacement, and whitespace handling.
- Functional Iteration with purrr
Learn map(), map2(), pmap() for iterating over data and handle errors with safely(), possibly(), quietly().
- Working with dates in R using lubridate: a tutorial
Work with dates and times in R using the lubridate package. Parse, format, extract components, compute durations, and handle timezones safely.
- Handling Factors with forcats
Learn how to manage categorical data in R using the forcats package. Master factor creation, reordering, lumping, and recoding.