R: tidyverse for Data Science
R is a powerful, wide-spread and freely available language and environment for statistical computing and graphics.
This twelve-hour-course for intermediate R users focuses on the tidyverse, a collection of R packages for data science. The course is a mixture between brief presentations, demonstrations (on-screen, using R and RStudio) and supervised exercises (“learning by doing”).
General information
| Duration | 12 hours |
|---|
dplyr - Data management & manipulation
ggplot2 - High-level visualisations ("The grammar of graphics")
purrr - Enhanced functional programming
tidyr - Helpers to create tidy data sets
readr - Fast and friendly data import/export
tibble - Modern data frames
ggplot2 - High-level visualisations ("The grammar of graphics")
purrr - Enhanced functional programming
tidyr - Helpers to create tidy data sets
readr - Fast and friendly data import/export
tibble - Modern data frames
Basic knowledge of R, preferably attendance of the course "R: Basic Introduction". You should have an idea of the following expressions and be able to create/perform them in R: vectors, matrices, data.frames, indexing, high- and low level plotting functions for standard plots.
Students and employees of the University of Zurich. This course is particularly suitable for students at the BSc/MSc-level.
Handouts will be distributed during the course. Furthermore, the book from Wickham und Grolemund (Wickham, Hadley; Grolemund, Garrett (2017): R for data science, import, tidy, transform, visualize, and model data, Sebastopol, O'Reilly) would help learners to deepen their understanding of R for data science. It is however no prerequisite for this course.
Dates