R Ladies Freiburg (English) - Intro to R & R-Studio: Zero to sHero {Part 1}

Описание: All materials available on the R-Ladies Freiburg Github repo:
https://github.com/rladies/meetup-pre...

Event was originally live on Zoom:
https://www.meetup.com/rladies-freibu...
Follow us for future

Taught by Kyla McConnell (@McConnellKyla) and Julia Müller (@JuliaMuellerFr), PhD students at the University of Freiburg in Linguistics.

Just getting involved with R or want to level up your skills? Have you used base-R but are still trying to wrap your head around the tidyverse "pipe"? Have a messy dataset and don't know where to start? Seen beautiful visualizations on Twitter and want to make your own?

If you’ve answered ‘yes’ to at least one of these questions, fear no more! In this monthly workshop series, we will walk you through the fundamental uses of tidyverse and ggplot at your own pace with the help of hands-on exercises. Tidyverse and ggplot are a classic combination of R packages that allow you to "wrangle" your unwieldy data into whatever shape you need and creative beautiful and informative visualizations.

Over the course of this series, you will learn the most useful features of R Studio and R Markdown, how to read in and explore data, and transform it into a shape that's easy to work with. You will be able to create new columns and summary tables, subset interesting rows or columns, and combine and reshape dataframes. We will also dive into ggplot, one of the best tools for creating great-looking bar charts, scatterplots, and more!

This is (currently) a five-part series, aimed at total beginners and/or people with some experience in base-R or tidyverse who are looking to freshen up or expand their skills. Feel free to join at any point, we will briefly review the previous topic at the beginning of each session.

January 20th {Part 1}: The R & R-Studio ABCs (packages, files, data types & basic data exploration)
February 17th {Part 2}: Tidy data & introduction to data wrangling (tibbles, renaming, reordering, subsetting)
March 17th {Part 3}: Data wrangling with dplyr (new columns, if-else statements, summary tables, joining dataframes)
April 21st {Part 4}: Introduction to visualizations with ggplot (line graphs, bar charts, scatterplots, histograms, and more!)
May 19th {Part 5}: Advanced topics in wrangling and ggplot (pivoting, ggplot style options, etc.)

Info on installing R and R-Studio here: https://rstudio-education.github.io/h...