RStudio is the primary R integrated development environment that people learn and work in. Are there alternatives to this iconic program? Why would you want to leave RStudio? The two primary reasons are a need to work with R in an environment where you don't have a graphical interface (e.g., on an HPC) or when you need to automate the running of your code. This Code Club will show you how you can run R from the command line and find tools to replace your favorite functionality from RStudio. This is part of a series of videos demonstrating how to functions from base R to make these data compatible with tools from the tidyverse
You can find my blog post for this episode at [ Ссылка ]
The data were generated in our Kozich et al. 2013 paper ([ Ссылка ]) using samples from the Schloss et al. 2012 paper ([ Ссылка ]).
#R #RStudio #IDE #Rstats
Want more practice on the concepts covered in Code Club? You can sign up for my weekly newsletter at [ Ссылка ] to get practice problems, tips, and insights.
If you're interested in taking an upcoming 3 day R workshop be sure to check out our schedule at [ Ссылка ]
You can also find complete tutorials for learning R with the tidyverse using...
Microbial ecology data: [ Ссылка ]
General data: [ Ссылка ]
0:00 Creating your own R integrated development environment
3:15 Running R from the command line
5:10 Quitting R from the command line
5:37 Running R scripts from the command line
6:01 Find a text editor: nano, vim, emacs, atom, bbedit, sublime, visual studio code
8:55 Integrating version control into a text editor
10:16 Working with figures from outside RStudio
11:16 Getting help from within R at the command line
12:12 Installing and updating packages
13:07 RStudio server
