As a user of Anaconda python I have been receiving (Ubuntu) system warnings of low free space in my home directory. Investigating what was causing this I found out that Anaconda python had several versions of each package. The overall size of the
pkgs directory was 14+ GB. After cleaning it is about 3GB.
The second largest directory was my mail in Thunderbird.
So it would be wise, especially if you are limited in disk space, to clean Anaconda. The commands I used are as follows:
conda clean --all conda update conda # just to make sure nothing is broken and # your environment is updated source activate <your-environment> conda update --all conda clean --all
last updated: 2015-08-29
Hands-on dplyr tutorial for faster data manipulation in R Interactive Visualizations From R Using Rcharts rMaps – Interactive Maps from R (github repo) (requires “devtools” from cran)
Using R for Psychological Research – Personality Project, William Revelle
Try R by Code School (on codeschool)
Introduction to R, Leada
see Assorted links – Data Visualization (to be published later)
see Assorted links – Data sources (To be published later)
If you’d like to contribute to this list, please leave them in the comments below.
The open-source world keeps surprising me. It is really amazing how internationally distributed individuals meet and collaborate on open-source projects and develop amazing products that exceed commercially available products. One such example is the development of the R statistical programming language.
Watch the video below and observe how its development since 1997 is similar to the work of ants and bees constructing colonies and hives.
A while ago I published a post on how to install some basic packages in R. This post goes further by sharing with you an Rscript (as part of another Ubuntu customization script) to install many popular R packages.
I’ve written the Rscript to be run after a fresh installation of Ubuntu. The Rscript is called by the Ubuntu customization script (yet to be published) and should install some basic and popular R packages.