As an update to an earlier post, here’s how to use the latest versions of GDAL/PROJ with R spatial packages.
brew install pkg-config
brew install gdal
Next, we need to install a few packages from source in order to use the new GDAL libraries:
Just noticed the Queen is listed as an author in this (and probably other) R packages https://t.co/ehCb3uHjpx #rstats pic.twitter.com/KRKKQvlGX4
— David Smith (`@revodavid`) September 7, 2017
A number of people have been surprised to learn that Her Majesty the Queen is listed as an author on a number of our packages.
For example, in the SpaDES package:
UPDATE: see more recent version of this post here.
I wanted to play around with the new sf package, which requires the latest GDAL (>= 2.0.0), GEOS (>= 3.3.0), and PROJ.4 (>= 4.8.0).
However, the version of GDAL installed via brew is 1.11.4, so I needed to update to the latest version and reinstall a few R packages in order to get sf to work on macOS.
In preparing a presentation on developing R packages using RStudio for the Victoria R Users Meetup Group this month, organizer Kiri Whan and I put together a very simple demo R package.
This is actually really easy to do, but most of the google hits I came across were old (from 2010) or horribly complex (building gdal and proj4 from source then building rgdal itself).
Whenever I used to sit down in front of the computer to write anything other than an email, I would immediately open Microsoft Word and start clacking away on the keyboard. When I switched operating systems (away from Windows) I began using Open Office Writer and even now I still use Libre Office Writer for some of my writing needs. Each of these word processors offer similar sets of tools and can effectively be used for a wide range of writing tasks, from letters to essays, yet I feel most people use Word not because it’s always the best tool for the job, but because it’s ubiquitous and familiar.
Simple, yet for various reasons many people simply don’t. Backing up data and documents is critical in the event of random computer (or, more likely, user) failure. Losing your data sucks. I have seen too many frantic colleagues try to get at data on a failed hard drive: many had some (but not all) of their most important data backed up, but others were left with few options and resorted to spending hundreds of dollars on data recovery assistance.
When I started grad school, I had no idea at the time just how much I’d learn doing a PhD. I’m not just talking about the “big picture” stuff: how to do research, design and conduct experiments, analyze data, and synthesize information. I mean all of the day-to-day skills associated with academic writing, data entry, and organization.
Wow, my other posts on the topic are getting a lot of hits!
Some exciting info for anyone still struggling with getting abbreviated journal names working with Mendeley: this feature is coming soon!
I just transferred my hosting away from GoDaddy (good riddance!) and am now self-hosting this site on a Raspberry Pi.
There may be some DNS and 404 hiccups for the next 48 hours or so while all the new settings “take”. Please update your bookmarks accordingly, and thank you for you patience.