Putting words on paper to express an idea or make an argument has become a real struggle for me. In fact, writing has become a little paralyzing for me. At work we operate in a document culture and the blinking cursor seems to mock me each time I open up a file. I have dozens of ideas for blog posts floating around in my notebooks, but the effort of turning them into prose is daunting.
After switching to Ubuntu as my operating system I needed to re-install all of the R packages I needed to work on my website. These included both the packages needed by blogdown and packages I used in specific articles. I didn’t know what I was missing until I ran into an error. Installing the missing software packages was time consuming and tedious. Not only was the process frustrating, recreating my development environment piece by piece did not follow best practices for reproducibility.
Trapped at home, I’ve been slowly making my way through chores I’ve been putting off. One of the things I put off is performing a clean install of my operating system on my aging MacBook Pro. At nearly 10 years old, it is starting to show its age. In an effort to breath new life into the machine, I decided to switch to a Linux operating system. I’ve been thinking about switching operating systems for a little while so, I spent a time using Ubuntu, Mint and Fedora in VMs before committing to the change.
I’m excited to announce that my first R package, noaaoceans, is now available on CRAN. The current version focuses on accessing data from the CO-OPS API. The package also facilitates the collection of basic metadata for each of the stations that collect the data available in the API. Installation The package can be installed from CRAN or GitHub.
Install from CRAN install.packages('noaaoceans') # Install from GitHub remotes::install_github('warlicks/noaaoceans') Introduction There are two functions included in the package and they are often used together to provide the information of interest.
I have a confession to make. When I first started using R, I hated RStudio. I want to emphasize the past tense of the previous sentence, given that it is a rather adversarial statement. However, over the past year I have really come to appreciate the power of RStudio and have since rebuilt my workflow around it. The restructuring of my work flow around RStudio has been driven by three things.