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.
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.
Clean up days in my apartment building netted me two computers that are perfect for running some basic experiments. The nicer of the two - a Dell Latitude C640- has a 2.40 GHz processor, 1 Gb of RAM and a 60 GB hard drive. It’s basically an over-sized Raspbery Pi. Despite the relatively low power the machine is perfect for learning how to set up an R Studio Server.
Welcome to Let’s Ask The Data. I have launched my first website/blog in an endeavour to share my experience and learning with others doing similar work in the Data Science and/or Applied Statistic community. I’m plan to use it as a place to document my adventures exploring and practising new methods or showcase projects with cool data sets. In doing so, I hope that others doing similar work can learn from my blog.