About the post Just like in the previous entry, we will be using R to access our school’s Google Analytics data through their API. In this post, I want to highlight how we can figure out when a vistor to our website completes our a goal on our site. In my case, I am interested in learning more about how, and when, prospective students (and/or parents) complete our information request form.
I recently asked a question on Stack Overflow on the best way to set environment variables on a Mac for use within an RStudio session.
It wasn’t as straightforward as I would have thought, so I wanted to share this quick post as a way to remind my future self of a quick way to solve the issue.
Overview Generally, you can set environment variables by:
export YOUR_VAR=abc123 within a terminal.
rmongodb Tutorial This is a quick document aimed at highlighting the basics of what you might want to do using MongoDB and R. I am coming at this, almost completely, from a SQL mindset.
Install The easiest way to install, I believe, is
library(devtools) install_github(repo = "mongosoup/rmongodb") Connect Below we will load the package and connect to Mongo. The console will print TRUE if we are good to go.
Why this post Basically, my analytical toolbox consists of a few basic things:
Programming Languages (R and python) Storage (MySQL and MongoDB) Visualization and Reporting (Tableau Desktop) If I even remotely resembled a Data Scientist, other tools listed above would include the all things command line, Hadoop, d3, and some familiarity with AWS. With that said, you can do some really cool research with the tools listed above.
I long have wanted to post about the things I am doing with R and Google Analytics for my division, so I was very excited to see that tonight’s #emchat is on web analytics. This post will be more on the technical end, but I wanted to highlight what’s possible beyond the basic point-and-click interface in Google Analytics.
Why do this post? Google, as well as other vendors, provide APIs to our web data.