A few weeks ago the wonderful RWeekly mailing list introduced me to a new type of plot - the point density plot. Wonderfully, the ability to make this plot has been added to the R community in the form of a new package, ggpointdensity. From the top line description, it’s a cross between a scatter plot and a 2D density plot. The motivation for creating the package and using this new plot is that the points in scatter plots can overlap one another while the alternative density plots lose the resolution given by plotting indiviudal points.
In my professional life, I manage and analyze data on a team that studies the social networks surounding children with autism. The purpose of this post is not to discuss that work in depth, but rather to show how to quickly and easily import one type of data I work with into R. For social network analysis, I use the package igraph. The type of data I’m going to talk about iporting today is egocentric network data.
In my last post I showed how using the package httr, You can access the RateBeer API to get information about beers made by a brewery. When I left off, I showed a problem - the API only shows 10 beers at a time. Today, I’m going to show how we can get more beers at once. After that, I’m going to show how we can use the API, rvest, and purrr to get beers from all the brewers around me.
A few months ago, I was talking with a friend of mine about the idea for this blog and how I wanted to use data science to explore beer. He suggested that I use the blog as well as beer to learn something new about where I live. So I ask, what can beer teach me about Philadelphia? The first thing I need? Data! Oddly enough, it’s actually pretty challenging to get access to high quality, current beer data.