Kevin Feasel


Graph, R

Thomas Lin Pedersen announces tidygraph, a tidyverse library for dealing with graphs and trees in R:

One of the simplest concepts when computing graph based values is that of
centrality, i.e. how central is a node or edge in the graph. As this
definition is inherently vague, a lot of different centrality scores exists that
all treat the concept of central a bit different. One of the famous ones is
the pagerank algorithm that was powering Google Search in the beginning.
tidygraph currently has 11 different centrality measures and all of these are
prefixed with centrality_* for easy discoverability. All of them returns a
numeric vector matching the nodes (or edges in the case of

This is a big project and is definitely interesting if you’re looking at analyzing graph data.

Related Posts

The Lesser-Known Apply Functions In R

Andrew Treadway covers a few of the lesser-known apply functions in R: rapply Let’s start with rapply. This function has a couple of different purposes. One is to recursively apply a function to a list. We’ll get to that in a moment. The other use of rapply is to a apply a function to only those elements in […]

Read More

Controlling Azure Services In R With AzureR

Hong Ooi announces a new set of packages called AzureR: As background, some of you may remember the AzureSMR package, which was written a few years back as an R interface to Azure. AzureSMR was very successful and gained a significant number of users, but it was never meant to be maintainable in the long term. As […]

Read More


July 2017
« Jun Aug »