Less visually striking than my last project, this visualization shows the voting patterns of Canadian Members of Parliament. It uses a Principal Component Analysis (or PCA) transformation to convert the multidimensional voting record of each MP to a 2D (or Cartesian) form.
Each point on the chart represents an MP. The color of every MP follows their party affiliation. They are tightly clustered because of party discipline : in Canada, MPs normally vote in accordance to directions given by the Prime Minister.
Continue reading “Legislative Explorer | Multidimensional Vote Explorer”
I was very impressed by the friendship map made by Facebook intern, Paul Butler and I realized that I had access to a similar dataset at Science-Metrix (an old employer I left a while ago). Instead of a database of friendship data, I had access to a database of scientific collaborations. Bibliometric firms use this kind of data to get a (very) approximated view of science, but I thought that for a data visualization, it was good enough
This post is now obsolete, please see the new one (click here!)
Continue reading “Map of scientific collaboration between researchers”