One piece of advice I give for those wanting to get into data visualization is to trash the defaults (see the last part of this interview with me). Jon Schwabish, an economist with the government, gives a detailed example of...
Update on July 15, 2013: Thanks to Harlan Nelson for noting on AnalyticBridge that the ozone concentrations for both New York and Ozonopolis are non-negative quantities, so their kernel density plot should have non-negative support sets. This has been corrected in this post by - defining new variables called max.ozone and max.ozone2 - using the […]
Introduction Continuing my recent series on exploratory data analysis (EDA), and following up on the last post on the conceptual foundations of empirical cumulative distribution functions (CDFs), this post shows how to plot them in R. (Previous posts in this series on EDA include descriptive statistics, box plots, kernel density estimation, and violin plots.) I […]
For the sake of brevity, this post has been created from the first half of a previous long post on kernel density estimation. This first half focuses on the conceptual foundations of kernel density estimation. The second half will focus on constructing kernel density plots and rug plots in R. Introduction Recently, I began a […]