I saw Simon Jackson’s recent blog post regarding ordering categories within facets. He proposed a way of dealing with the problem of ordering variables shared across facets within facets. This problem becomes apparent in text analysis where words are shared … Continue reading →
Visual storytelling Visualising data helps understanding facts. Sometimes it’s very easy to understand a graph; sometimes it’s necessary to read it and to study it to discover unknown territory. Such graphs are little masterpieces. Here’s one of these and I am sure the authors had more than one iteration and discussion while creating it. The … Continue reading Reading a Picture
Several years back I wrote a two part blog series in response to seeing questions about plotting and reordering on list serves, talkstats.com, and stackoverflow. Part I discussed the basics of reordering plots by reordering factor levels. The essential gist was: … Continue reading →
A while back I showed you how to make volcano plots in base R for visualizing gene expression results. This is just one of many genome-scale plots where you might want to show all individual results but highlight or call out important results by labeli...
We saw this scatterplot with marginal densities the other day, in a blog post by Thomas Wiecki: The graph was produced in Python, using the seaborn package. Seaborn calls it a “jointplot;” it’s called a “scatterhist” in Ma...
Visual representations of statistical data are attractive – and worth to build an own website with nothing but (info)graphs and …Continue reading →
Comparing statistical visualizations over a period of 100 years is quite rare. The newly published Atlas of the Swiss Federal …Continue reading →
I forgot where I originally found the code to do this, but I recently had to dig it out again to remind myself how to draw two different y axes on the same plot to show the values of two different features of the data. This is somewhat distinct from th...
At our most recent R user group meeting we were delighted to have presentations from Mark Lawson and Steve Hoang, both bioinformaticians at Hemoshear. All of the code used in both demos is in our Meetup’s GitHub repo.Making heatmaps in RSteve started...
The default plot method for dataframes in R is to show each numeric variable in a pair-wise scatter plot. I find this to be a really useful first look at a dataset, both to see correlations and joint distributions between variables, but also to quickly diagnose potential strangeness like bands of repeating values or outliers. […]
