An Unspoken Job Perk of Data Science: Artistic Mistakes

Occasionally I end up making something that is unintentionally beautiful but that will never end up in a paper. I call these artistic mistakes and below are a collection of some of the prettier ones. Most of them come from my experiments with machine vision, particularly transformations of map images that produced wildly unexpected results.


Comparing Bivariate Plots Under Different Assumptions

I’m a strong proponent of graphical comparisons before diving into models, but which exploratory plot to use depends heavily on the underlying distributions of the data and which signals you’re looking for. Below I compare 4 kinds of bivariate plots for continuous variables (binning into 10 quantiles with boxplots, scatter-plot with a lowess fit, hexbins [...]

Cool Visualizations

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Cool Visualizations

Mapped: British, Spanish and Dutch Shipping 1750-1800I recently stumbled upon a fascinating dataset which contains digitised information from the log books of ships (mostly from Britain, France, Spain and The Netherlands) sailing between 1750 and 1850. The creation of this dataset was completed as part of the Climatological Database for the World’s Oceans 1750-1850 [...]

Mosaic Plots with Percentage Labels

Michael Friendly’s book “Visualizing Categorical Data” has many great examples of visually representing cross tabs. An R package that emerged from that book is the vcd package for making mosaic plots. Something I could not find an example of, however, was how to use the elaborate struct-plot framework to overlay percentages on each tile. What [...]