I had the privilege of having Peter Wang himself demonstrate datashader for me and answer a few of my questions.
I am so excited about datashader capabilities I literally will not wait for the functionality to be exposed in R through rbokeh. I am going to leave my usual knitr/rmarkdown world and dust off Jupyter Notebook just to use datashader plotting. This is worth trying, even for diehard R users. Continue reading Datashader is a big deal
sigr is a simple R package that conveniently formats a few statistics and their significance tests. This allows the analyst to use the correct test no matter what modeling package or procedure they use.
replyr is an R package that contains extensions, adaptions, and work-arounds to make remote Rdplyr data sources (including big data systems such as Spark) behave more like local data. This allows the analyst to more easily develop and debug procedures that simultaneously work on a variety of data services (in-memory data.frame, SQLite, PostgreSQL, and Spark2 currently being the primary supported platforms).
I am going to write about an insidious statistical, data analysis, and presentation fallacy I call “the zero bug” and the habits you need to cultivate to avoid it.
The zero bug
Here is the zero bug in a nutshell: common data aggregation tools often can not “count to zero” from examples, and this causes problems. Please read on for what this means, the consequences, and how to avoid the problem. Continue reading The Zero Bug