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Data Algebra 0.9.0 Release

I am pleased to announce the 0.9.0 release of the data algebra. The data algebra is realization of the Codd relational algebra for data in written in terms of Python method chaining. It allows the concise clear specification of useful data transforms. Some examples can be found here. Benefits include […]

A Richer Category for Data Wrangling

I’ve been writing a lot about a category theory interpretations of data-processing pipelines and some of the improvements we feel it is driving in both the data_algebra and in rquery/rqdatatable. I think I’ve found an even better category theory re-formulation of the package, which I will describe here.

Advanced Data Reshaping in Python and R

This note is a simple data wrangling example worked using both the Python data_algebra package and the R cdata package. Both of these packages make data wrangling easy through he use of coordinatized data concepts (relying heavily on Codd’s “rule of access”). The advantages of data_algebra and cdata are: The […]

rquery: SQL from R

My BARUG rquery talk went very well, thank you very much to the attendees for being an attentive and generous audience. (John teaching rquery at BARUG, photo credit: Timothy Liu) I am now looking for invitations to give a streamlined version of this talk privately to groups using R who […]

Visualizing relational joins

I want to discuss a nice series of figures used to teach relational join semantics in R for Data Science by Garrett Grolemund and Hadley Wickham, O’Reilly 2016. Below is an example from their book illustrating an inner join: Please read on for my discussion of this diagram and teaching […]