Posted on Fri 04 November 2016 in TDDA • Tagged with tdda, constraints, pandas
We recently extended the tdda library to include support for automatic discovery of constraints from datasets, and for verification of datasets against constraints. Yesterday's post—Constraint Discovery and Verification for Pandas DataFrames—describes these developments and the API.
The library we published is intended to be a base for …
Continue readingPosted on Thu 03 November 2016 in TDDA • Tagged with tdda, constraints, pandas
In a previous post, Constraints and Assertions, we introduced the idea of using constraints to verify input, output and intermediate datasets for an analytical process. We also demonstrated that candidate constraints can be automatically generated from example datasets. We prototyped this in our own software (Miró) expressing constraints as …
Continue readingIn my PyCon UK talk yesterday I promised to update the and document
the copy of writabletestcase.WritableTestCase on GitHub.
The version I've put up is not quite as powerful as the example I showed in the talk—that will follow—but has the basic functionality.
I've now added examples …
Continue readingPython UK 2016, Cardiff.
I gave a talk on test-driven data analysis at PyCon UK 2016, Cardiff, today.
The slides (which are kind-of useless without the words) are available here.
More usefully, a rough transcript, with thumbnail slides, is available here.
Continue readingPosted on Mon 15 February 2016 in TDDA • Tagged with tdda, bad data
My first paid programming job was working for my local education authority during the summer. The Advisory Unit for Computer-Based Education (AUCBE), run by a fantastic visionary and literal "greybeard" called Bill Tagg, produced software for schools in Hertfordshire and environs, and one of their products was a simple database …
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