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Image Source: Wikipedia License CC-BY-SA 3.0 If you, like me, frequently commute via public transit, you may be familiar with the following situation: You arrive at the bus stop, ready to catch your bus: a line that advertises arrivals every 10 minutes. You glance at your watch and note the time...
Python is quick and easy to code, but can be slow when doing intensive numerical operations. Translating code to Cython can be helpful, but in most cases requires a bit of trial and error to achieve the optimal result.
This week, Twitter upped their single-tweet character limit from 140 to 280, purportedly based on this interesting analysis of tweet lengths published on Twitter's engineering blog.
I've found one of the best ways to grow in my scientific coding is to spend time comparing the efficiency of various approaches to implementing particular algorithms that I find useful, in order to build an intuition of the performance of the building blocks of the scientific Python ecosystem.
Jupyter notebooks provide a useful environment for interactive exploration of data. A common question I get, though, is how you can progress from this nonlinear, interactive, trial-and-error style of exploration to a more linear and reproducible analysis based on organized, packaged, and tested…
This week Pronto CycleShare, Seattle's Bicycle Share system, turned one year old. To celebrate this, Pronto made available a large cache of data from the first year of operation and announced the Pronto Cycle Share's Data Challenge, which offers prizes for different categories of analysis.
In recent months, a host of new tools and packages have been announced for working with data at scale in Python. For an excellent and entertaining summary of these, I'd suggest watching Rob Story's Python Data Bikeshed talk from the 2015 PyData Seattle conference.
Last year I wrote a blog post examining trends in Seattle bicycling and how they relate to weather, daylight, day of the week, and other factors. Here I want to revisit the same data from a different perspective: rather than making assumptions in order to build models that might describe the data,…
Cycling in Seattle seems to be taking off. This can be seen qualitatively in the increased visibility of advocacy groups like Seattle Neighborhood Greenways and Cascade Bicycle Club, the excellent reporting of sites like the Seattle Bike Blog, and the investment by the city in high-profile traffic…
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