Published on: 6th June 2022 Introduction to testing for data science Testing is one of the most important skills for any data scientist to learn. In my experience, adding tests to your code is the...
Parallel loop the loop in numpy
Slow data analysis code can be a real drag. There are numerous ways to accelerate bottleneck code in Numpy such as compiling expressions with NumExpr or Pythran. However, if you are calling a third...
Attaining flow while writing software
Attaining flow while writing software tl:dr I have broken my former cycles of anxiety, frustration and elation when writing software by adopting proven principles of software engineering. By adopt...
What software skills do oceanographers want to learn
tl:dr A small survey of oceanographers shows there is high demand for training to improve their software engineering skills. The range of topics is broad ranging from basic programming to advanced ...
Dev in docker without going insane
Dev in Docker without going insane Tl;dr Developing in docker is designed to make your life better but done the wrong way this workflow can seem very slow. I share here some crucial modifications ...
JPO at 50: Part II
Where do oceanographers study? The part of the ocean that oceanographers choose to study is determined not just by scientific interest but also by geo-political factors. In this section we see how...
JPO at 50: Part I
50 years of the Journal of Physical Oceanography: using NLP to understand how oceanography has evolved. The Journal of Physical Oceanography (JPO) has been a leading journal for physical oceanograp...
Dev in docker
Dev in Docker Tl;dr Developing in docker gives you a consistent runtime environment that’s great for sharing. Use multi-stage builds and virtual environments to rapdily build and re-build your doc...
Career progression
Career progression - lessons learned In the last two years I’ve changed from being a research scientist in physical oceanography to data scientist in industry with Analytics Engines. I discussed t...