A few tips to be a good UNIX neighbour and make your scripts more portable.

In this article, we benchmark various methods to write data to MS SQL Server from pandas DataFrames to see which is the fastest. We compare multi, fast_executemany and turbodbc, and find the best candidate.

In this article, we take a deeper dive into the benchmark exercise times and weights for the 2019 CrossFit Open athletes, including sprinting, running, squat, deadlift, clean & jerk, and snatch.

In this final article on 2019 CrossFit Open athlete statistics, we take a look at the spread of times for CrossFit's iconic workouts from athlete profile pages: Fran, Grace, Helen, Filthy Fifty, and Fight Gone Bad.

In this article, we disect the various physical, strength and athletic attributes of hundreds of thousands of 2019 CrossFit Open athletes as self-reported in their athlete profiles.

I encounter an unhashable type error when trying to get the unique number of geometries in a GeoDataFrame, and we learn about mutability (vs immutability) of Python objects in order to sidestep the issue.

In our final installment for the Higher Level Function in Python Series, we dive into the Python filter function. No sidetracks this time around. We simply take a look at how it's used, try to find a way where it would be superior to list comprehensions, fail, and conclude the series.

We go through uses of the Python reduce function, when it's useful and its performance benefits. This time, we spend some time exploring function composition, and how to manage large function chains, e.g. in a data processing pipeline.

We go through uses of the Python map function, when it's useful and its performance benefits, and get sidetracked into benchmarking different syntaxes for exponential expressions.

A general primer on Python for science and engineering, with an emphasis on the SciPy ecosystem of packages.