Archives of Data science

Leadership discussion session at PyDataLondon 2024

At this year’s PyDataLondon 2024 conference I ran my regular Leadership discussion for team leaders & department heads. It is an open session for 40-60 senior people, under Chatham House rules, to discuss issues and seek feedback. We had a lot of happy people in the room for this session (photo below – taken with […]
5 months ago

Skinny Pandas Riding on a Rocket at PyDataGlobal 2020

On November 11th we saw the most ambitious ever PyData conference – PyData Global 2020 was a combination of world-wide PyData groups putting on a huge event to both build our international community and to leverage the on-line only conferences that we need to run during Covid 19. The conference brought together almost 2,000 attendees […]
4 years ago

Weekish notes

I’ve recently switched back from Sourdough yeast to dried packet yeast mix, given a recipe by a colleague (thanks Nick!). I immediately set to work modifying his recipe (well, cutting out steps if we’re honest). The first loaf looked fine but was bland – I cut out too much salt. The next was really very […]
4 years ago

Weekish notes

I gave another iteration of my Making Pandas Fly talk sequence for PyDataAmsterdam recently and received some lovely postcards from attendees as a result. I’ve also had time to list new iterations of my training courses for Higher Performance Python (October) and Software Engineering for Data Scientists (September), both will run virtually via Zoom & […]
4 years ago

“Making Pandas Fly” for PyDataAmsterdam 2020

I thank the PyDataAmsterdam 2020 organisers for another chance to speak on Making Pandas Fly (PyDataAmsterdam 2020). This variant of the talk focuses more on: Understanding when categories beat strings and smaller floats beat larger ones What’s happening with NumPy behind the scenes How we can save 50% of our RAM (and so fit in […]
4 years ago

Weeknote (dtype-diet)

Over the weekend I hacked on dtype_diet – a tool for Pandas users that checks their DataFrame to see if smaller datatypes might be applicable. If so they’d offer no data loss and a reduction in RAM, for Categorical data there’s also the possibility of faster calculations. This tool makes no changes, it recommends the […]
4 years ago

Week(ish) note

So – High Performance Python 2nd ed finally shipped (Amazon, Goodreads) – yay! In brief we’ve added notes on how you can be a “highly performant programmer”, added some more profiling, added Pandas onto NumPy, improved the Compiling to C chapter with more Numba and a new full section on GPUs (in the first edition […]
5 years ago

Notes on last week’s Higher Performance Python class

Last week I ran a two-morning Higher Performance Python class, we covered: Profiling slow code (using a 2D particle infection model in an interactive Jupyter Notebook) with line_profiler & PySpy Vectorising code with NumPy vs running the original with PyPy Moving to Numba to make iterative and vectorised NumPy really fast (with up to a […]
5 years ago

Notes from Zoom call on “Problems & Solutions for Data Science Remote Work”

On Friday I held an open Zoom call to discuss the problems and solutions posed by remote work for data scientists. I put this together as I’ve observed from my teaching cohorts and from conversation with colleagues that for anyone “suddenly working remotely” the process has typically not been smooth. I invited folk to join […]
5 years ago