PyGrunn, a one day Python conference in Groningen (aka Grunn), The Netherlands was held this year on Friday May 9th. It's a small but fun and interesting conference that's seems to be growing year over year. It has an excellent mix of well seasoned speakers, that have made their name within the Python community, and less experienced speakers that are all keen to show how Python's versatility is put to good use in their day to day jobs
This year they were looking for talks related to Python in science and education and Python and big data. My day-to-day work involves none of these topics of interest. However a Python library that I have been using regularly, Pandas, is used extensively within science. Hence I figured I'd submit a talk I had previously given at a Python Users Netherlands (PUN) meetup.
I was happy to see the talk accepted. Even though PyGrunn is a relatively small conference it would provide the largest audience to have presented for (I was one of the less experienced speakers). The idea was to rewrite that presentation to use different examples with even a little geoprocessing in it. Though as I was in de middle of wrapping up a contracting gig I unfortunately ran out of time. I do not think that hurt the presentation at all. Those that had seen my presentation previously would have chosen a different parallel talk anyway; new examples or not. I did convert the presentation from the IPython Notebook viewer reveal.js based one to Apple Keynote due to my bad experiences with the former
Here it is:
Pandas is an increasingly popular and fast Python library for analyzing large amounts of data. It has made Python a practical choice for performing data analysis. This talk will introduce Pandas and show real world examples slicing and dicing raw data into meaningful information.