Sunday, July 5, 2015
Quick example: A heat map of pedestrian counts
It might not look like it, but I have been super-busy lately working on data science and machine learning tech. I've been going on a bit of a vision quest trying to wrap my head around the whole thing. You know what -- I'm pretty lost. I've learned a lot of things, but I can also see how much deeper the rabbit-hole goes.
While that will bear fruit in time, I've decided to add a series of 'shorts' to the blog. Things which I can genuinely do more easily, and never mind if that risks being too simple to be of wider interest. The point here isn't to blaze a trail, but rather to keep up my exercise.
The plot above was generated by this code (link goes to a notebook).
The City of Melbourne provides quite fine-grained pedestrian count information for major locations in my home town -- see http://www.pedestrian.melbourne.vic.gov.au/. I really applaud this effort. I'm very excited about anything which reflects the physical world into the digital. This data updates in near-real-time as well, which is just wonderful.
Down the road I hope to use this to do some interesting prediction software, but for now I just want to explore the data. I'm also learning how to plot things.