I'm a little disappointed, insofar as this data tells us nothing we don't already know-the area around Fremont BART is more affluent than Fruitvale, OMG! But it

I'm a little disappointed, insofar as this data tells us nothing we don't already know-the area around Fremont BART is more affluent than Fruitvale, OMG! But it is a nice bit of data visualization, and I applaud them for that. I live in the Bay Area, develop software, and rely on public transit everyday. I definitely see improvements in what data should be presented. For example, for Caltrain, break each graph down further. Find the number of passengers who board at Baby Bullets, NB and SB, for the weekday commutes. What you need is more demographic data about the riders of each system, at specific times. Anyone whose been on Caltrain can tell you that the weekday commute is very much a white collar commute. Finance, Law and Tech going north to SF, mostly tech going south to MV (by the time baby bullets get to SJ Diridon, they are very empty). Palo Alto is an outlier, a lot of people commute from points south to Stanford, which obviously isn't a tech company. Having said that, since I really enjoy developing transit software, I'm really going to take a look at the code and see what I can do. Its a really good start, and I'm happy they posted it to HN.