Do you have an Uber Problem ? I do. I’d catch an Uber to the toilet if I could. Some quick details so far, below:
- Uber recently released their travel datasets. Two things:
- Here are my initial findings for my 3 favourite cities: my home town of Brisbane, my second hometown and largest city in AU for comparison, Sydney, and London – which I also love and have lived and worked in.
- Details to follow – these are just my initial findings.
I grew up in Brisbane since aged 6 until I went to-and-froing from my mid-twenties onwards. Back in the earlier day around the mid-eighties when my appreciation for the size, services, and rates of development of a city’s maturity was in-tune. The phrase “Oh Brisbane it’s just a jumped-up country town”. Partially this was true because I still remember the little things for example walking the city streets after 5pm, trying to get home after footy training… place was a ghost town. And similarly out in the suburbs – everyone indoors by the time the street lights were on and if you want your Beef & Black Bean and Lemon Chicken from the (if you’re lucky”) local Chinese Takeaway, best fire up the Valiant and get that order across the counter pronto.
So what does the Uber data tells about the city and it’s denizens today ? Uber release the data in fairly aggregated form and sanitized for personally identifiable information. So anyway, I thought I’d choose a recent, busy period to give us an upper bounds – November 2018 to January 2019:
<More to follow>
Same time-frame, much bigger and older city than Brisvegas (as it’s lovingly become know by):
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Lived and worked here and had a ball. Check out the graph though – strikingly radial. I guess these are the townships the tube forget ? Or where people cash-in together to the avoid the possible hassles of same ? Very eerie to see such regularity amongst such a large, mobile population. Again Tableau analysis to follow but here’s the first look:
<More to follow>