RentLingo's Charm Index

Uses Big Data to visualize best/worst parts of town

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Here at @TeleportInc we're fascinated with how software can help people figure out their best place to live. Love when more people are thinking about this, so was excited to see @DanLaufer from RentLingo to take a different stab at visualizing the quality of rental spaces. Their Charm Index has a tilt towards availability and quality of shopping -- but includes other data about expected lifestyle as well. Check it out.
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This is a great concept. I need to move to a new apartment on this July and would definitely try this out. As I'm building this service to help people understand their indoor environment better, especially from the air quality stands point at @getawair, I think there might be a possibility that we can integrate together down the road. Apparently, people do want to make an informed decision in finding place to live, and air quality in an apartment can be a really important data. Any comment or thoughts on this??
Thanks @sanbaek! That's a cool idea. We're always looking to deepen location insights for users. I think incorporating air quality data could be super interesting. Ping me at dan [at] rentlingo to chat offline! cc: @getawair
Thanks Sten for hunting us! I'd love any feedback from the PH community and happy to answer any questions as well!
@danlaufer I've thought about doing something similar, except for just finding out where the top ~ 10% most dangerous parts of cities were. I personally love just wandering/biking around exploring, but knowing these no-go zones from first glance would be cool.
@nwkwan makes sense. I've seen things like that out there. We factor in crime (you can see the bright red in the tenderloin if you're looking at SF for example) but felt for our use case something more comprehensive made sense. There are lots of crime databases out there if you're looking to build that though!
Awesome, that's exactly what I was looking for!
@farano btw, as a comparison, do please check too :)