Awesome!! Trying to learn more about the GIS world myself

Thanks!

Glad it was helpful!

That’s a great observation. We may have uncovered a finding which is actually a cause.

very true, maybe we can get some more insights into why the stores are exactly where they are. which can then help us predict where the next stores will be for example.

@@ritvikmath exactly! You could start building a regression using various land features and socioeconomics as explanatory variables. My gut tells me there are likely some predictive features you’d stumble on. Then run the same analysis in a place like Seattle and see if your LA-based regression model holds up.

Great to hear!

Seems to me, in the video it's calculating Euclidean Distance

Definitely! this straight line distance is (usually) not close the walkable distance or drivable distance except when those line segments connect two locations down the same street.

Of course!

Wow that’s a great question! My initial thought is to scan over all the areas of Los Angeles county, and find the one whose closest Starbucks is farthest away. Going a step further we would want to take into account population density data to make sure we don’t end up building a store in the mountains somewhere.

Thank you very much!

yes it should be! will just require some extra API calls to get the driving distance.

Thank you! Cheers!