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HW11-Anqi Li #14

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Looks pretty ambitious. If you do find yourself stuck and need to make compromises, aim for more preprocessing of data or only supporting a subset of the entire NY subway system for demo purposes

9.Zip Code-Level Home Value Index and Rental Index -CSV available from Zillow

Probable data gathering and processing procedure:
1)scrape Dataset 4 from MTA and merge it with Dataset 2

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Are you comfortable with this step? I don't want to discourage it, but I also want to make sure you don't take on too much


Probable data gathering and processing procedure:
1)scrape Dataset 4 from MTA and merge it with Dataset 2
2)turn Datasets 5,6,8 & 9 into GeoJSON format

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Likely can cram them all into the same vectors since they seem to have the same units of aggregation

@@ -55,6 +98,13 @@ are hard to use and think about. Global variables are a strategy for
coping with that difficulty by breaking data out of the asynchronous
context.

Probable difficulties:
1.joininig datasets spatially

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Turf can probably do this if you're just looking to label points with values from vectors they're inside of: http://turfjs.org/docs/#tag

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