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I have a dataset that contains zip codes. I want to figure out the name of the associated NYC neighborhood. For example, I have zip code 10021 and I want to know 10021 is located in Upper East Side.

Is there a way to do this mapping?

The dataset also has latitude and longitude values.

Is there a better way to determine the neighborhoods?

I also looked at this: https://en.wikipedia.org/wiki/List_of_Manhattan_neighborhoods Which looks like its done at the street level. (Above link is just for manhattan zip codes, but similar for other boroughs) I looked at this page that does some of the zip code mappings, but it doesn't include all the NYC zip codes.

I also looked at Seeking New York Neighborhoods Boundaries?, which uses shapefiles for the neighborhoods. I'm not familiar with shapefiles. I think I could map the points and then map the shape layer on top of it.

Is there way I can "join" this data. (Meaning if I were to use zip codes?

If one dataset had zip code and the other dataset had zip code I could join records on the zip code value. I don't know how I could do this with shapes.

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    Zip Codes are linear features -- the path(s) the USPS carrier(s) walks/drives to deliver mail. You're not likely to find 1:1 correspondence between neighborhood and Zip Code, even at a Zip+4 level -- many-to-many is far more likely. – Vince Mar 26 at 17:52

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