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Most ZIP codes in the US are fairly familiar - 5 digits, like 90210.

However I've come across some weird ZIP codes in Anchorage - like 995MX. (Visible on this map)

Many websites (like google maps) don't accept this as a valid ZIP. Even clicking on it on the map above claims it's a "filler"? Where did this come from? Why are there these unusual ZIP codes around there, and do they have a 'normal' ZIP code alias?

hippietrail
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Mark Mayo
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2 Answers2

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Zip codes were not allocated to these areas. When needed, MX will be substituted by numbers when the zip code is allocated for a portion of the "filler" area. See for example 99691 within the 996MX area.

Alaska is huge and very sparsely populated. No point in allocating zip codes for areas where no-one is going to send any mail.

Flimzy
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oh whatever
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Maponics who provide data for many mapping tools, would appear to be the source of this - for as they state in their documentation:

ZIP Codes

This product includes the names and boundaries (and other attributes as Maponics may choose to provide) for postal ZIP Codes in the United States. Maponics’ proprietary process builds these polygons using multiple data sources. The ZIP Code boundaries are based off of the carrier route boundaries, using a combine/dissolve/extend approach. Because there are cases where carrier routes do not exist, the ZIP Code boundaries have been extended using a proprietary process so that ZIP Codes cover the entire US. However, there are intentional holes in the ZIP Code layer for major water and landmark areas. In all cases where carrier routes exist, the ZIP Codes share the border line with carrier routes.

There are some areas where there is not sufficient data to create ZIP Code polygons. Where possible, Maponics has created temporary ZIP Code areas and given the area a ZIP Code starting with the three digit ZIP Code followed by either an “MH” or “MX” (ex. 901MH) to differentiate area encompassed by water (“MH” ) or land (“MX”). Other such areas appear as holes. Some unique ZIP Codes might appear as polygons (for example, a university).

Mark Mayo
  • 160,001
  • 106
  • 687
  • 1,492