Is there a service/API that will take a postal/zip code and return the bounding(perimeter) coordinates so I can build a Geometry object in a MS SQL database?
By bounding coordinates, I mean I would like to retrieve a list of GPS coordinates that construct a polygon that defines the US zip code.
An elaboration of my comment, that ZIP codes are not polygons....
We often think of ZIP codes as areas (polygons) because we say, "Oh, I live in this ZIP code..." which gives the impression of a containing region, and maybe the fact that ZIP stands for "Zone Improvement Plan" helps the false association with polygons.
In actuality, ZIP codes are lines which represent, in a sense, mail carrier routes. Geometrically, lines do not have area. Just as lines are strings of points along a coordinate plane, ZIP code lines are strings of delivery points in the abstract space of USPS-designated addresses.
They are not correlated to geographical coordinates. What you will find, though, is that they appear to be geographically oriented because it would be inefficient for carriers to have a route completely irrelevant of distance and location.
What is this "abstract space of USPS-designated addresses"? That's how I am describing the large and mysterious database of deliverable locations maintained by the US Postal Service. Addresses are not allotted based on geography, but on the routes that carriers travel which usually relates to streets and travelability.
Some 5-digit ZIP codes are only a single building, or a complex of buildings, or even a single floor of a building (yes, multiple zip codes can be at a single coordinate because their delivery points are layered vertically). Some of these -- among others -- are "unique" ZIPs. Companies and universities frequently get their own ZIP codes for marketing or organizational purposes. For instance, the ZIP code "12345" belongs to General Electric up in Schenectady, NY. (Edit: In a previous version of Google Maps, when you follow that link, you'd notice that the placement marker was hovering, because it points to a ZIP code, which is not a coordinate. While most US ZIP codes used to show a region on Google Maps, these types cannot because the USPS does not "own" them, so to speak, and they have no area.)
Just for fun, let's try verifying an address in a unique ZIP code. Head over to SmartyStreets and punch in a bogus address in 12345, like:
Street: 999 Sdf sdf
ZIP Code: 12345
When you try to verify that, notice that... it's VALID! Why? The USPS will deliver a piece to the receptacle for that unique ZIP code, but at that point, it's up to GE to distribute it. Pretty much anything internal to the ZIP code is irrelevant to the USPS, including the street address (technically "delivery line 1"). Many universities function in a similar manner. Here's more information regarding that.
Now, try the same bogus address, but without a ZIP code, and instead do the city/state:
Street: 999 Sdf sdf
City: Schenectady
State: NY
It doesn't validate. This is because even though Schenectady contains 12345, where the address is "valid," it geometrically intersects with the "real" ZIP codes for Schenectady.
Take another instance: military. Certain naval ships have their own ZIP codes. Military addresses are an entirely different class of addresses using the same namespace. Ships move. Geographical coordinates don't.
ZIP precision is another fun one. 5-digit ZIP codes are the least "precise" (though the term "specific" might be more meaningful here, since ZIP codes don't pinpoint anything). 7- and 9-digit ZIP codes are the most specific, often down to block or neighborhood-level in urban areas. But since each ZIP code is a different size, it's really hard to tell what actual distances you're talking.
A 9-digit ZIP code might be portioned to a floor of a building, so there you have overlapping ZIP codes for potentially hundreds of addresses.
Bottom line: ZIP codes don't, contrary to popular belief, provide geographical or boundary data. They vary widely and are actually quite un-helpful unless you're delivering mail or packages... but the USPS' job was to design efficient carrier routes, not partition the population into coordinate regions so much.
That's more the job of the census bureau. They've compiled a list of cartographic boundaries since ZIP codes are "convenient" to work with. To do this, they sectioned bunches of addresses into census blocks. Then, they aggregated USPS ZIP code data to find the relation between their census blocks (which has some rough coordinate data) and the ZIP codes. Thus, we have approximations of what it would look like to plot a line as a polygon. (Apparently, they converted a 1D line into a 2D polygon by transforming a 2D polygon based on its contents to fit linear data -- for each non-unique, regular ZIP code.)
From their website (link above):
A ZIP Code tabulation area (ZCTA) is a statistical geographic entity
that approximates the delivery area for a U.S. Postal Service
five-digit or three-digit ZIP Code. ZCTAs are aggregations of census
blocks that have the same predominant ZIP Code associated with the
addresses in the U.S. Census Bureau's Master Address File (MAF).
Three-digit ZCTA codes are applied to large contiguous areas for which
the U.S. Census Bureau does not have five-digit ZIP Code information
in its MAF. ZCTAs do not precisely depict ZIP Code delivery areas, and
do not include all ZIP Codes used for mail delivery. The U.S. Census
Bureau has established ZCTAs as a new geographic entity similar to,
but replacing, data tabulations for ZIP Codes undertaken in
conjunction with the 1990 and earlier censuses.
The USCB's dataset is incomplete, and at times inaccurate. Google still has holes in their data, too (the 12345 is a somewhat good example) -- but Google will patch it eventually by going over each address and ZIP code by hand. They do this already, but haven't made all their map data perfect quite yet. Naturally, access to this data is limited to API terms, and it's very expensive to raise these.
Phew. I'm beat. I hope that helps clarify things. Disclaimer: I used to be a developer at SmartyStreets. More information on geocoding with address data.
Even more information about ZIP codes.
What you are asking for is a service to provide "Free Zip code Geocoding". There are a few out there with varying quality. You're going to have a bad time coding something like this yourself because of a few reasons:
Zip codes can be assigned to a single building or to a post office.
Zip codes are NOT considered a polygonal area. Projecting Zip codes to a polygonal area will require you to make an educated guess where the boundary is between one zipcode and the next.
ZIP code address data specifies only a center location for the ZIP code. Zip code data provides the general vicinity of an address. Mailing addresses that exist between one zipcode and another can be in dispute on which zipcode it actually is in.
A mailing address may be physically closer to zipcode 11111, yet its official zip code is a more distant zip code point 11112.
Google Maps has a geocoding API:
The google maps API is client-side javascript. You can directly query the geocoding system from php using an http request. However, google maps only gives you what the United States Postal Service gives them. A point representing the center of the zipcode.
https://developers.google.com/maps/#Geocoding_Examples
map city/zipcode polygons using google maps
Thoughts on projecting a zipcode to its lat/long bounding box
There are approximately 43,000 ZIP Codes in the United States. This number fluctuates from month to month, depending on the number of changes made. The zipcodes used by the USPS are not represented as polygons and do not have hard and fast boundaries.
The USPS (United States Postal Service) is the authority that defines each zipcode lat/long. Any software which resolves a zipcode to a geographical location would be in need of weekly updates. One company called alignstar provides demographics and GIS data of zipcodes ( http://www.alignstar.com/data.html ).
Given a physical (mailing) address, find the geographical coordinates in order to display that location on a map.
If you want to reliably project what shape the zipcode is in, you are going to need to brute force it and ask: "give me every street address by zipcode", then paint boxes around those mis-shapen blobs. Then you can get a general feel for what geographical areas the zipcodes cover.
http://vterrain.org/Culture/geocoding.html
If you were to throw millions of mailing address points into an algorithm resolving every one to a lat/long, you might be able to build a rudimentary blob bounding box of that zipcode. You would have to re-run this algorithm and it would theoretically heal itself whenever the zipcode numbers move.
Other ideas
http://shop.delorme.com/OA_HTML/DELibeCCtpSctDspRte.jsp?section=10075
http://www.zip-codes.com/zip-code-map-boundary-data.asp
step 1:download cb_2018_us_zcta510_500k.zip
https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html
if you want to keep them in mysql
step 2: in your mysql create a db of named :spatialdata
run this command
ogr2ogr -f "MySQL" MYSQL:"spatialdata,host=localhost,user=root" -nln "map" -a_srs "EPSG:4683" cb_2018_us_zcta510_500k.shp -overwrite -addfields -fieldTypeToString All -lco ENGINE=MyISAM
i uploaded the file on github(https://github.com/sahilkashyap64/USA-zipcode-boundary/blob/master/USAspatialdata.zip)
In the your "spatialdata db" there will be 2 table named map & geometry_columns .
In 'map' there will be a column named "shape".
shape column is of type "geometry" and it contains polygon/multipolygon files
In 'geometry_columns' there will will be srid defined
how to check if point falls in the polygon
SELECT * FROM map WHERE ST_Contains( map.SHAPE, ST_GeomFromText( 'POINT(63.39550 -148.89730 )', 4683 ) )
and want to show boundary on a map
select zcta5ce10 as zipcode, ST_AsGeoJSON(SHAPE) sh from map where ST_Contains( map.SHAPE, ST_GeomFromText( 'POINT(34.1116 -85.6092 )', 4683 ) )
"ST_AsGeoJSON" this returns spatial data as geojson.
Use http://geojson.tools/
"HERE maps" to check the shape of geojson
if you want to generate topojson
mapshaper converts shapefile to topojson (no need to convert it to kml file)
npx -p mapshaper mapshaper-xl cb_2018_us_zcta510_500k.shp snap -simplify 0.1% -filter-fields ZCTA5CE10 -rename-fields zip=ZCTA5CE10 -o format=topojson cb_2018_us_zcta510_500k.json
If you want to convert shapefile to kml
`ogr2ogr -f KML tl_2019_us_zcta510.kml -mapFieldType Integer64=Real tl_2019_us_zcta510.shp
I have used mapbox gl to display 2 zipcodes
example: https://sahilkashyap64.github.io/USA-zipcode-boundary/
code :https://github.com/sahilkashyap64/USA-zipcode-boundary
SQL Server Solution
Download the Shape files from the US Census:
https://catalog.data.gov/dataset/2019-cartographic-boundary-shapefile-2010-zip-code-tabulation-areas-for-united-states-1-500000
I then found this repository to import the shape file to SQL Server, it was very fast and required no additional coding: https://github.com/xfischer/Shape2SqlServer
Then I could write my own script to find out which zip codes are in a polygon I created:
DECLARE #polygon GEOMETRY;
DECLARE #isValid bit = 0;
DECLARE #p nvarchar(2048) = 'POLYGON((-120.1547 39.2472,-120.3758 39.1950,-120.2124 38.7734,-119.6590 38.8162,-119.6342 39.3672,-120.1836 39.2525,-120.1547 39.2472))'
SET #polygon = GEOMETRY::STPolyFromText(#p,4326)
SET #isValid = #polygon.STIsValid()
IF (#isValid = 1)
SET #polygon = #polygon.MakeValid();
SET #isValid = #polygon.STIsValid()
IF (#isValid = 1)
BEGIN
SELECT * FROM cb_2019_us_zcta510_500k
WHERE geom.STIntersects(#polygon) = 1
END
ELSE
SELECT 'Polygon not valid'
I think this is what you need it uses US Census as repository: US Zipcode
Boundaries API: https://www.boundaries-io.com
Above API shows US Boundaries(GeoJson) by zipcode,city, and state. you should use the API programatically to handle large results.
Disclaimer,I work here
I think the world geoJson link and the google map geocode api can help you.
example: you can use the geocode api to code the zip,you will get the city,state,country,then,you search from the world and us geoJson get the boundry,I have an example of US State boundry,like dsdlink
Related
One is able to group the number of page views by country, per this documentation. PFB KQL query.
pageViews | project client_CountryOrRegion, itemCount, client_City
However, visualizing by client_City doesn't work.
Is there a way one could group and visualize by the name of the city instead?
Workbooks itself doesn't currently have any built in mapping of city to lat/long, we only have that at the country/region level. (In the screenshots above, you told workbooks that a column of data has country information, but then you passed it cities, so it doesn't know of any countries named those things)
there are various ways to do it by using the externaldata operator in ADX/Log Analytics to have the database load, parse, and join with your other data. If you can get to lat/long, then you can tell workbooks to use that mode where you tell it which columns are lat and long and you'd have your points.
not the exact files you want, but in another example someone wanted to map from ip address to country, and in that example you'd add something like this to your query:
let geoData = externaldata
(network:string,geoname_id:string,continent_code:string,continent_name:string,
country_iso_code:string,country_name:string,is_anonymous_proxy:string,is_satellite_provider:string)
[#"https://raw.githubusercontent.com/datasets/geoip2-ipv4/master/data/geoip2-ipv4.csv"] with (ignoreFirstRecord=true, format="csv");
geoData
| limit 10
in your real query you'd not have the limit, you'd use the kql join operator to do an intersection and you'd get your lat/long that way.
I am using pyteaser to get information from a listing of websites. Since there could be hundreds of sites, I am trying to put it in a loop. When I run this code by itself:
summaries = SummarizeUrl(df['url'].values[1])
print (summaries)
It gives the following output, working fine:
[u'Bookings Institute researcher Paul C. Light published a study about failed government projects and their causes.', u'In 2011, U.K. government officials scraped a massive 9-year, $16 billion project to create a unified electronic health records system for British citizens.', u'Changing requirements, insufficient testing, and the monolithic nature of the project contributed to this failed government project for the failure.', u'Projected to cost $68 million, the projects costs skyrocketed to $700 million before being abandoned.', u'Here are a few examples of failed government projects, with estimated costs and causes:\n\nThe FBI system was designed to modernize tech systems and enable easier access across diverse FBI information assets.']
When I put it in a loop as follows:
i=0
for i in list(df):
summaries = SummarizeUrl(df['url'].values[i])
str1 = ''.join(summaries)#convert to string
print (str1)
I get the following error:
IndexError: only integers, slices (:), ellipsis (...), numpy.newaxis (None) and integer or boolean arrays are valid indices
I am trying to increment i based on the value in the dataframe. The dataframe looks like this:
dataframe
It works when I do it manually.
You're not incrementing i with this. In your code i is not an integer. It is an object consisting of one entry of what ever df is.
You could try to print your i like:
for i in list(df):
print(type(i))
print(i)
to see what it is. Then you should correct you access of the url, which could be i['url']
In DevPost Watson Developer Challenge for Conversational Applications post, I saw Watson (maybe) able to analyze following phrase "I want to visit Tokyo, Sydney, Manchester, and Reykjavik during a trip that takes 30 days".
Is there a better way to extract those array of locations without having to predefine max no of location variables (i.e. set location1 - 5) and manually specify various grammar items like $ (Locations)={location1} * (Locations)={location2} * (Locations)={location3} * (Locations)={location4} as per Pizza example dialog? I would like to follow up with comment such as "That's a lot" if location > 4, or "Sure" if less.
You could try something like alchemy or relationship extraction to identify all of the languages, and then simply add them to the user profile in Dialog. But today, the best way to do this within a broader conversation will be to do it the same way the pizza sample does as you outlined above.
I am looking for a solution to create a better OSMAND map for a region , as existing OSM maps are not complete.
If I get a map in Navteq/Garmin/Tom Tom format, will I be able to convert it to Osmand OBF format and replace in Osmand ?
There seems to be less references to this topic.
I would expect Navteq/Garmin/Tom Tom would give maps in shapefile format, and OSM can take data from shapefiles per http://wiki.openstreetmap.org/wiki/Shapefiles#Obtaining_OSM_data_from_shapefiles
HOWEVER... Navteq, Garmin, and Tom Tom are commercial organizations which value their data; I would be very surprised if their license would allow you to give it to OSM for free use. Furthermore, I expect that OSM would not allow you to give it to them. So I would be very surprised if this approach worked.
I'm trying to avoid reinventing the wheel when it comes to storing street addresses in a table only once. Uniqueness constraints won't work in some common situations:
100 W 5th Ave
100 West 5th Ave
100 W 5th
200 N 6th Ave Suite 405
200 N 6th Ave #405
I could implement some business logic or a trigger to normalize all fields before inserting and use uniqueness constraints across several fields in the table, but it would be easy to miss some cases with something that varies as much as street addresses.
What would be best would be a universal identifier for each address, perhaps based on GPS coordinates. Before storing a new address look up its GUID and see if the GUID already exists in the Address table.
An organization like Mapquest, the Postal Serice, FedEx, or the US government probably has a system like this.
Has anyone found a good solution to this?
Here's my Address table now (generated by JPA):
CREATE TABLE address
(
id bigint NOT NULL,
"number" character varying(255),
dir character varying(255),
street character varying(255),
"type" character varying(255),
trailingdir character varying(255),
unit character varying(255),
city character varying(255),
state character varying(255),
zip integer,
zip4 integer,
CONSTRAINT address_pkey PRIMARY KEY (id)
)
Look up the address in Google maps and use the spelling they use.
You need support for regular expressions like syntax. You can come up with some kind of automata function that will parse tokens and try matching them and then expand or contract them into abbreviations. I'd look into glob() like functions that give support to *? etc on unix as a quick dirty fix.
I wasn't looking for address validation or normalization, although address validation is a good idea. I need a unique identifier for each street address to avoid duplicate records.
It looks like geocoding can provide a solution. With geocoding the input can be a street address and the output will be latitude and longitude coordinates with enough precision to resolve a specific building.
There's a more serious problem with street address ambiguity than I thought. This is from the Wikipedia page on geocoding:
"...there are multiple 100 Washington Streets in Boston, Massachusetts because several cities have been annexed without changing street names."
The Wikipedia page on geocoding has a list of resources (many free) to perform geocoding.
I settled on the USC WebGIS service due to their nice web service interface and being easy to sign up for.
Geocodes aren't suitable as a unique key for street addresses, though, for a number of reasons. For example, geocoding cannot distinguish between different units in a condominium complex or apartment building.
I decided to use the parsed address from the geocoding result and put unique constraints on the street number, street name, unit, city, state, and zip. It's not perfect, but it works for what I'm doing.