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  • Introduction
  • Libraries
  • Authentication
  • Geocoding
  • Reverse Geocoding
  • Fields
  • Address components
  • Accuracy score
  • Address formats
  • Errors
  • Warnings
  • Client-side access
  • Changelog
  • Contact & Support
  • Introduction

    Geocodio's RESTful API allows you to perform forward and reverse geocoding lookups. We support both batch requests as well as individual lookups.

    You can also optionally ask for data appends such as timezone, Congressional districts or similar things of that nature.

    The base API url is https://api.enterprise.geocod.io/v1.7/.

    All HTTP responses (including errors) are returned with JSON-formatted output.

    We may add additional properties to the output in the future, but existing properties will never be changed or removed without a new API version release.

    Libraries

    Official libraries

    These libraries are officially written and maintained by Geocodio. Have an issue? We will in most cases be able to help via online chat or email.

    GitHub pull requests and issues are also more than welcome!

    Platform Library
    PHP Geocodio/geocodio-library-php
    Node.js Geocodio/geocodio-library-node
    Ruby Geocodio/geocodio-gem

    Third-party libraries

    Thanks to the wonderful open-source community, we have language bindings for several additional languages and platforms.

    We will do our best to assist in online chat or email, but may not be able to help in all cases with these libraries.

    Some of the libraries are featured here with basic examples, but please make sure to check out the full documentation for the individual libraries (linked below).

    Platform Library Featured in documentation
    Ruby alexreisner/geocoder supports Geocodio thanks to PR by @dblockdotorg
    Ruby davidcelis/geocodio by @davidcelis
    Python bennylope/pygeocodio by @bennylope
    Clojure jboverfelt/rodeo by @jboverfelt
    Perl mrallen1/WebService-Geocodio by @bytemeorg
    Go stevepartridge/geocodio by stevepartridge
    R hrbrmstr/rgeocodio by hrbrmstr
    R jessecambon/tidygeocoder by jessecambon
    C# snake-plissken/cSharpGeocodio by Frank Deasey
    C# arex388/Arex388.Geocodio by arex388
    Rust Cosiamo/geocodio_lib_rust by Cosiamo
    Java deansg/jeocodio by Dean Gurvitz
    Are you the author of an awesome library that you would like to get featured here? Just let us know or create a pull request.

    Installing the library:

    # Make sure to have `curl` installed to test the API in your terminal
    
    # Add the following to your Gemfile:
    gem 'geocodio-gem'
    
    # And then run:
    bundle install
    
    pip install pygeocodio
    
    # Install via Composer
    composer require geocodio/geocodio-library-php
    
    <?php
    require('vendor/autoload.php');
    
    # Don't fancy Composer? Not a problem!
    # Check out our sample code here: https://github.com/Geocodio/php-samples
    
    # Install via npm
    $ npm install --save geocodio-library-node
    
    # Install via Yarn
    $ yarn add geocodio-library-node
    
    # Leiningen
    [rodeo "2.0.1"]
    
    # Maven
    <dependency>
      <groupId>rodeo</groupId>
      <artifactId>rodeo</artifactId>
      <version>2.0.1</version>
    </dependency>
    
    # Gradle
    compile "rodeo:rodeo:2.0.1"
    

    Authentication

    To set the API_KEY:

    # With curl, you can just pass the query parameter with each request
    curl "https://api.enterprise.geocod.io/v1.7/api_endpoint_here?api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    <?php
    $geocoder = new Geocodio\Geocodio();
    $geocoder->setApiKey('YOUR_API_KEY');
    $geocoder->setHostname('api.enterprise.geocod.io');
    
    const Geocodio = require('geocodio-library-node');
    const geocoder = new Geocodio('YOUR_API_KEY', 'api.enterprise.geocod.io');
    
    // You can also leave out the parameters and define the following environment variables instead:
    // GEOCODIO_API_KEY=YOUR_API_KEY
    // GEOCODIO_HOSTNAME=api.enterprise.geocod.io
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    ;; You can set the API key in the GEOCODIO_API_KEY environment variable
    ;; or with each request using the :api_key parameter
    

    All requests require an API key. You can register here to get your own API key.

    The API key must be included in all requests using the ?api_key=YOUR_API_KEY query parameter.

    Accounts can have multiple API keys. This can be useful if you're working on several projects and want to be able to revoke access using the API key for a single project in the future or if you want to keep track of usage per API key.

    You can also download a CSV of usage and fees per API key.

    Geocoding

    Geocoding (also known as forward geocoding) allows you to convert one or more addresses into geographic coordinates (i.e. latitude and longitude). Geocoding will also parse the address and append additional information (e.g. if you specify a zip code, Geocodio will return the city and state corresponding the zip code as well)

    Geocodio supports geocoding of addresses, cities and zip codes in various formats.

    You can either geocode a single address at a time or collect multiple addresses in batches in order to geocode up to 10,000 addresses at the time.

    Whenever possible, batch requests are recommended since they are significantly faster due to reduced network overhead.

    Single address

    A single address can be geocoded by making a simple GET request to the geocode endpoint, you can try this in your browser right now.

    To geocode a single address:

    # Using q parameter
    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2c+Arlington+VA&api_key=YOUR_API_KEY"
    
    # Using individual address components
    curl "https://api.enterprise.geocod.io/v1.7/geocode?street=1109+N+Highland+St&city=Arlington&state=VA&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA")
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA');
    
    const Geocodio = require('geocodio-library-node');
    const geocoder = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA')
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY")
    

    Example response:

    {
      "input": {
        "address_components": {
          "number": "1109",
          "predirectional": "N",
          "street": "Highland",
          "suffix": "St",
          "formatted_street": "N Highland St",
          "city": "Arlington",
          "state": "VA",
          "zip": "22201",
          "country": "US"
        },
        "formatted_address": "1109 N Highland St, Arlington, VA 22201"
      },
      "results": [
        {
          "address_components": {
            "number": "1109",
            "predirectional": "N",
            "street": "Highland",
            "suffix": "St",
            "formatted_street": "N Highland St",
            "city": "Arlington",
            "county": "Arlington County",
            "state": "VA",
            "zip": "22201",
            "country": "US"
          },
          "formatted_address": "1109 N Highland St, Arlington, VA 22201",
          "location": {
            "lat": 38.886665,
            "lng": -77.094733
          },
          "accuracy": 1,
          "accuracy_type": "rooftop",
          "source": "Virginia GIS Clearinghouse"
        }
      ]
    }
    

    HTTP Request

    GET https://api.enterprise.geocod.io/v1.7/geocode

    URL Parameters

    Parameter Description
    q The query (i.e. address) to geocode
    api_key Your Geocodio API key
    country Optional parameter. The country to geocode the address in. The default is to infer from the query, with a fallback to USA.
    fields Optional parameter to request additional field appends.
    limit Optional parameter. The maximum number of results to return. The default is no limit. If set to 0, no limit will be applied.
    format Optional parameter to change the JSON output format to a different pre-defined structure. Currently, "simple" is the only valid value. If not set, the default full JSON output structure is used.
    Parameter Description
    verbose Optional parameter. Available only for enterprise and on-premise customers. Enabling verbose output.

    Alternative URL Parameters

    Instead of using the q parameter, you can use a combination of street, city, state postal_code, and/or country. This can be useful if the address is already stored as separate fields on your end.

    Parameter Description
    street E.g. 1600 Pennsylvania Ave NW
    city E.g. Washington
    state E.g. DC
    postal_code E.g. 20500
    country E.g. Canada (Default to USA)

    The format parameter

    #  To receive a `simple` response, include the string `"simple"`
    #  as the fourth argument after any fields or limit parameters
    #  you have set.
    
      require 'geocodio/gem'
    
      geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
      response = geocodio.geocode(["1109 N Highland St, Arlington, VA"], [], nil, "simple")
    

    Example response when format is set to simple:

    {
      "address": "1109 N Highland St, Arlington, VA 22201",
      "lat": 38.886665,
      "lng": -77.094733,
      "accuracy": 1,
      "accuracy_type": "rooftop",
      "source": "Arlington"
    }
    

    Example response when format is set to simple and no results are found:

    {
      "address": null,
      "lat": null,
      "lng": null,
      "accuracy": null,
      "accuracy_type": null,
      "source": null
    }
    

    In most cases, the standard output format would be used. In certain situations, it can however be beneficial to work with a JSON structure that is specifically designed for your use case.

    simple format

    When format is set to simple, a very simple JSON structure is outputted, with only basic information for the best matched results. This makes it much easier to work with the JSON document in situtations where extra verbosity is not needed.

    The fields parameter is still supported when the simple output format is selected, but the limit parameter has no effect.

    The verbose parameter

    When including the verbose query parameter in your API request, a breakdown of the accuracy score will be returned with each geocoding result. This can be found in the accuracy_breakdown JSON key.

    This feature is only available for enterprise and on-premise customers.

    The accuracy breakdown lists all of the factors used to compute the accuracy score. Each factor has a short description along with a designated category. The following categories are available: MISC, SCORING, STATE, POSTAL_CODE, POSTAL_SERVICE, HOUSE_NUMBER, ENGINE_CASCADE, POINT_GEOCODING_ENGINE, RANGE_GEOCODING_ENGINE, INTERSECTION_GEOCODING_ENGINE, PLACE_GEOCODING_ENGINE.

    Accuracy breakdown descriptions and scores are subject to change and should not be programatically relied upon. Categories can however be expected to be consistent.

    Example response with the following query: "1109 Highland St, Arlington, VA 22201" (Directional is missing)

    ...
    "accuracy": 0.9,
    "accuracy_type": "rooftop",
    "accuracy_breakdown": {
      "Directional was added even though input did not have one": {
        "score": -1,
        "category": "SCORING"
      },
      "Exact USPS match": {
        "score": 0.01,
        "category": "POSTAL_SERVICE"
      }
    },
    ...
    

    Geocoding with Unit Numbers

    To geocode an address with a Unit Number

      curl "https://api.enterprise.geocod.io/v1.7/geocode?q=2800+Clarendon+Blvd+Suite+R500+Arlington+VA+22201&api_key=YOUR_API_KEY"
    

    Example response with Unit Number

    {
      "input": {
        "address_components": {
          "number": "2800",
          "street": "Clarendon",
          "suffix": "Blvd",
          "secondaryunit": "Ste",
          "secondarynumber": "R500",
          "formatted_street": "Clarendon Blvd",
          "city": "Arlington",
          "state": "VA",
          "zip": "22201",
          "country": "US"
        },
        "formatted_address": "2800 Clarendon Blvd, Ste R500, Arlington, VA 22201"
      },
      "results": [
        {
          "address_components": {
            "number": "2800",
            "street": "Clarendon",
            "suffix": "Blvd",
            "secondaryunit": "Ste",
            "secondarynumber": "R500",
            "formatted_street": "Clarendon Blvd",
            "city": "Arlington",
            "county": "Arlington County",
            "state": "VA",
            "zip": "22201",
            "country": "US"
          },
          "formatted_address": "2800 Clarendon Blvd, Ste R500, Arlington, VA 22201",
          "location": {
            "lat": 38.887455,
            "lng": -77.092018
          },
          "accuracy": 1,
          "accuracy_type": "rooftop",
          "source": "Arlington"
        }
      ]
    }
    

    If you include an Apartment or Suite number along as a suffix to the street name, we will parse that number and return it as part of your response. It will be broken out into the secondaryunit and secondarynumber keys within address_components.

    For US addresses: The secondaryunit value will be standardized based on USPS records, if the unit number is deemed mailable and valid.

    E.g. if the unit number is inputted as #R500, the outputted value will be Ste R500.

    In order to verify that the unit number is valid per USPS, you can request the zip4 field append and check the exact_match value. If it is set to true it means that the unit number is accepted by USPS.

    The input Object

    The input object that is returned in the API response is not a one-for-one parsing of the initial address that is provided. In order to ensure that the address_components returned in input are accurate, we cross-reference them with the address_components returned in the results object.

    As such, if we aren't able to identify the exact address location in results, this could impact our ability to return a parsed address in input. In the vast majority of cases, the data returned will match the original address provided to the Geocodio API, but there may be some instances where we are not able to parse the exact input - especially in responses with lower accuracy_type values like place or street_center.

    Batch geocoding

    To perform batch geocoding:

    curl -X POST \
      -H "Content-Type: application/json" \
      -d '["1109 N Highland St, Arlington VA", "525 University Ave, Toronto, ON, Canada", "4410 S Highway 17 92, Casselberry FL", "15000 NE 24th Street, Redmond WA", "17015 Walnut Grove Drive, Morgan Hill CA"]' \
      https://api.enterprise.geocod.io/v1.7/geocode?api_key=YOUR_API_KEY
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    locations = geocodio.geocode(['1109 N Highland St, Arlington VA', '525 University Ave, Toronto, ON, Canada', '4410 S Highway 17 92, Casselberry FL', '15000 NE 24th Street, Redmond WA', '17015 Walnut Grove Drive, Morgan Hill CA'])
    
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    locations = client.batch_geocode([
      '1109 N Highland St, Arlington VA',
      '525 University Ave, Toronto, ON, Canada',
      '4410 S Highway 17 92, Casselberry FL',
      '15000 NE 24th Street, Redmond WA',
      '17015 Walnut Grove Drive, Morgan Hill CA'
    ])
    
    <?php
    $addresses = [
      '1109 N Highland St, Arlington VA',
      '525 University Ave, Toronto, ON, Canada',
      '4410 S Highway 17 92, Casselberry FL',
      '15000 NE 24th Street, Redmond WA',
      '17015 Walnut Grove Drive, Morgan Hill CA'
    ];
    $response = $geocoder->geocode($addresses);
    
    const Geocodio = require('geocodio-library-node');
    const geocoder = new Geocodio('YOUR_API_KEY');
    
    const addresses = [
      '1109 N Highland St, Arlington VA',
      '525 University Ave, Toronto, ON, Canada',
      '4410 S Highway 17 92, Casselberry FL',
      '15000 NE 24th Street, Redmond WA',
      '17015 Walnut Grove Drive, Morgan Hill CA'
    ];
    
    geocoder.geocode(addresses)
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    ;; You can set the API key in the GEOCODIO_API_KEY environment variable
    
    (batch ["1109 N Highland St, Arlington VA" "525 University Ave, Toronto, ON, Canada" "4410 S Highway 17 92, Casselberry FL" "15000 NE 24th Street, Redmond WA" "17015 Walnut Grove Drive, Morgan Hill CA"] :api_key "YOUR_API_KEY")
    

    Example response:

    {
      "results": [
        {
          "query": "1109 N Highland St, Arlington VA",
          "response": {
            "input": {
              "address_components": {
                "number": "1109",
                "predirectional": "N",
                "street": "Highland",
                "suffix": "St",
                "formatted_street": "N Highland St",
                "city": "Arlington",
                "state": "VA",
                "country": "US"
              },
              "formatted_address": "1109 N Highland St, Arlington, VA"
            },
            "results": [
              {
                "address_components": {
                  "number": "1109",
                  "predirectional": "N",
                  "street": "Highland",
                  "suffix": "St",
                  "formatted_street": "N Highland St",
                  "city": "Arlington",
                  "county": "Arlington County",
                  "state": "VA",
                  "zip": "22201",
                  "country": "US"
                },
                "formatted_address": "1109 N Highland St, Arlington, VA 22201",
                "location": {
                  "lat": 38.886672,
                  "lng": -77.094735
                },
                "accuracy": 1,
                "accuracy_type": "rooftop",
                "source": "Arlington"
              },
              {
                "address_components": {
                  "number": "1109",
                  "predirectional": "N",
                  "street": "Highland",
                  "suffix": "St",
                  "formatted_street": "N Highland St",
                  "city": "Arlington",
                  "county": "Arlington County",
                  "state": "VA",
                  "zip": "22201",
                  "country": "US"
                },
                "formatted_address": "1109 N Highland St, Arlington, VA 22201",
                "location": {
                  "lat": 38.886665,
                  "lng": -77.094733
                },
                "accuracy": 1,
                "accuracy_type": "rooftop",
                "source": "Virginia Geographic Information Network (VGIN)"
              }
            ]
          }
        },
        {
          "query": "525 University Ave, Toronto, ON, Canada",
          "response": {
            "input": {
              "address_components": {
                "number": "525",
                "street": "University",
                "suffix": "Ave",
                "formatted_street": "University Ave",
                "city": "Toronto",
                "state": "ON",
                "country": "CA"
              },
              "formatted_address": "525 University Ave, Toronto, ON"
            },
            "results": [
              {
                "address_components": {
                  "number": "525",
                  "street": "University",
                  "suffix": "Ave",
                  "formatted_street": "University Ave",
                  "city": "Toronto",
                  "state": "ON",
                  "country": "CA"
                },
                "formatted_address": "525 University Ave, Toronto, ON",
                "location": {
                  "lat": 43.656258,
                  "lng": -79.388223
                },
                "accuracy": 1,
                "accuracy_type": "rooftop",
                "source": "City of Toronto Open Data"
              }
            ]
          }
        },
        ...
      ]
    }
    

    If you have several addresses that you need to geocode, batch geocoding is a much faster option since it removes the overhead of having to perform multiple HTTP requests.

    Batch geocoding requests are performed by making a POST request to the geocode endpoint, suppliying a JSON array or JSON object in the body with any key of your choosing.

    HTTP Request

    POST https://api.enterprise.geocod.io/v1.7/geocode

    URL Parameters

    Parameter Description
    api_key Your Geocodio API key
    fields Optional parameter to request additional field appends.
    limit Optional parameter. The maximum number of results to return. The default is no limit. If set to 0, no limit will be applied.

    JSON array/object

    When making a batch geocoding request, you can POST queries as either a JSON array or a JSON object. If a JSON object is posted, you can specify a custom key for each element of your choice. This can be useful to match queries up with your existing data after the request is complete.

    If using a JSON array, results are guaranteed to be returned in the same order as they are requested.

    You can also use the alternative parameters with batch geocoding; just pass an associative array instead of a string for each address.

    Here's a couple of examples of what the POST body can look like:

    JSON array

    [
      "1109 N Highland St, Arlington VA",
      "525 University Ave, Toronto, ON, Canada",
      "4410 S Highway 17 92, Casselberry FL",
      "15000 NE 24th Street, Redmond WA",
      "17015 Walnut Grove Drive, Morgan Hill CA"
    ]
    

    Example response when POST'ing JSON object:

    {
      "results": {
        "FID1": {
          "query": "1109 N Highland St, Arlington VA",
          "response": {
            "input": {
              "address_components": {
                "number": "1109",
                "predirectional": "N",
                "street": "Highland",
                "suffix": "St",
                "formatted_street": "N Highland St",
                "city": "Arlington",
                "state": "VA",
                "country": "US"
              },
              "formatted_address": "1109 N Highland St, Arlington, VA"
            },
            "results": [
              {
                "address_components": {
                  "number": "1109",
                  "predirectional": "N",
                  "street": "Highland",
                  "suffix": "St",
                  "formatted_street": "N Highland St",
                  "city": "Arlington",
                  "county": "Arlington County",
                  "state": "VA",
                  "zip": "22201",
                  "country": "US"
                },
                "formatted_address": "1109 N Highland St, Arlington, VA 22201",
                "location": {
                  "lat": 38.886672,
                  "lng": -77.094735
                },
                "accuracy": 1,
                "accuracy_type": "rooftop",
                "source": "Arlington"
              }
            ]
          }
        },
        "FID2": {
         ...
        },
        "FID3": {
         ...
        },
        "FID4": {
         ...
        },
        "FID5": {
         ...
        }
      }
    }
    

    JSON object

    {
      "FID1": "1109 N Highland St, Arlington VA",
      "FID2": "525 University Ave, Toronto, ON, Canada",
      "FID3": "4410 S Highway 17 92, Casselberry FL",
      "FID4": "15000 NE 24th Street, Redmond WA",
      "FID5": "17015 Walnut Grove Drive, Morgan Hill CA"
    }
    

    JSON object with parameters

    {
      "1": {
        "street": "1109 N Highland St",
        "city": "Arlington",
        "state": "VA"
      },
      "2": {
        "city": "Toronto",
        "country": "CA"
      }
    }
    

    Accepted Address Components

    When suppplying an address as individual components (instead of a single string) you can use a combination of street, city, state postal_code, and/or country. This can be useful if the address is already stored as separate fields on your end.

    Parameter Description
    street E.g. 1600 Pennsylvania Ave NW
    city E.g. Washington
    state E.g. DC
    postal_code E.g. 20500
    country E.g. Canada (Default to USA)

    Reverse Geocoding

    Reverse geocoding is the process of converting latitude and longitude into a street address.

    Geocodio will find matching street(s) and determine the correct house number based on the location. Note that Geocodio does not guarantee to return a valid house number; it is our closest approximation.

    As with forward geocoding, you can either geocode a single set of coordinates at the time or collect multiple coordinates in batches. You can batch reverse geocode up to 10,000 coordinates at a time.

    This endpoint can return up to 5 possible matches ranked and ordered by an accuracy score.

    Reverse geocoding single coordinate

    To reverse geocode a single coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.9002898,-76.9990361&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    addresses = geocodio.reverse(['38.9002898,-76.9990361'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    addresses = client.reverse((38.9002898, -76.9990361))
    
    <?php
    $response = $geocoder->reverse('38.9002898,-76.9990361');
    
    const Geocodio = require('geocodio-library-node');
    const geocoder = new Geocodio('YOUR_API_KEY');
    
    geocoder.reverse('38.9002898,-76.9990361')
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single-reverse "38.9002898,-76.9990361" :api_key "YOUR_API_KEY")
    

    Example response:

    {
      "results": [
        {
          "address_components": {
            "number": "508",
            "street": "H",
            "suffix": "St",
            "postdirectional": "NE",
            "formatted_street": "H St NE",
            "city": "Washington",
            "county": "District of Columbia",
            "state": "DC",
            "zip": "20002",
            "country": "US"
          },
          "formatted_address": "508 H St NE, Washington, DC 20002",
          "location": {
            "lat": 38.900432,
            "lng": -76.999031
          },
          "accuracy": 1,
          "accuracy_type": "rooftop",
          "source": "City of Washington"
        },
        {
          "address_components": {
            "number": "510",
            "street": "H",
            "suffix": "St",
            "postdirectional": "NE",
            "formatted_street": "H St NE",
            "city": "Washington",
            "county": "District of Columbia",
            "state": "DC",
            "zip": "20002",
            "country": "US"
          },
          "formatted_address": "510 H St NE, Washington, DC 20002",
          "location": {
            "lat": 38.900429,
            "lng": -76.998965
          },
          "accuracy": 0.9,
          "accuracy_type": "rooftop",
          "source": "City of Washington"
        },
        ...
      ]
    }
    

    A single coordinate can be reverse geocoded by making a simple GET request to the reverse endpoint, you can try this in your browser right now.

    HTTP Request

    GET https://api.enterprise.geocod.io/v1.7/reverse

    URL Parameters

    Parameter Description
    q The query (i.e. latitude/longitude pair) to geocode. The coordinate pair should be comma-separated
    api_key Your Geocodio API key
    fields Optional parameter to request additional field appends.
    limit Optional parameter. The maximum number of results to return. The default is no limit. If set to 0, no limit will be applied.
    format Optional parameter to change the JSON output format to a different pre-defined structure. Currently, "simple" is the only valid value. If not set, the default full JSON output structure is used.

    The format parameter

    #  To receive a `simple` response, include the string `"simple"`
    #  as the fourth argument after any fields or limit parameters
    #  you have set.
    
      require 'geocodio/gem'
    
      geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
      response = geocodio.reverse(["38.9002898,-76.9990361"], [], nil, "simple")
    

    Example response, when format is set to simple:

    {
      "address": "508 H St NE, Washington, DC 20002",
      "lat": 38.900432,
      "lng": -76.999031,
      "accuracy": 1,
      "accuracy_type": "rooftop",
      "source": "Statewide"
    }
    

    Example response, when format is set to simple and no results are found:

    {
      "address": null,
      "lat": null,
      "lng": null,
      "accuracy": null,
      "accuracy_type": null,
      "source": null
    }
    

    In most cases, the standard output format would be used. In certain situations, it can however be beneficial to work with a JSON structure that is specifically designed for your use case.

    simple format

    When format is set to simple, a very simple JSON structure is outputted, with only basic information for the best matched results. This makes it much easier to work with the JSON document in situtations where extra verbosity is not needed.

    The fields parameter is still supported when the simple output format is selected, but the limit parameter has no effect.

    Batch reverse geocoding

    To perform batch reverse geocoding:

    curl -X POST \
      -H "Content-Type: application/json" \
      -d '["35.9746000,-77.9658000","32.8793700,-96.6303900","33.8337100,-117.8362320","35.4171240,-80.6784760"]' \
      https://api.enterprise.geocod.io/v1.7/reverse?api_key=YOUR_API_KEY
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    address_sets = geocodio.reverse(['35.9746000,-77.9658000', '32.8793700,-96.6303900', '33.8337100,-117.8362320', '35.4171240,-80.6784760'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    address_sets = client.reverse([
      (35.9746000, -77.9658000),
      (32.8793700, -96.6303900),
      (33.8337100, -117.8362320),
      (35.4171240, -80.6784760),
    ])
    
    <?php
    $coordinates = [
      '35.9746000,-77.9658000',
      '32.8793700,-96.6303900',
      '33.8337100,-117.8362320',
      '35.4171240,-80.6784760'
    ];
    $results = $geocoder->reverse($coordinates);
    
    const Geocodio = require('geocodio-library-node');
    const geocoder = new Geocodio('YOUR_API_KEY');
    
    const coordinates = [
      '35.9746000,-77.9658000',
      '32.8793700,96.6303900',
      '33.8337100,117.8362320',
      '35.4171240,-80.6784760'
    ];
    
    geocoder.reverse(coordinates)
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (batch-reverse ["35.9746000,-77.9658000" "32.8793700,-96.6303900" "33.8337100,-117.8362320" "35.4171240,-80.6784760"] :api-key "YOUR_API_KEY")
    

    Example response (shortened for brevity):

    {
      "results": [
        {
          "query": "35.9746000,-77.9658000",
          "response": {
            "results": [
              {
                "address_components": {
                  "number": "101",
                  "predirectional": "W",
                  "street": "Washington",
                  "suffix": "St",
                  "formatted_street": "W Washington St",
                  "city": "Nashville",
                  "county": "Nash County",
                  "state": "NC",
                  "zip": "27856",
                  "country": "US"
                },
                "formatted_address": "101 W Washington St, Nashville, NC 27856",
                "location": {
                  "lat": 35.974357,
                  "lng": -77.966064
                },
                "accuracy": 1,
                "accuracy_type": "rooftop",
                "source": "NC Geographic Information Coordinating Council"
              },
              {
                "address_components": {
                  "number": "100",
                  "predirectional": "E",
                  "street": "Washington",
                  "suffix": "St",
                  "formatted_street": "E Washington St",
                  "city": "Nashville",
                  "county": "Nash County",
                  "state": "NC",
                  "zip": "27856",
                  "country": "US"
                },
                "formatted_address": "100 E Washington St, Nashville, NC 27856",
                "location": {
                  "lat": 35.974786,
                  "lng": -77.965387
                },
                "accuracy": 0.9,
                "accuracy_type": "rooftop",
                "source": "NC Geographic Information Coordinating Council"
              },
              ...
            ]
          }
        },
        {
          "query": "32.8793700,-96.6303900",
          "response": {
            "results": [
              {
                "address_components": {
                  "number": "3034",
                  "predirectional": "S",
                  "street": "1st",
                  "suffix": "St",
                  "formatted_street": "S 1st St",
                  "city": "Garland",
                  "county": "Dallas County",
                  "state": "TX",
                  "zip": "75041",
                  "country": "US"
                },
                "formatted_address": "3034 S 1st St, Garland, TX 75041",
                "location": {
                  "lat": 32.879386,
                  "lng": -96.630471
                },
                "accuracy": 1,
                "accuracy_type": "rooftop",
                "source": "City of Garland"
              },
              ...
            ]
          }
        },
        ...
      ]
    }
    

    If you have several coordinates that you need to reverse geocode, batch reverse geocoding is a much faster option since it removes the overhead of having to perform multiple HTTP requests.

    Batch reverse geocoding requests are performed by making a POST request to the reverse endpoint, suppliying a JSON array in the body.

    HTTP Request

    POST https://api.enterprise.geocod.io/v1.7/reverse

    URL Parameters

    Parameter Description
    api_key Your Geocodio API key
    fields Optional parameter to request additional field appends.
    limit Optional parameter. The maximum number of results to return. The default is no limit. If set to 0, no limit will be applied.

    Fields

    To get cd and stateleg field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=cd,stateleg&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=cd,stateleg&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['cd', 'stateleg'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['cd', 'stateleg'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["cd", "stateleg"])
    location = client.reverse((38.886672, -77.094735), fields=["cd", "stateleg"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['cd', 'stateleg']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['cd', 'stateleg']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['cd', 'stateleg'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['cd', 'stateleg'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["cd" "stateleg"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["cd" "stateleg"])
    

    Example response:

    {
      "input": {
        "address_components": {
          "number": "1109",
          "predirectional": "N",
          "street": "Highland",
          "suffix": "St",
          "formatted_street": "N Highland St",
          "city": "Arlington",
          "state": "VA",
          "country": "US"
        },
        "formatted_address": "1109 N Highland St, Arlington, VA"
      },
      "results": [
        {
          "address_components": {
            "number": "1109",
            "predirectional": "N",
            "street": "Highland",
            "suffix": "St",
            "formatted_street": "N Highland St",
            "city": "Arlington",
            "county": "Arlington County",
            "state": "VA",
            "zip": "22201",
            "country": "US"
          },
          "formatted_address": "1109 N Highland St, Arlington, VA 22201",
          "location": {
            "lat": 38.886672,
            "lng": -77.094735
          },
          "accuracy": 1,
          "accuracy_type": "rooftop",
          "source": "Arlington",
          "fields": {
            "congressional_districts": [
              {
                "name": "Congressional District 8",
                "district_number": 8,
                "ocd_id": "ocd-division/country:us/state:va/cd:8",
                "congress_number": "118th",
                "congress_years": "2023-2025",
                "proportion": 1,
                "current_legislators": [
                  {
                    "type": "representative",
                    "bio": {
                      "last_name": "Beyer",
                      "first_name": "Donald",
                      "birthday": "1950-06-20",
                      "gender": "M",
                      "party": "Democrat"
                    },
                    "contact": {
                      "url": "https://beyer.house.gov",
                      "address": "1119 Longworth House Office Building Washington DC 20515-4608",
                      "phone": "202-225-4376",
                      "contact_form": null
                    },
                    "social": {
                      "rss_url": null,
                      "twitter": "RepDonBeyer",
                      "facebook": "RepDonBeyer",
                      "youtube": null,
                      "youtube_id": "UCPJGVbOVcAVGiBwq8qr_T9w"
                    },
                    "references": {
                      "bioguide_id": "B001292",
                      "thomas_id": "02272",
                      "opensecrets_id": "N00036018",
                      "lis_id": null,
                      "cspan_id": "21141",
                      "govtrack_id": "412657",
                      "votesmart_id": "1707",
                      "ballotpedia_id": "Don Beyer",
                      "washington_post_id": null,
                      "icpsr_id": "21554",
                      "wikipedia_id": "Don Beyer"
                    },
                    "source": "Legislator data is originally collected and aggregated by https://github.com/unitedstates/"
                  },
                  {
                    "type": "senator",
                    "bio": {
                      "last_name": "Warner",
                      "first_name": "Mark",
                      "birthday": "1954-12-15",
                      "gender": "M",
                      "party": "Democrat"
                    },
                    "contact": {
                      "url": "https://www.warner.senate.gov",
                      "address": "703 Hart Senate Office Building Washington DC 20510",
                      "phone": "202-224-2023",
                      "contact_form": "https://www.warner.senate.gov/public/index.cfm?p=Contact"
                    },
                    "social": {
                      "rss_url": "http://www.warner.senate.gov/public/?a=rss.feed",
                      "twitter": "MarkWarner",
                      "facebook": "MarkRWarner",
                      "youtube": "SenatorMarkWarner",
                      "youtube_id": "UCwyivNlEGf4sGd1oDLfY5jw"
                    },
                    "references": {
                      "bioguide_id": "W000805",
                      "thomas_id": "01897",
                      "opensecrets_id": "N00002097",
                      "lis_id": "S327",
                      "cspan_id": "7630",
                      "govtrack_id": "412321",
                      "votesmart_id": "535",
                      "ballotpedia_id": "Mark Warner",
                      "washington_post_id": null,
                      "icpsr_id": "40909",
                      "wikipedia_id": "Mark Warner"
                    },
                    "source": "Legislator data is originally collected and aggregated by https://github.com/unitedstates/"
                  },
                  {
                    "type": "senator",
                    "bio": {
                      "last_name": "Kaine",
                      "first_name": "Timothy",
                      "birthday": "1958-02-26",
                      "gender": "M",
                      "party": "Democrat"
                    },
                    "contact": {
                      "url": "https://www.kaine.senate.gov",
                      "address": "231 Russell Senate Office Building Washington DC 20510",
                      "phone": "202-224-4024",
                      "contact_form": "https://www.kaine.senate.gov/contact"
                    },
                    "social": {
                      "rss_url": "http://www.kaine.senate.gov/rss/feeds/?type=all",
                      "twitter": null,
                      "facebook": "SenatorKaine",
                      "youtube": "SenatorTimKaine",
                      "youtube_id": "UC27LgTZlUnBQoNEQFZdn9LA"
                    },
                    "references": {
                      "bioguide_id": "K000384",
                      "thomas_id": "02176",
                      "opensecrets_id": "N00033177",
                      "lis_id": "S362",
                      "cspan_id": "49219",
                      "govtrack_id": "412582",
                      "votesmart_id": "50772",
                      "ballotpedia_id": "Tim Kaine",
                      "washington_post_id": null,
                      "icpsr_id": "41305",
                      "wikipedia_id": "Tim Kaine"
                    },
                    "source": "Legislator data is originally collected and aggregated by https://github.com/unitedstates/"
                  }
                ]
              }
            ],
            "state_legislative_districts": {
              "house": [
                {
                  "name": "State House District 47",
                  "district_number": "47",
                  "ocd_id": "ocd-division/country:us/state:va/sldl:47",
                  "is_upcoming_state_legislative_district": false,
                  "proportion": 1
                }
              ],
              "senate": [
                {
                  "name": "State Senate District 31",
                  "district_number": "31",
                  "ocd_id": "ocd-division/country:us/state:va/sldu:31",
                  "is_upcoming_state_legislative_district": false,
                  "proportion": 1
                }
              ]
            }
          }
        }
      ]
    }
    

    Geocodio allows you to request additional data with forward and reverse geocoding requests. We call this additional data fields.

    To request additional data, just add a fields parameter to your query string and set the value according to the table below. You can request multiple data fields at the same time by separating them with a comma. If the fields parameter has been specified, a new fields key is exposed with each geocoding result containing all necessary data for each field.

    Go ahead, try this in your browser right now.

    Some fields are specific to the US and cannot be queried for other countries.

    Parameter name Description Coverage
    cd, cd113, cd114, cd115, cd116, cd117, cd118 Congressional District & Legislator information US-only
    stateleg, stateleg-next State Legislative District (House & Senate) US-only
    school School District (elementary/secondary or unified) US-only
    census, census2000, census2010, census2011, census2012, census2013, census2014, census2015, census2016, census2017, census2018, census2019, census2020, census2021, census2022, census2023 Census Block/Tract, FIPS codes & MSA/CSA codes US-only
    acs-demographics Demographics (Census) US-only
    acs-economics Economics: Income Data (Census) US-only
    acs-families Families (Census) US-only
    acs-housing Housing (Census) US-only
    acs-social Social: Education & Veteran Status (Census) US-only
    zip4 USPS Zip+4 code and delivery information US-only
    riding, riding-next Riding: Canadian Federal Electoral District Canada-only
    provriding, provriding-next Riding: Canadian Provincial/Territorial Electoral District Canada-only
    statcan Canadian statistical boundaries from Statistics Canada Canada-only
    timezone Timezone

    Congressional Districts

    Field name: cd, cd113, cd114, cd115, cd116, cd117, cd118

    To get cd field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=cd&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=cd&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['cd'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['cd'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["cd"])
    location = client.reverse((38.886672, -77.094735), fields=["cd"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['cd']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['cd']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['cd'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['cd'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["cd"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["cd"])
    
    ...
    "fields": {
        "congressional_districts": [
            {
                "name": "Congressional District 8",
                "district_number": 8,
                "ocd_id": "ocd-division/country:us/state:va/cd:8",
                "congress_number": "118th",
                "congress_years": "2023-2025",
                "proportion": 1,
                "current_legislators": [
                    {
                        "type": "representative",
                        "bio": {
                            "last_name": "Beyer",
                            "first_name": "Donald",
                            "birthday": "1950-06-20",
                            "gender": "M",
                            "party": "Democrat"
                        },
                        "contact": {
                            "url": "https://beyer.house.gov",
                            "address": "1119 Longworth House Office Building Washington DC 20515-4608",
                            "phone": "202-225-4376",
                            "contact_form": null
                        },
                        "social": {
                            "rss_url": null,
                            "twitter": "RepDonBeyer",
                            "facebook": "RepDonBeyer",
                            "youtube": null,
                            "youtube_id": "UCPJGVbOVcAVGiBwq8qr_T9w"
                        },
                        "references": {
                            "bioguide_id": "B001292",
                            "thomas_id": "02272",
                            "opensecrets_id": "N00036018",
                            "lis_id": null,
                            "cspan_id": "21141",
                            "govtrack_id": "412657",
                            "votesmart_id": "1707",
                            "ballotpedia_id": "Don Beyer",
                            "washington_post_id": null,
                            "icpsr_id": "21554",
                            "wikipedia_id": "Don Beyer"
                        },
                        "source": "Legislator data is originally collected and aggregated by https://github.com/unitedstates/"
                    },
                    {
                        "type": "senator",
                        "bio": {
                            "last_name": "Warner",
                            "first_name": "Mark",
                            "birthday": "1954-12-15",
                            "gender": "M",
                            "party": "Democrat"
                        },
                        "contact": {
                            "url": "https://www.warner.senate.gov",
                            "address": "703 Hart Senate Office Building Washington DC 20510",
                            "phone": "202-224-2023",
                            "contact_form": "https://www.warner.senate.gov/public/index.cfm?p=Contact"
                        },
                        "social": {
                            "rss_url": "http://www.warner.senate.gov/public/?a=rss.feed",
                            "twitter": "MarkWarner",
                            "facebook": "MarkRWarner",
                            "youtube": "SenatorMarkWarner",
                            "youtube_id": "UCwyivNlEGf4sGd1oDLfY5jw"
                        },
                        "references": {
                            "bioguide_id": "W000805",
                            "thomas_id": "01897",
                            "opensecrets_id": "N00002097",
                            "lis_id": "S327",
                            "cspan_id": "7630",
                            "govtrack_id": "412321",
                            "votesmart_id": "535",
                            "ballotpedia_id": "Mark Warner",
                            "washington_post_id": null,
                            "icpsr_id": "40909",
                            "wikipedia_id": "Mark Warner"
                        },
                        "source": "Legislator data is originally collected and aggregated by https://github.com/unitedstates/"
                    },
                    {
                        "type": "senator",
                        "bio": {
                            "last_name": "Kaine",
                            "first_name": "Timothy",
                            "birthday": "1958-02-26",
                            "gender": "M",
                            "party": "Democrat"
                        },
                        "contact": {
                            "url": "https://www.kaine.senate.gov",
                            "address": "231 Russell Senate Office Building Washington DC 20510",
                            "phone": "202-224-4024",
                            "contact_form": "https://www.kaine.senate.gov/contact"
                        },
                        "social": {
                            "rss_url": "http://www.kaine.senate.gov/rss/feeds/?type=all",
                            "twitter": null,
                            "facebook": "SenatorKaine",
                            "youtube": "SenatorTimKaine",
                            "youtube_id": "UC27LgTZlUnBQoNEQFZdn9LA"
                        },
                        "references": {
                            "bioguide_id": "K000384",
                            "thomas_id": "02176",
                            "opensecrets_id": "N00033177",
                            "lis_id": "S362",
                            "cspan_id": "49219",
                            "govtrack_id": "412582",
                            "votesmart_id": "50772",
                            "ballotpedia_id": "Tim Kaine",
                            "washington_post_id": null,
                            "icpsr_id": "41305",
                            "wikipedia_id": "Tim Kaine"
                        },
                        "source": "Legislator data is originally collected and aggregated by https://github.com/unitedstates/"
                    }
                ]
            }
        ],
    },
    ...
    

    You can retrieve the Congressional district for an address or coordinate pair using any one of the valid parameter names in the fields query parameter. cd will always return the Congressional district for the current Congress while e.g. cd113 will continue to show the Congressional district for the 113th Congress.

    The field returns the full name of the Congressional district, the district number, the Congress number, and the year range. If the current congress (i.e. cd or cd118) is specified, we will also return detailed information about the current legislators.

    OCD Identifiers

    Open Civic Data Division Identifiers (OCD-IDs) are returned for each district when using cd118.

    When requesting boundaries for other congressional periods, the ocd_id property is still present, but set to null.

    Appending Congressional districts for ZIP codes

    Geocodio can return the most likely Congressional districts given a ZIP code. In cases where there may be multiple possible Congressional districts for a postal code, we will return multiple Congressional districts, and rank them each using a proportion key. This key is a decimal percentage representation of how much of the district boundary that intersect with the zip code boundary (i.e. bigger number = more likely to be the correct district for citizens in that zip code).

    Districts are always sorted by the proportion value in descending order (largest first).

    State Legislative Districts

    Field name: stateleg or stateleg-next

    To get stateleg field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=stateleg&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=stateleg&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['stateleg'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['stateleg'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["stateleg"])
    location = client.reverse((38.886672, -77.094735), fields=["stateleg"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['stateleg']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['stateleg']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['stateleg'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['stateleg'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["stateleg"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["stateleg"])
    

    Example lookup using a full address with stateleg

    ...
    "fields": {
      "state_legislative_districts": {
        "house": [
          {
            "name": "State House District 47",
            "district_number": "47",
            "ocd_id": "ocd-division/country:us/state:va/sldl:47",
            "is_upcoming_state_legislative_district": false,
            "proportion": 1
          }
        ],
        "senate": [
          {
            "name": "State Senate District 31",
            "district_number": "31",
            "ocd_id": "ocd-division/country:us/state:va/sldu:31",
            "is_upcoming_state_legislative_district": false,
            "proportion": 1
          }
        ]
      }
    }
    ...
    

    You can retrieve the state legislative districts for an address or coordinate using stateleg in the fields query parameter. The stateleg-next can be used to retrieve state legislative districts based on upcoming district changes.

    The field will return both the house and senate state legislative district (also known as lower and upper) with the full name and district number for each. For areas with a unicameral legislature (such as Washington, DC or Nebraska), the house and senate keys return the same district.

    Using stateleg-next

    stateleg-next is a preview of upcoming redistricting changes for states that have off-year elections.

    Where available, the state legislative district returned will be based on newly redistricted boundaries.

    The following states are affected. Redistricted boundaries will be returned with the stateleg data append, after the noted cut-off date. Until then, stateleg-next is needed to retrieve districts based on redistricted boundaries.

    If new boundaries are not available, the current boundaries are used instead (effectively returning the same data as when the stateleg field append is used). The is_upcoming_state_legislative_district indicates whether redistricted data is returned.

    To get stateleg-next field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=stateleg-next&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=stateleg-next&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['stateleg-next'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['stateleg-next'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["stateleg-next"])
    location = client.reverse((38.886672, -77.094735), fields=["stateleg-next"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['stateleg-next']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['stateleg-next']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['stateleg-next'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['stateleg-next'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["stateleg-next"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["stateleg-next"])
    

    Example lookup using a full address with stateleg-next

    ...
    "fields": {
      "state_legislative_districts": {
        "house": [
          {
            "name": "State House District 2",
            "district_number": "2",
            "ocd_id": "ocd-division/country:us/state:va/sldl:2",
            "is_upcoming_state_legislative_district": true,
            "proportion": 1
          }
        ],
        "senate": [
          {
            "name": "State Senate District 40",
            "district_number": "40",
            "ocd_id": "ocd-division/country:us/state:va/sldu:40",
            "is_upcoming_state_legislative_district": true,
            "proportion": 1
          }
        ]
      }
    }
    ...
    

    OCD Identifiers

    Open Civic Data Division Identifiers (OCD-IDs) are returned for all legislative districts.

    This id can be used as a unique identifier for each district.

    Example lookup using the 22206 zip code instead of a full address

    ...
    "fields": {
      "state_legislative_districts": {
        "house": [
          {
            "name": "State House District 49",
            "district_number": "49",
            "ocd_id": "ocd-division/country:us/state:va/sldl:49",
            "is_upcoming_state_legislative_district": false,
            "proportion": 0.532
          },
          {
            "name": "State House District 45",
            "district_number": "45",
            "ocd_id": "ocd-division/country:us/state:va/sldl:45",
            "is_upcoming_state_legislative_district": false,
            "proportion": 0.453
          },
          {
            "name": "State House District 46",
            "district_number": "46",
            "ocd_id": "ocd-division/country:us/state:va/sldl:46",
            "is_upcoming_state_legislative_district": false,
            "proportion": 0.015
          }
        ],
        "senate": [
          {
            "name": "State Senate District 30",
            "district_number": "30",
            "ocd_id": "ocd-division/country:us/state:va/sldu:30",
            "is_upcoming_state_legislative_district": false,
            "proportion": 1
          }
        ]
      }
    }
    ...
    

    Appending state legislative districts for ZIP codes

    Geocodio can return the most likely state legislative districts given a ZIP code. In cases where there may be multiple possible state legislative districts for a postal code, we will return multiple state legislative districts, and rank them each using a proportion key. This key is a decimal percentage representation of how much of the district boundary that intersect with the zip code boundary (i.e. bigger number = more likely to be the correct district for citizens in that zip code).

    Districts are always sorted by the proportion in descending order (largest first).

    School Districts

    Field name: school

    To get school field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=school&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=school&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['school'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['school'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["school"])
    location = client.reverse((38.886672, -77.094735), fields=["school"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['school']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['school']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['school'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['school'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["school"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["school"])
    

    Unified school district example

    ...
    "fields": {
      "school_districts": {
        "unified": {
          "name": "Desert Sands Unified School District",
          "lea_code": "11110",
          "grade_low": "KG",
          "grade_high": "12"
        }
      },
    }
    ...
    

    Elementary/Secondary school districts example

    ...
    "fields": {
      "school_districts": {
          "elementary": {
            "name": "Topsfield School District",
            "lea_code": "11670",
            "grade_low": "PK",
            "grade_high": "06"
          },
          "secondary": {
            "name": "Masconomet School District",
            "lea_code": "07410",
            "grade_low": "07",
            "grade_high": "12"
          }
        }
      }
    }
    ...
    

    You can retrieve the school district for an address or coordinate using school in the fields query parameter.

    The field will return either a unified school district or separate elementary and secondary fields depending on the area. Each school district is returned with its full name, the LEA (Local Education Agency) code, as well as the grades supported. Kindergarden is abbreviated as KG and pre-kindergarten is abbreviated as PK.

    Census Block/Tract, FIPS codes & MSA/CSA codes

    Field name: census, census2000, census2010, census2011, census2012, census2013, census2014, census2015, census2016, census2017, census2018, census2019, census2020, census2021, census2022, census2023

    To get census2010 and census field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=census2010,census&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=census2010,census&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['census2010', 'census'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['census2010', 'census'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["census2010", "census"])
    location = client.reverse((38.886672, -77.094735), fields=["census2010", "census"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['census2010', 'census']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['census2010', 'census']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['census2010', 'census'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['census2010', 'census'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["census2010" "census"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["census2010" "census"])
    
    ...
    "fields": {
      "census": {
        "2010": {
          "census_year": 2010,
          "state_fips": "51",
          "county_fips": "51013",
          "tract_code": "101801",
          "block_code": "1004",
          "block_group": "1",
          "full_fips": "510131018011004",
          "place": {
            "name": "Arlington",
            "fips": "5103000"
          },
          "metro_micro_statistical_area": {
            "name": "Washington-Arlington-Alexandria, DC-VA-MD-WV",
            "area_code": "47900",
            "type": "metropolitan"
          },
          "combined_statistical_area": {
            "name": "Washington-Baltimore-Northern Virginia, DC-MD-VA-WV",
            "area_code": "51548"
          },
          "metropolitan_division": {
            "name": "Washington-Arlington-Alexandria, DC-VA-MD-WV",
            "area_code": "47894"
          },
          "county_subdivision": {
            "name": "Arlington",
            "fips": "90072",
            "fips_class": {
              "class_code": "Z7",
              "description": "A county subdivision that is coextensive with a county or equivalent feature or all or part of an incorporated place that the Census Bureau recognizes separately"
            }
          },
          "source": "US Census Bureau"
        },
        "2023": {
          "census_year": 2023,
          "state_fips": "51",
          "county_fips": "51013",
          "tract_code": "101801",
          "block_code": "2004",
          "block_group": "2",
          "full_fips": "510131018012004",
          "place": {
            "name": "Arlington",
            "fips": "5103000"
          },
          "metro_micro_statistical_area": {
            "name": "Washington-Arlington-Alexandria, DC-VA-MD-WV",
            "area_code": "47900",
            "type": "metropolitan"
          },
          "combined_statistical_area": {
            "name": "Washington-Baltimore-Arlington, DC-MD-VA-WV-PA",
            "area_code": "548"
          },
          "metropolitan_division": {
            "name": "Arlington-Alexandria-Reston, VA-WV",
            "area_code": "11694"
          },
          "county_subdivision": {
            "name": "Arlington",
            "fips": "90072",
            "fips_class": {
              "class_code": "Z7",
              "description": "A county subdivision that is coextensive with a county or equivalent feature or all or part of an incorporated place that the Census Bureau recognizes separately"
            }
          },
          "source": "US Census Bureau"
        }
      }
    }
    ...
    

    This will append various US Census-designated codes to your address.

    You can request vintage data for every year back to the 2010 Census. This is done by specifying the year together with the field name, e.g. census2015 for 2015 data. It is also possible to request multiple years at the same time, e.g. census2010,census (as shown in the example response).

    Data for the 2000 census is available as well, using the census2000 field append. Only County, Place, Tract and Block FIPS codes are returned for this Census year.

    Field Description
    census_year The full year that the Census data belongs to (The U.S. Census Bureau might make slight boundary changes from year to year)
    state_fips The two-digit state FIPS code. A full list is available on Wikipedia
    county_fips The five-digit county FIPS code. The two first digits represents the state. A full list of US counties is available on Wikipedia
    tract_code The 6-digit census tract code. This is a subdivision of a county, used for statistical purposes.
    block_code The full 4-digit block code that the location belongs to. This is the smallest geographical unit that the U.S. Census Bureau provides statistical data for.
    block_group The single-digit group number for the block
    full_fips The full 15-digit fips code, consisting of the county fips, tract code and block code

    The U.S. Census Bureau also provides a more detailed guide for the above terms.

    Using Census tracts and blocks, you can match addresses and latitude/longitude pairs with statistical data from the U.S. Census Bureau. For example, appending Census tracts and blocks to addresses enables you to utilize the American Community Survey (ACS) data.

    Place

    This field is returned for locations that are within a census designated place. If the location is not in a census designated place, the API will return null instead of the individual fields.

    You can read more about Census-designated places on Wikipedia.

    Field Description
    name The official Census-designated name for the place
    fips The 7-digit place FIPS code. A place is defined as a city or other census designated area. A full list of ANSI codes is available from the U.S. Census Bureau

    Metropolitan/Micropolitan Statistical Area (MSA)

    This field is returned for locations that are within an MSA area. If no MSA area is associated with the location, the API will return null instead of the individual fields.

    You can read more about Metropolitan and Micropolitan areas on Wikipedia.

    Field Description
    name The official Census-designated name for the area
    area_code Unique code for the area, also known as the CBSA code
    type Can either be "metropolitan" or "micropolitan"

    Combined Statistical Area (CSA)

    This field is returned for locations that are within an CSA area. If no CSA area is associated with the location, the API will return null instead of the individual fields.

    You can read more about Combined Statisical Areas on Wikipedia.

    Field Description
    name The official Census-designated name for the area
    area_code Unique census-defined code for the area

    Metropolitan Divisions (METDIV)

    This field is returned for locations that are within a Metropolitan Division. If no area is associated with the location, the API will return null instead of the individual fields.

    Metropolitan Divisions was introduced by the U.S. Census Bureau in 2003 to further split larger MSA's (Metropolitan Statistical Areas) into smaller groups.

    You can read more about Metropolitan divisions on Wikipedia.

    Field Description
    name The official Census-designated name for the area
    area_code Unique census-defined code for the area

    County Subdivisions

    Depending on the state, this is either a MCD (Minor Civil Division) or CCD (Census County Division).

    Field Description
    name The name of the county subdivision. Depending on the state, this could be a city/town/township name or a district number
    fips Unique census-defined code for the area
    fips_class The class_code and description for the given class code

    Census ACS (American Community Survey)

    Geocodio can return results from the American Community Survey, for any given address in the US. This is performed by looking up 5-year estimates for the census block group associated with the address.

    Please note that a single census block group can cover hundreds of households. As such, the returned data is not specific to the given location only.

    We have divided ACS results into 5 categories: Demographics, Economics (Income Data), Families, Housing and Social (Education & Veteran Status).

    Pricing

    For billing purposes, each category counts as an additional lookup. Do however note that the census field is always included with any acs- field lookups at no additional cost.

    Address formats

    ACS field results are only returned for the following accuracy types:

    As such, it is not possible to get ACS results for city or zip code results. Lookups are not counted towards account usage when ACS field appends are requested for these less accurate results.

    Metadata

    ACS overall metadata:

    ...
    "fields": {
      "acs": {
        "meta": {
          "source": "American Community Survey from the US Census Bureau",
          "survey_years": "2017-2021",
          "survey_duration_years": "5"
        }
        ...
      }
    }
    

    Individual ACS result metadata:

    ...
    "Median age": {
      "meta": {
        "table_id": "B01002",
        "universe": "Total population"
       },
       ...
    }
    

    A meta field with high level data information is returned for all acs results in general as well as individual ACS values.

    This contains information about the exact ACS results we are using, including the years they are covering. We always use 5-year estimates, and always use the most recent data that is available.

    When our ACS results are updated to a newer version, it is not considering a breaking change. This is done as soon as newer Census data is fully available and verified.

    For each individual result, we return the official ACS table id as well as the "universe" that the values covers.

    The universe can be values such as Households, Population 15 Years and Older, Total population, etc.

    Demographics (Census)

    Field name: acs-demographics

    To get acs-demographics field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=acs-demographics&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=acs-demographics&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['acs-demographics'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['acs-demographics'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["acs-demographics"])
    location = client.reverse((38.886672, -77.094735), fields=["acs-demographics"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['acs-demographics']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['acs-demographics']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['acs-demographics'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['acs-demographics'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["acs-demographics"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["acs-demographics"])
    
    ...
    "fields": {
      "census": {...},
      "acs": {
        "meta": {
          "source": "American Community Survey from the US Census Bureau",
          "survey_years": "2017-2021",
          "survey_duration_years": "5"
        },
        "demographics": {
          "Median age": {
            "meta": {
              "table_id": "B01002",
              "universe": "Total population"
            },
            "Total": {
              "value": 29.8,
              "margin_of_error": 2.9
            },
            "Male": {
              "value": 29.8,
              "margin_of_error": 2.1
            },
            "Female": {
              "value": 29.9,
              "margin_of_error": 4.3
            }
          },
          "Population by age range": {
            "meta": {
              "table_id": "B01001",
              "universe": "Total population"
            },
            "Total": {
              "value": 1585,
              "margin_of_error": 287
            },
            "Male": {
              "value": 808,
              "margin_of_error": 200,
              "percentage": 0.51
            },
            "Male: Under 5 years": {
              "value": 23,
              "margin_of_error": 20,
              "percentage": 0.028
            },
            "Male: 5 to 9 years": {
              "value": 13,
              "margin_of_error": 18,
              "percentage": 0.016
            },
            "Male: 10 to 14 years": {
              "value": 20,
              "margin_of_error": 26,
              "percentage": 0.025
            },
            "Male: 15 to 17 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 18 and 19 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 20 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 21 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 22 to 24 years": {
              "value": 96,
              "margin_of_error": 78,
              "percentage": 0.119
            },
            "Male: 25 to 29 years": {
              "value": 268,
              "margin_of_error": 122,
              "percentage": 0.332
            },
            "Male: 30 to 34 years": {
              "value": 124,
              "margin_of_error": 65,
              "percentage": 0.153
            },
            "Male: 35 to 39 years": {
              "value": 56,
              "margin_of_error": 35,
              "percentage": 0.069
            },
            "Male: 40 to 44 years": {
              "value": 84,
              "margin_of_error": 48,
              "percentage": 0.104
            },
            "Male: 45 to 49 years": {
              "value": 30,
              "margin_of_error": 30,
              "percentage": 0.037
            },
            "Male: 50 to 54 years": {
              "value": 33,
              "margin_of_error": 28,
              "percentage": 0.041
            },
            "Male: 55 to 59 years": {
              "value": 29,
              "margin_of_error": 27,
              "percentage": 0.036
            },
            "Male: 60 and 61 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 62 to 64 years": {
              "value": 12,
              "margin_of_error": 19,
              "percentage": 0.015
            },
            "Male: 65 and 66 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 67 to 69 years": {
              "value": 11,
              "margin_of_error": 18,
              "percentage": 0.014
            },
            "Male: 70 to 74 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 75 to 79 years": {
              "value": 9,
              "margin_of_error": 17,
              "percentage": 0.011
            },
            "Male: 80 to 84 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 85 years and over": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female": {
              "value": 777,
              "margin_of_error": 139,
              "percentage": 0.49
            },
            "Female: Under 5 years": {
              "value": 30,
              "margin_of_error": 27,
              "percentage": 0.039
            },
            "Female: 5 to 9 years": {
              "value": 7,
              "margin_of_error": 11,
              "percentage": 0.009
            },
            "Female: 10 to 14 years": {
              "value": 21,
              "margin_of_error": 24,
              "percentage": 0.027
            },
            "Female: 15 to 17 years": {
              "value": 25,
              "margin_of_error": 33,
              "percentage": 0.032
            },
            "Female: 18 and 19 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 20 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 21 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 22 to 24 years": {
              "value": 113,
              "margin_of_error": 106,
              "percentage": 0.145
            },
            "Female: 25 to 29 years": {
              "value": 195,
              "margin_of_error": 63,
              "percentage": 0.251
            },
            "Female: 30 to 34 years": {
              "value": 119,
              "margin_of_error": 52,
              "percentage": 0.153
            },
            "Female: 35 to 39 years": {
              "value": 63,
              "margin_of_error": 48,
              "percentage": 0.081
            },
            "Female: 40 to 44 years": {
              "value": 44,
              "margin_of_error": 30,
              "percentage": 0.057
            },
            "Female: 45 to 49 years": {
              "value": 54,
              "margin_of_error": 39,
              "percentage": 0.069
            },
            "Female: 50 to 54 years": {
              "value": 24,
              "margin_of_error": 21,
              "percentage": 0.031
            },
            "Female: 55 to 59 years": {
              "value": 7,
              "margin_of_error": 13,
              "percentage": 0.009
            },
            "Female: 60 and 61 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 62 to 64 years": {
              "value": 30,
              "margin_of_error": 31,
              "percentage": 0.039
            },
            "Female: 65 and 66 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 67 to 69 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 70 to 74 years": {
              "value": 14,
              "margin_of_error": 21,
              "percentage": 0.018
            },
            "Female: 75 to 79 years": {
              "value": 31,
              "margin_of_error": 37,
              "percentage": 0.04
            },
            "Female: 80 to 84 years": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 85 years and over": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            }
          },
          "Sex": {
            "meta": {
              "table_id": "B01001",
              "universe": "Total population"
            },
            "Total": {
              "value": 1585,
              "margin_of_error": 287
            },
            "Male": {
              "value": 808,
              "margin_of_error": 200,
              "percentage": 0.51
            },
            "Female": {
              "value": 777,
              "margin_of_error": 139,
              "percentage": 0.49
            }
          },
          "Race and ethnicity": {
            "meta": {
              "table_id": "B03002",
              "universe": "Total population"
            },
            "Total": {
              "value": 1585,
              "margin_of_error": 287
            },
            "Not Hispanic or Latino": {
              "value": 1522,
              "margin_of_error": 289,
              "percentage": 0.96
            },
            "Not Hispanic or Latino: White alone": {
              "value": 1175,
              "margin_of_error": 257,
              "percentage": 0.772
            },
            "Not Hispanic or Latino: Black or African American alone": {
              "value": 36,
              "margin_of_error": 31,
              "percentage": 0.024
            },
            "Not Hispanic or Latino: American Indian and Alaska Native alone": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Not Hispanic or Latino: Asian alone": {
              "value": 206,
              "margin_of_error": 108,
              "percentage": 0.135
            },
            "Not Hispanic or Latino: Native Hawaiian and Other Pacific Islander alone": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Not Hispanic or Latino: Some other race alone": {
              "value": 23,
              "margin_of_error": 25,
              "percentage": 0.015
            },
            "Not Hispanic or Latino: Two or more races": {
              "value": 82,
              "margin_of_error": 62,
              "percentage": 0.054
            },
            "Not Hispanic or Latino: Two or more races: Two races including Some other race": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Not Hispanic or Latino: Two or more races: Two races excluding Some other race, and three or more races": {
              "value": 82,
              "margin_of_error": 62,
              "percentage": 1
            },
            "Hispanic or Latino": {
              "value": 63,
              "margin_of_error": 43,
              "percentage": 0.04
            },
            "Hispanic or Latino: White alone": {
              "value": 36,
              "margin_of_error": 30,
              "percentage": 0.571
            },
            "Hispanic or Latino: Black or African American alone": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Hispanic or Latino: American Indian and Alaska Native alone": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Hispanic or Latino: Asian alone": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Hispanic or Latino: Native Hawaiian and Other Pacific Islander alone": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Hispanic or Latino: Some other race alone": {
              "value": 10,
              "margin_of_error": 16,
              "percentage": 0.159
            },
            "Hispanic or Latino: Two or more races": {
              "value": 17,
              "margin_of_error": 25,
              "percentage": 0.27
            },
            "Hispanic or Latino: Two or more races: Two races including Some other race": {
              "value": 17,
              "margin_of_error": 25,
              "percentage": 1
            },
            "Hispanic or Latino: Two or more races: Two races excluding Some other race, and three or more races": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            }
          }
        }
      }
    }
    ...
    

    We provide the data exactly as it is packaged by the Census Bureau in the breakouts it gives. The only change we have made is to add a "percentage" calculation to aid ease of use.

    The data returned includes the following data points. For each data point, the data returned includes the value, margin of error, and percentage.

    Economics: Income Data (Census)

    Field name: acs-economics

    To get acs-economics field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=acs-economics&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=acs-economics&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['acs-economics'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['acs-economics'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["acs-economics"])
    location = client.reverse((38.886672, -77.094735), fields=["acs-economics"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['acs-economics']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['acs-economics']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['acs-economics'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['acs-economics'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["acs-economics"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["acs-economics"])
    
    ...
    "fields": {
      "census": {...},
      "acs": {
        "meta": {
          "source": "American Community Survey from the US Census Bureau",
          "survey_years": "2017-2021",
          "survey_duration_years": "5"
        },
        "economics": {
          "Number of households": {
            "meta": {
              "table_id": "B19001",
              "universe": "Households"
            },
            "Total": {
              "value": 856,
              "margin_of_error": 119
            }
          },
          "Median household income": {
            "meta": {
              "table_id": "B19013",
              "universe": "Households"
            },
            "Total": {
              "value": 163646,
              "margin_of_error": 9443
            }
          },
          "Household income": {
            "meta": {
              "table_id": "B19001",
              "universe": "Households"
            },
            "Less than $10,000": {
              "value": 7,
              "margin_of_error": 11,
              "percentage": 0.008
            },
            "$10,000 to $14,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$15,000 to $19,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$20,000 to $24,999": {
              "value": 23,
              "margin_of_error": 34,
              "percentage": 0.027
            },
            "$25,000 to $29,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$30,000 to $34,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$35,000 to $39,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$40,000 to $44,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$45,000 to $49,999": {
              "value": 9,
              "margin_of_error": 13,
              "percentage": 0.011
            },
            "$50,000 to $59,999": {
              "value": 8,
              "margin_of_error": 13,
              "percentage": 0.009
            },
            "$60,000 to $74,999": {
              "value": 23,
              "margin_of_error": 20,
              "percentage": 0.027
            },
            "$75,000 to $99,999": {
              "value": 93,
              "margin_of_error": 55,
              "percentage": 0.109
            },
            "$100,000 to $124,999": {
              "value": 97,
              "margin_of_error": 50,
              "percentage": 0.113
            },
            "$125,000 to $149,999": {
              "value": 101,
              "margin_of_error": 53,
              "percentage": 0.118
            },
            "$150,000 to $199,999": {
              "value": 200,
              "margin_of_error": 97,
              "percentage": 0.234
            },
            "$200,000 or more": {
              "value": 295,
              "margin_of_error": 86,
              "percentage": 0.345
            }
          }
        }
      }
    }
    ...
    

    We provide the data exactly as it is packaged by the Census Bureau in the breakouts it gives. The only change we have made is to add a "percentage" calculation to aid ease of use.

    The data returned includes the following data points. For each data point, the data returned includes the value, margin of error, and percentage.

    Families (Census)

    Field name: acs-families

    To get acs-families field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=acs-families&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=acs-families&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['acs-families'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['acs-families'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["acs-families"])
    location = client.reverse((38.886672, -77.094735), fields=["acs-families"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['acs-families']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['acs-families']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['acs-families'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['acs-families'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["acs-families"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["acs-families"])
    
    ...
    "fields": {
      "census": {...},
      "acs": {
        "meta": {
          "source": "American Community Survey from the US Census Bureau",
          "survey_years": "2017-2021",
          "survey_duration_years": "5"
        },
        "families": {
          "Household type by household": {
            "meta": {
              "table_id": "B11001",
              "universe": "Households"
            },
            "Total": {
              "value": 856,
              "margin_of_error": 119
            },
            "Family households": {
              "value": 272,
              "margin_of_error": 70,
              "percentage": 0.318
            },
            "Family households: Married-couple family": {
              "value": 234,
              "margin_of_error": 66,
              "percentage": 0.86
            },
            "Family households: Other family": {
              "value": 38,
              "margin_of_error": 30,
              "percentage": 0.14
            },
            "Family households: Other family: Male householder, no spouse present": {
              "value": 6,
              "margin_of_error": 9,
              "percentage": 0.158
            },
            "Family households: Other family: Female householder, no spouse present": {
              "value": 32,
              "margin_of_error": 28,
              "percentage": 0.842
            },
            "Nonfamily households": {
              "value": 584,
              "margin_of_error": 123,
              "percentage": 0.682
            },
            "Nonfamily households: Householder living alone": {
              "value": 320,
              "margin_of_error": 91,
              "percentage": 0.548
            },
            "Nonfamily households: Householder not living alone": {
              "value": 264,
              "margin_of_error": 114,
              "percentage": 0.452
            }
          },
          "Household type by population": {
            "meta": {
              "table_id": "B11002",
              "universe": "Population in Households"
            },
            "Total": {
              "value": 1585,
              "margin_of_error": 287
            },
            "In family households": {
              "value": 663,
              "margin_of_error": 169,
              "percentage": 0.418
            },
            "In family households: In married-couple family": {
              "value": 550,
              "margin_of_error": 159,
              "percentage": 0.83
            },
            "In family households: In married-couple family: Relatives": {
              "value": 550,
              "margin_of_error": 159,
              "percentage": 1
            },
            "In family households: In married-couple family: Nonrelatives": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "In family households: In male householder, no spouse present, family": {
              "value": 16,
              "margin_of_error": 27,
              "percentage": 0.024
            },
            "In family households: In male householder, no spouse present, family: Relatives": {
              "value": 11,
              "margin_of_error": 18,
              "percentage": 0.688
            },
            "In family households: In male householder, no spouse present, family: Nonrelatives": {
              "value": 5,
              "margin_of_error": 9,
              "percentage": 0.313
            },
            "In family households: In female householder, no spouse present, family": {
              "value": 97,
              "margin_of_error": 83,
              "percentage": 0.146
            },
            "In family households: In female householder, no spouse present, family: Relatives": {
              "value": 90,
              "margin_of_error": 76,
              "percentage": 0.928
            },
            "In family households: In female householder, no spouse present, family: Nonrelatives": {
              "value": 7,
              "margin_of_error": 11,
              "percentage": 0.072
            },
            "In nonfamily households": {
              "value": 922,
              "margin_of_error": 277,
              "percentage": 0.582
            }
          },
          "Marital status": {
            "meta": {
              "table_id": "B12001",
              "universe": "Population 15 Years And Older"
            },
            "Male": {
              "value": 752,
              "margin_of_error": 196,
              "percentage": 0.511
            },
            "Male: Never married": {
              "value": 437,
              "margin_of_error": 187,
              "percentage": 0.581
            },
            "Male: Now married": {
              "value": 308,
              "margin_of_error": 71,
              "percentage": 0.41
            },
            "Male: Now married: Married, spouse present": {
              "value": 243,
              "margin_of_error": 72,
              "percentage": 0.789
            },
            "Male: Now married: Married, spouse absent": {
              "value": 65,
              "margin_of_error": 53,
              "percentage": 0.211
            },
            "Male: Now married: Married, spouse absent: Separated": {
              "value": 32,
              "margin_of_error": 41,
              "percentage": 0.492
            },
            "Male: Now married: Married, spouse absent: Other": {
              "value": 33,
              "margin_of_error": 30,
              "percentage": 0.508
            },
            "Male: Widowed": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: Divorced": {
              "value": 7,
              "margin_of_error": 11,
              "percentage": 0.009
            },
            "Female": {
              "value": 719,
              "margin_of_error": 139,
              "percentage": 0.489
            },
            "Female: Never married": {
              "value": 339,
              "margin_of_error": 127,
              "percentage": 0.471
            },
            "Female: Now married": {
              "value": 229,
              "margin_of_error": 66,
              "percentage": 0.318
            },
            "Female: Now married: Married, spouse present": {
              "value": 226,
              "margin_of_error": 66,
              "percentage": 0.987
            },
            "Female: Now married: Married, spouse absent": {
              "value": 3,
              "margin_of_error": 5,
              "percentage": 0.013
            },
            "Female: Now married: Married, spouse absent: Separated": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: Now married: Married, spouse absent: Other": {
              "value": 3,
              "margin_of_error": 5,
              "percentage": 1
            },
            "Female: Widowed": {
              "value": 43,
              "margin_of_error": 41,
              "percentage": 0.06
            },
            "Female: Divorced": {
              "value": 108,
              "margin_of_error": 52,
              "percentage": 0.15
            }
          }
        }
      }
    }
    
    ...
    

    We provide the data exactly as it is packaged by the Census Bureau in the breakouts it gives. The only change we have made is to add a "percentage" calculation to aid ease of use.

    The data returned includes the following data points. For each data point, the data returned includes the value, margin of error, and percentage.

    Housing (Census)

    Field name: acs-housing

    To get acs-housing field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=acs-housing&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=acs-housing&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['acs-housing'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['acs-housing'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["acs-housing"])
    location = client.reverse((38.886672, -77.094735), fields=["acs-housing"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['acs-housing']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['acs-housing']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['acs-housing'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['acs-housing'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["acs-housing"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["acs-housing"])
    
    ...
    "fields": {
      "census": {...},
      "acs": {
        "meta": {
          "source": "American Community Survey from the US Census Bureau",
          "survey_years": "2017-2021",
          "survey_duration_years": "5"
        },
        "housing": {
          "Number of housing units": {
            "meta": {
              "table_id": "B25002",
              "universe": "Housing Units"
            },
            "Total": {
              "value": 936,
              "margin_of_error": 128
            }
          },
          "Occupancy status": {
            "meta": {
              "table_id": "B25002",
              "universe": "Housing Units"
            },
            "Occupied": {
              "value": 856,
              "margin_of_error": 119,
              "percentage": 0.915
            },
            "Vacant": {
              "value": 80,
              "margin_of_error": 68,
              "percentage": 0.085
            }
          },
          "Ownership of occupied units": {
            "meta": {
              "table_id": "B25003",
              "universe": "Occupied Housing Units"
            },
            "Owner occupied": {
              "value": 212,
              "margin_of_error": 67,
              "percentage": 0.248
            },
            "Renter occupied": {
              "value": 644,
              "margin_of_error": 127,
              "percentage": 0.752
            }
          },
          "Units in structure": {
            "meta": {
              "table_id": "B25024",
              "universe": "Housing Units"
            },
            "1, detached unit": {
              "value": 5,
              "margin_of_error": 10,
              "percentage": 0.005
            },
            "1, attached unit": {
              "value": 43,
              "margin_of_error": 24,
              "percentage": 0.046
            },
            "2 units": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "3 or 4 units": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "5 to 9 units": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "10 to 19 unit": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "20 to 49 units": {
              "value": 34,
              "margin_of_error": 28,
              "percentage": 0.036
            },
            "50 or more units": {
              "value": 854,
              "margin_of_error": 124,
              "percentage": 0.912
            },
            "Mobile home units": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Boat, RV, van, etc. units": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            }
          },
          "Median value of owner-occupied housing units": {
            "meta": {
              "table_id": "B25077",
              "universe": "Owner-Occupied Housing Units"
            },
            "Total": {
              "value": 665900,
              "margin_of_error": 58612
            }
          },
          "Value of owner-occupied housing units": {
            "meta": {
              "table_id": "B25075",
              "universe": "Owner-Occupied Housing Units"
            },
            "Less than $10,000": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$10,000 to $14,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$15,000 to $19,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$20,000 to $24,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$25,000 to $29,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$30,000 to $34,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$35,000 to $39,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$40,000 to $49,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$50,000 to $59,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$60,000 to $69,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$70,000 to $79,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$80,000 to $89,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$90,000 to $99,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$100,000 to $124,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$125,000 to $149,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$150,000 to $174,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$175,000 to $199,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$200,000 to $249,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$250,000 to $299,999": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "$300,000 to $399,999": {
              "value": 5,
              "margin_of_error": 10,
              "percentage": 0.024
            },
            "$400,000 to $499,999": {
              "value": 28,
              "margin_of_error": 28,
              "percentage": 0.132
            },
            "$500,000 to $749,999": {
              "value": 110,
              "margin_of_error": 58,
              "percentage": 0.519
            },
            "$750,000 to $999,999": {
              "value": 12,
              "margin_of_error": 14,
              "percentage": 0.057
            },
            "$1,000,000 to $1,499,999": {
              "value": 48,
              "margin_of_error": 34,
              "percentage": 0.226
            },
            "$1,500,000 to $1,999,999": {
              "value": 9,
              "margin_of_error": 13,
              "percentage": 0.042
            },
            "$2,000,000 or more": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            }
          }
        }
      }
    }
    ...
    

    We provide the data exactly as it is packaged by the Census Bureau in the breakouts it gives. The only change we have made is to add a "percentage" calculation to aid ease of use.

    For each data point, we return the value, margin of error, and percentage.

    Data points returned are:

    Social: Education & Veteran Status (Census)

    Field name: acs-social

    To get acs-social field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=acs-social&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=acs-social&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['acs-social'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['acs-social'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["acs-social"])
    location = client.reverse((38.886672, -77.094735), fields=["acs-social"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['acs-social']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['acs-social']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['acs-social'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['acs-social'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["acs-social"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["acs-social"])
    
    ...
    "fields": {
      "census": {...},
      "acs": {
        "meta": {
          "source": "American Community Survey from the US Census Bureau",
          "survey_years": "2017-2021",
          "survey_duration_years": "5"
        },
        "social": {
          "Population by minimum level of education": {
            "meta": {
              "table_id": "B15002",
              "universe": "Population 25 Years And Over"
            },
            "Total": {
              "value": 1237,
              "margin_of_error": 168
            },
            "Male": {
              "value": 656,
              "margin_of_error": 151,
              "percentage": 0.53
            },
            "Male: No schooling completed": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: Nursery to 4th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 5th and 6th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 7th and 8th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 9th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 10th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 11th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 12th grade, no diploma": {
              "value": 6,
              "margin_of_error": 10,
              "percentage": 0.009
            },
            "Male: High school graduate (includes equivalency)": {
              "value": 6,
              "margin_of_error": 9,
              "percentage": 0.009
            },
            "Male: Some college, less than 1 year": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: Some college, 1 or more years, no degree": {
              "value": 27,
              "margin_of_error": 30,
              "percentage": 0.041
            },
            "Male: Associate's degree": {
              "value": 15,
              "margin_of_error": 17,
              "percentage": 0.023
            },
            "Male: Bachelor's degree": {
              "value": 251,
              "margin_of_error": 110,
              "percentage": 0.383
            },
            "Male: Master's degree": {
              "value": 216,
              "margin_of_error": 99,
              "percentage": 0.329
            },
            "Male: Professional school degree": {
              "value": 118,
              "margin_of_error": 55,
              "percentage": 0.18
            },
            "Male: Doctorate degree": {
              "value": 17,
              "margin_of_error": 22,
              "percentage": 0.026
            },
            "Female": {
              "value": 581,
              "margin_of_error": 99,
              "percentage": 0.47
            },
            "Female: No schooling completed": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: Nursery to 4th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 5th and 6th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 7th and 8th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 9th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 10th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 11th grade": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 12th grade, no diploma": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: High school graduate (includes equivalency)": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: Some college, less than 1 year": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: Some college, 1 or more years, no degree": {
              "value": 28,
              "margin_of_error": 25,
              "percentage": 0.048
            },
            "Female: Associate's degree": {
              "value": 13,
              "margin_of_error": 18,
              "percentage": 0.022
            },
            "Female: Bachelor's degree": {
              "value": 228,
              "margin_of_error": 84,
              "percentage": 0.392
            },
            "Female: Master's degree": {
              "value": 207,
              "margin_of_error": 70,
              "percentage": 0.356
            },
            "Female: Professional school degree": {
              "value": 80,
              "margin_of_error": 40,
              "percentage": 0.138
            },
            "Female: Doctorate degree": {
              "value": 25,
              "margin_of_error": 32,
              "percentage": 0.043
            }
          },
          "Population with veteran status": {
            "meta": {
              "table_id": "B21001",
              "universe": "Civilian Population 18 Years And Over"
            },
            "Total": {
              "value": 1412,
              "margin_of_error": 286
            },
            "Veteran": {
              "value": 57,
              "margin_of_error": 39,
              "percentage": 0.04
            },
            "Nonveteran": {
              "value": 1355,
              "margin_of_error": 286,
              "percentage": 0.96
            },
            "Male": {
              "value": 747,
              "margin_of_error": 196,
              "percentage": 0.529
            },
            "Male: Veteran": {
              "value": 57,
              "margin_of_error": 39,
              "percentage": 0.076
            },
            "Male: Nonveteran": {
              "value": 690,
              "margin_of_error": 198,
              "percentage": 0.924
            },
            "Male: 18 to 34 years": {
              "value": 488,
              "margin_of_error": 189,
              "percentage": 0.653
            },
            "Male: 18 to 34 years: Veteran": {
              "value": 13,
              "margin_of_error": 21,
              "percentage": 0.027
            },
            "Male: 18 to 34 years: Nonveteran": {
              "value": 475,
              "margin_of_error": 190,
              "percentage": 0.973
            },
            "Male: 35 to 54 years": {
              "value": 198,
              "margin_of_error": 63,
              "percentage": 0.265
            },
            "Male: 35 to 54 years: Veteran": {
              "value": 33,
              "margin_of_error": 28,
              "percentage": 0.167
            },
            "Male: 35 to 54 years: Nonveteran": {
              "value": 165,
              "margin_of_error": 60,
              "percentage": 0.833
            },
            "Male: 55 to 64 years": {
              "value": 41,
              "margin_of_error": 32,
              "percentage": 0.055
            },
            "Male: 55 to 64 years: Veteran": {
              "value": 11,
              "margin_of_error": 16,
              "percentage": 0.268
            },
            "Male: 55 to 64 years: Nonveteran": {
              "value": 30,
              "margin_of_error": 29,
              "percentage": 0.732
            },
            "Male: 65 to 74 years": {
              "value": 11,
              "margin_of_error": 18,
              "percentage": 0.015
            },
            "Male: 65 to 74 years: Veteran": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 65 to 74 years: Nonveteran": {
              "value": 11,
              "margin_of_error": 18,
              "percentage": 1
            },
            "Male: 75 years and over": {
              "value": 9,
              "margin_of_error": 17,
              "percentage": 0.012
            },
            "Male: 75 years and over: Veteran": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Male: 75 years and over: Nonveteran": {
              "value": 9,
              "margin_of_error": 17,
              "percentage": 1
            },
            "Female": {
              "value": 665,
              "margin_of_error": 130,
              "percentage": 0.471
            },
            "Female: Veteran": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: Nonveteran": {
              "value": 665,
              "margin_of_error": 130,
              "percentage": 1
            },
            "Female: 18 to 34 years": {
              "value": 427,
              "margin_of_error": 126,
              "percentage": 0.642
            },
            "Female: 18 to 34 years: Veteran": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 18 to 34 years: Nonveteran": {
              "value": 427,
              "margin_of_error": 126,
              "percentage": 1
            },
            "Female: 35 to 54 years": {
              "value": 156,
              "margin_of_error": 60,
              "percentage": 0.235
            },
            "Female: 35 to 54 years: Veteran": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 35 to 54 years: Nonveteran": {
              "value": 156,
              "margin_of_error": 60,
              "percentage": 1
            },
            "Female: 55 to 64 years": {
              "value": 37,
              "margin_of_error": 32,
              "percentage": 0.056
            },
            "Female: 55 to 64 years: Veteran": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 55 to 64 years: Nonveteran": {
              "value": 37,
              "margin_of_error": 32,
              "percentage": 1
            },
            "Female: 65 to 74 years": {
              "value": 14,
              "margin_of_error": 21,
              "percentage": 0.021
            },
            "Female: 65 to 74 years: Veteran": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 65 to 74 years: Nonveteran": {
              "value": 14,
              "margin_of_error": 21,
              "percentage": 1
            },
            "Female: 75 years and over": {
              "value": 31,
              "margin_of_error": 37,
              "percentage": 0.047
            },
            "Female: 75 years and over: Veteran": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Female: 75 years and over: Nonveteran": {
              "value": 31,
              "margin_of_error": 37,
              "percentage": 1
            }
          },
          "Period of military service for veterans": {
            "meta": {
              "table_id": "B21002",
              "universe": "Civilian Veterans 18 Years And Over"
            },
            "Total": {
              "value": 57,
              "margin_of_error": 39
            },
            "Gulf War (9/2001 or later), no Gulf War (8/1990 to 8/2001), no Vietnam Era": {
              "value": 34,
              "margin_of_error": 34,
              "percentage": 0.596
            },
            "Gulf War (9/2001 or later) and Gulf War (8/1990 to 8/2001), no Vietnam Era": {
              "value": 18,
              "margin_of_error": 20,
              "percentage": 0.316
            },
            "Gulf War (9/2001 or later), and Gulf War (8/1990 to 8/2001), and Vietnam Era": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Gulf War (8/1990 to 8/2001), no Vietnam Era": {
              "value": 3,
              "margin_of_error": 6,
              "percentage": 0.053
            },
            "Gulf War (8/1990 to 8/2001) and Vietnam Era": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Vietnam Era, no Korean War, no World War II": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Vietnam Era and Korean War, no World War II": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Vietnam Era and Korean War and World War II": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Korean War, no Vietnam Era, no World War II": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Korean War and World War II, no Vietnam Era": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "World War II, no Korean War, no Vietnam Era": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Between Gulf War and Vietnam Era only": {
              "value": 2,
              "margin_of_error": 8,
              "percentage": 0.035
            },
            "Between Vietnam Era and Korean War only": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Between Korean War and World War II only": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            },
            "Pre-World War II only": {
              "value": 0,
              "margin_of_error": 13,
              "percentage": 0
            }
          }
        }
      }
    }
    ...
    

    We provide the data exactly as it is packaged by the Census Bureau in the breakouts it gives. The only change we have made is to add a "percentage" calculation to aid ease of use.

    The data returned includes the following data points. For each data point, the data returned includes the value, margin of error, and percentage.

    USPS ZIP+4

    Field name: zip4

    To get zip4 field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=zip4&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=zip4&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['zip4'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['zip4'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["zip4"])
    location = client.reverse((38.886672, -77.094735), fields=["zip4"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['zip4']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['zip4']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['zip4'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['zip4'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["zip4"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["zip4"])
    
    ...
    "fields": {
      "zip4": {
        "record_type": {
          "code": "S",
          "description": "Street"
        },
        "carrier_route": {
          "id": "C007",
          "description": "City Delivery"
        },
        "building_or_firm_name": null,
        "plus4": [
          "2890"
        ],
        "zip9": [
          "22201-2890"
        ],
        "government_building": null,
        "facility_code": {
          "code": "P",
          "description": "Post Office"
        },
        "city_delivery": true,
        "valid_delivery_area": true,
        "exact_match": true
      }
    }
    ...
    

    In most cases, only a single ZIP4 code is assigned to a result. If that is the case each array has one item.

    ...
    "plus4": [
      "2890"
    ],
    "zip9": [
      "22201-2890"
    ],
    ...
    

    For businesses with a range of ZIP4 codes, an array with 2 items is returned:

    ...
    "plus4": [
      "2890",
      "2900",
    ],
    "zip9": [
      "22201-2890",
      "22201-2900"
    ],
    ...
    

    In some rare cases a ZIP4 record is returned but without a ZIP+4 code (e.g. when it is not a valid delivery area)

    ...
    "plus4": [],
    "zip9": [],
    ...
    

    Example of a building or firm name being returned (316 Pennsylvania Ave. SE, Lobby, Washington, DC)

    ...
    "building_or_firm_name": "The Natl Capital Bank Of Washington",
    ...
    

    Example of a government building result (134 Union Blvd Ste 130 Lakewood, CO)

    ...
    "government_building": {
        "code": "B",
        "description": "Federal Government Building"
    },
    ...
    

    This performs a lookup to determine the USPS ZIP+4 code for a given US location, this lets you retrieve the full 9-digit ZIP Code™, by combining the 5-digit ZIP code with the ZIP+4 code.

    Additional USPS delivery data is also returned.

    Record Type

    The type of ZIP+4 result. Possible values are:

    Carrier Route ID

    A 4-byte code that determines the type of postal route that that servers the address. Possible values are:

    Building or Firm Name

    A USPS-provided name associated with the address. This is available for businesses that have registered their name with USPS and for most federal and state government buildings including schools and offices.

    The building or firm name field takes the secondary address unit into account if available.

    If no name is available, the value is set to null.

    ZIP+4 and ZIP9

    The range of ZIP Codes that are associated with this result as representated by the minimum and maximum number.

    The ZIP9 code consists of the ZIP5 code, a dash, and the +4 code.

    Government Building

    Type of government building (if applicable).

    If no name is available, the value is set to null.

    Facility Code

    Facility code associated with the 5-digit ZIP Code

    Possible values are:

    City Delivery Indicator

    Indicates whether our not the local post office has a city delivery carrier route.

    Valid delivery area

    In some cases an address exists but it is not a valid delivery point for postal purposes. This could for example be because it is an undeveloped lot.

    Exact match

    An exact match means that there was no ambiguity with the lookup and that the given ZIP+4 code is the correct and only match for the given address.

    Most often, not-exact matches are due to lookups for an apartment or office building that is missing a unit/apartment number.

    In these cases it is not possible to determine an accurate ZIP+4 code without supplying secondary address line information.

    Riding: Canadian Federal Electoral District

    Field name: riding or riding-next

    To get riding field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=300+King+St%2C+Sturgeon+Falls%2C+ON+P2B+3A1%2C+Canada&fields=riding&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=46.225866,-79.36316&fields=riding&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['300 King St, Sturgeon Falls, ON P2B 3A1, Canada'], ['riding'])
    location = geocodio.reverse(['46.225866,-79.36316'], ['riding'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("300 King St, Sturgeon Falls, ON P2B 3A1, Canada", fields=["riding"])
    location = client.reverse((46.225866, -79.36316), fields=["riding"])
    
    <?php
    $response = $geocoder->geocode('300 King St, Sturgeon Falls, ON P2B 3A1, Canada', ['riding']);
    $response = $geocoder->reverse('46.225866,-79.36316', ['riding']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('300 King St, Sturgeon Falls, ON P2B 3A1, Canada', ['riding'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('46.225866,-79.36316', ['riding'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "300 King St, Sturgeon Falls, ON P2B 3A1, Canada" :api_key "YOUR_API_KEY" :fields ["riding"])
    (single-reverse "46.225866,-79.36316" :api_key "YOUR_API_KEY" :fields ["riding"])
    

    Example for "300 King St, Sturgeon Falls, ON P2B 3A1, Canada"

    ...
    "fields": {
      "riding": {
        "year": 2013,
        "code": "35070",
        "ocd_id": "ocd-division/country:ca/ed:35070-2013",
        "name_french": "Nipissing--Timiskaming",
        "name_english": "Nipissing--Timiskaming",
        "source": "Statistics Canada"
      }
    }
    ...
    

    Look up the riding for the specified address in Canada. The riding code and OCD-ID is returned along with the French and English name for the riding.

    The OCD-ID can be used to uniquely identify the district, using the Open Civic Data Division Identifiers project.

    In some cases the French and English names will be the same.

    Using riding-next

    riding-next is a preview of upcoming, redistricted ridings. The redistricted ridings were established in 2023 and will be in effect for a federal general election called any time after April 22, 2024.

    To get riding-next field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=300+King+St%2C+Sturgeon+Falls%2C+ON+P2B+3A1%2C+Canada&fields=riding-next&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=46.225866,-79.36316&fields=riding-next&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['300 King St, Sturgeon Falls, ON P2B 3A1, Canada'], ['riding-next'])
    location = geocodio.reverse(['46.225866,-79.36316'], ['riding-next'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("300 King St, Sturgeon Falls, ON P2B 3A1, Canada", fields=["riding-next"])
    location = client.reverse((46.225866, -79.36316), fields=["riding-next"])
    
    <?php
    $response = $geocoder->geocode('300 King St, Sturgeon Falls, ON P2B 3A1, Canada', ['riding-next']);
    $response = $geocoder->reverse('46.225866,-79.36316', ['riding-next']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('300 King St, Sturgeon Falls, ON P2B 3A1, Canada', ['riding-next'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('46.225866,-79.36316', ['riding-next'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "300 King St, Sturgeon Falls, ON P2B 3A1, Canada" :api_key "YOUR_API_KEY" :fields ["riding-next"])
    (single-reverse "46.225866,-79.36316" :api_key "YOUR_API_KEY" :fields ["riding-next"])
    

    Example for "300 King St, Sturgeon Falls, ON P2B 3A1, Canada"

    ...
    "fields": {
      "riding": {
        "year": 2023,
        "code": "35073",
        "ocd_id": "ocd-division/country:ca/ed:35073-2023",
        "name_french": "Nipissing—Timiskaming",
        "name_english": "Nipissing—Timiskaming",
        "source": "Federal Redistribution"
      }
    }
    ...
    

    Riding: Canadian Provincial Electoral District

    Field name: provriding or provriding-next

    To get provriding field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=300+King+St%2C+Sturgeon+Falls%2C+ON+P2B+3A1%2C+Canada&fields=provriding&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=46.225866,-79.36316&fields=provriding&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['300 King St, Sturgeon Falls, ON P2B 3A1, Canada'], ['provriding'])
    location = geocodio.reverse(['46.225866,-79.36316'], ['provriding'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("300 King St, Sturgeon Falls, ON P2B 3A1, Canada", fields=["provriding"])
    location = client.reverse((46.225866, -79.36316), fields=["provriding"])
    
    <?php
    $response = $geocoder->geocode('300 King St, Sturgeon Falls, ON P2B 3A1, Canada', ['provriding']);
    $response = $geocoder->reverse('46.225866,-79.36316', ['provriding']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('300 King St, Sturgeon Falls, ON P2B 3A1, Canada', ['provriding'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('46.225866,-79.36316', ['provriding'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "300 King St, Sturgeon Falls, ON P2B 3A1, Canada" :api_key "YOUR_API_KEY" :fields ["provriding"])
    (single-reverse "46.225866,-79.36316" :api_key "YOUR_API_KEY" :fields ["provriding"])
    

    Example for "300 King St, Sturgeon Falls, ON P2B 3A1, Canada"

    ...
    "fields": {
      "provincial_riding": {
        "ocd_id": "ocd-division/country:ca/province:on/ed:72-2015",
        "name_french": "Nipissing",
        "name_english": "Nipissing",
        "is_upcoming_district": false,
        "source": "Elections Ontario"
      }
    }
    ...
    

    Look up the provincial or territorial electoral district for the specified address in Canada. The OCD-ID is returned along with the French and English name for the riding.

    The OCD-ID can be used to uniquely identify the district, using the Open Civic Data Division Identifiers project.

    In some cases the French and English names will be the same.

    Using provriding-next

    provriding-next is a preview of upcoming, redistricted provincial ridings.

    To get provriding-next field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=203+Laycoe+Crescent%2C+Saskatoon%2C+SK%2C+Canada&fields=provriding-next&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=52.155106,-106.589896&fields=provriding-next&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['203 Laycoe Crescent, Saskatoon, SK, Canada'], ['provriding-next'])
    location = geocodio.reverse(['52.155106,-106.589896'], ['provriding-next'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("203 Laycoe Crescent, Saskatoon, SK, Canada", fields=["provriding-next"])
    location = client.reverse((52.155106, -106.589896), fields=["provriding-next"])
    
    <?php
    $response = $geocoder->geocode('203 Laycoe Crescent, Saskatoon, SK, Canada', ['provriding-next']);
    $response = $geocoder->reverse('52.155106,-106.589896', ['provriding-next']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('203 Laycoe Crescent, Saskatoon, SK, Canada', ['provriding-next'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('52.155106,-106.589896', ['provriding-next'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "203 Laycoe Crescent, Saskatoon, SK, Canada" :api_key "YOUR_API_KEY" :fields ["provriding-next"])
    (single-reverse "52.155106,-106.589896" :api_key "YOUR_API_KEY" :fields ["provriding-next"])
    

    Example for "203 Laycoe Crescent, Saskatoon, SK, Canada"

    ...
    "fields": {
      "provincial_riding": {
        "ocd_id": "ocd-division/country:ca/province:sk/ed:52-2022",
        "name_french": "Saskatoon University-Sutherland",
        "name_english": "Saskatoon University-Sutherland",
        "is_upcoming_district": true,
        "source": "Elections Saskatchewan"
      }
    }
    ...
    

    Canadian statistical boundaries from Statistics Canada

    Field name: statcan

    To get statcan field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=300+King+St%2C+Sturgeon+Falls%2C+ON+P2B+3A1%2C+Canada&fields=statcan&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=46.225866,-79.36316&fields=statcan&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['300 King St, Sturgeon Falls, ON P2B 3A1, Canada'], ['statcan'])
    location = geocodio.reverse(['46.225866,-79.36316'], ['statcan'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("300 King St, Sturgeon Falls, ON P2B 3A1, Canada", fields=["statcan"])
    location = client.reverse((46.225866, -79.36316), fields=["statcan"])
    
    <?php
    $response = $geocoder->geocode('300 King St, Sturgeon Falls, ON P2B 3A1, Canada', ['statcan']);
    $response = $geocoder->reverse('46.225866,-79.36316', ['statcan']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('300 King St, Sturgeon Falls, ON P2B 3A1, Canada', ['statcan'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('46.225866,-79.36316', ['statcan'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "300 King St, Sturgeon Falls, ON P2B 3A1, Canada" :api_key "YOUR_API_KEY" :fields ["statcan"])
    (single-reverse "46.225866,-79.36316" :api_key "YOUR_API_KEY" :fields ["statcan"])
    

    Example for "300 King St, Sturgeon Falls, ON P2B 3A1, Canada"

    ...
    "fields": {
      "statcan": {
        "division": {
          "id": "3549",
          "name": "Parry Sound",
          "type": "DIS",
          "type_description": "District"
        },
        "consolidated_subdivision": {
          "id": "3549066",
          "name": "Callander"
        },
        "subdivision": {
          "id": "3549066",
          "name": "Callander",
          "type": "MU",
          "type_description": "Municipality"
        },
        "economic_region": "Northeast / Nord-est",
        "statistical_area": {
          "code": "575",
          "code_description": "CMA or CA",
          "type": "2",
          "type_description": "Census subdivision within census agglomeration with at least one census tract"
        },
        "cma_ca": {
          "id": "575",
          "name": "North Bay",
          "type": "K",
          "type_description": "Census agglomeration (CA) that is tracted"
        },
        "tract": "5750100.00",
        "designated_place": null,
        "population_centre": {
          "id": "350595",
          "name": "North Bay",
          "type": "1",
          "type_description": "Core inside of a census metropolitan area or census agglomeration",
          "class": "3",
          "class_description": "Medium population centre (30,000 to 99,999)"
        },
        "dissemination_area": {
          "id": "35490146"
        },
        "dissemination_block": {
          "id": "35490146015",
          "population": "155"
        },
        "census_year": 2021
      }
    }
    ...
    

    Retrieve the Statistics Canada boundaries that the given query is within. These boundaries can be matched with data from Statistics Canada to get demographic information about the area the query is within.

    If a given geography does not apply to the query, null will be returned instead.

    Example for "26 Johnson Avenue, Teslin, YT Y0A 1B0, Canada"

    ...
    "fields": {
      "statcan": {
        "division": {
          "id": "6001",
          "name": "Yukon",
          "type": "TER",
          "type_description": "Territory / Territoire"
        },
        "consolidated_subdivision": {
          "id": "6001045",
          "name": "Yukon, Unorganized"
        },
        "subdivision": {
          "id": "6001047",
          "name": "Johnsons Crossing",
          "type": "SÉ",
          "type_description": "Not applicable"
        },
        "economic_region": "Yukon",
        "statistical_area": {
          "code": "000",
          "code_description": "Territories, classification is not applicable",
          "type": "8",
          "type_description": "Census subdivision within a territory"
        },
        "cma_ca": null,
        "tract": null,
        "designated_place": null,
        "population_centre": {
          "id": "609960",
          "name": "Yukon Territory Rural Area / Région rurale: Territoire du Yukon",
          "type": "5",
          "type_description": "Rural area outside of a census metropolitan area or census agglomeration",
          "class": "1",
          "class_description": "Rural area"
        },
        "dissemination_area": {
          "id": "60010135"
        },
        "dissemination_block": {
          "id": "60010135008",
          "population": "10"
        },
        "census_year": 2021
      }
    }
    ...
    

    The following geographies may be found:

    division: Census division

    One of the largest Census designated geographies. The id, name and type code for the query is returned. The type_description contains values such as "District", "County", "Region", among others.

    consolidated_subdivision: Census Consolidated Subdivision

    A geographic unit that is in-between divisions and subdivisions in size. It is a combination of adjacent census subdivisions.

    The id and name are returned for consolidated subdivisions

    subdivison: Census Subdivision

    This generally corresponds to a municipality.

    The subdivision id is returned along with it's name and type code. The type_description is an explanation of the type code and can contain values such as "Town", "Village", "Municipality" or "City" among many others.

    economic_region: Economic region name

    Economic regions are mostly groupings of complete census divisions, created to allow for analysis of regional economic activity.

    statistical_area: Statistical Area

    Statistical areas group census subdivisions based on what type of CMA/CA are they are part of.

    cma_ca: Census Metropolitan Area or Census Agglomeration

    The Census Metropolitan Area or Census Agglomeration that the query is part of. type_description can be either of the following: "Census metropolitan area (CMA)", "Census agglomeration (CA) that is not tracted", "Census agglomeration (CA) that is tracted".

    tract: Census Tract Code

    The full Canadian census tract code that this query is part of.

    designated_place: Designated place

    A Designated Place (DPL) typically refers to a small community or settlement that doesn't fulfill Statistics Canada's requirements for being a census subdivision (an area with municipal status) or a population centre.

    Provinces and territories work with Statistics Canada to establish designated places, which serve as data sources for submunicipal regions.

    population_centre: Population centre

    Population centres in Canada have a population of at least 1,000 and a population density of 400 persons or more per square kilometre, based on the current census population count. Rural areas are defined as areas outside population centres. All of Canada is covered by either population centres or rural areas.

    Population centres are grouped into three categories based on their population size: small, medium, and large. The population count for population centres includes all people living in the cores, secondary cores, and fringes of census metropolitan areas and census agglomerations, as well as those living in population centres outside of these areas.

    dissemination_area and dissemination_block: Dissemination area and block

    The dissemination area is geographically one step lower than census tracts. Dissemination blocks are one step lower than dissemination areas.

    You can read more about the various code names from the Statistics Canada technical specifications page. Statistics Canada also provides a helpful hierarchy of geographic areas.

    Timezone

    Field name: timezone

    To get timezone field appends for an address or a coordinate:

    curl "https://api.enterprise.geocod.io/v1.7/geocode?q=1109+N+Highland+St%2C+Arlington+VA&fields=timezone&api_key=YOUR_API_KEY"
    curl "https://api.enterprise.geocod.io/v1.7/reverse?q=38.886672,-77.094735&fields=timezone&api_key=YOUR_API_KEY"
    
    require 'geocodio/gem'
    
    geocodio = Geocodio::Gem.new('YOUR_API_KEY')
    
    location = geocodio.geocode(['1109 N Highland St, Arlington VA'], ['timezone'])
    location = geocodio.reverse(['38.886672,-77.094735'], ['timezone'])
    
    from geocodio import GeocodioClient
    
    client = GeocodioClient(YOUR_API_KEY)
    
    location = client.geocode("1109 N Highland St, Arlington VA", fields=["timezone"])
    location = client.reverse((38.886672, -77.094735), fields=["timezone"])
    
    <?php
    $response = $geocoder->geocode('1109 N Highland St, Arlington VA', ['timezone']);
    $response = $geocoder->reverse('38.886672,-77.094735', ['timezone']);
    
    const Geocodio = require('geocodio-library-node');
    const geocodio = new Geocodio('YOUR_API_KEY');
    
    geocoder.geocode('1109 N Highland St, Arlington VA', ['timezone'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    geocoder.reverse('38.886672,-77.094735', ['timezone'])
      .then(response => {
        console.log(response);
      })
      .catch(err => {
        console.error(err);
      }
    );
    
    (ns my.ns
      (:require [rodeo.core :refer :all]))
    
    (single "1109 N Highland St, Arlington VA" :api_key "YOUR_API_KEY" :fields ["timezone"])
    (single-reverse "38.886672,-77.094735" :api_key "YOUR_API_KEY" :fields ["timezone"])
    
    ...
    "fields": {
      "timezone": {
        "name": "America/New_York",
        "utc_offset": -5,
        "observes_dst": true,
        "abbreviation": "EST",
        "source": "© OpenStreetMap contributors"
      }
    }
    ...
    

    You can retrieve the timezone for an address or coordinate using timezone in the fields query parameter.

    The field will return the standardized name of the timezone as well as an abbreviation (see table below for examples), the UTC/GMT offset, and whether the location observes Daylight Saving Time (DST).

    The standardized name follows the tzdb format. E.g. America/New_York.

    Abbreviation Description
    AKST Alaska Standard Time
    AST Atlantic Standard Time
    ChST Chamorro Standard Time
    CST Central Standard Time
    EST Eastern Standard Time
    HAST Hawaii-Aleutian Standard Time
    MST Mountain Standard Time
    PST Pacific Standard Time
    SST Samoa Standard Time

    Address components

    All results come with an address_components dictionary. This is an overview of all of the possible keys that you may find.

    The key will not be present if there is no valid value for it. E.g. if the address does not have a predirectional, this key will not be present.

    Name Notes
    number House number, e.g. "2100" or "250 1/2"
    predirectional Directional that comes before the street name, 1-2 characters, e.g. N or NE
    prefix Abbreviated street prefix, particularily common in the case of French addresse e.g. Rue, Boulevard, Impasse
    street Name of the street without number, prefix or suffix, e.g. "Main"
    suffix Abbreviated street suffix, e.g. St., Ave. Rd.
    postdirectional Directional that comes after the street name, 1-2 characters, e.g. N or NE
    secondaryunit Name of the secondary unit, e.g. "Apt" or "Unit". For "input" address components only
    secondarynumber Secondary unit number. For "input" address components only
    city
    county
    state
    zip 5-digit zip code for US addresses. The 3-character FSA is returned for Canadian results - the full postal code is not returned
    country
    formatted_street Fully formatted street, including all directionals, suffix/prefix but not house number

    Accuracy score

    Each geocoded result is returned with an accuracy score, which is a decimal number ranging from 0.00 to 1.00. This score is generated by the internal Geocodio engine based on how accurate the result is believed to be. The higher the score, the better the result. Results are always returned ordered by accuracy score.

    For example, if against all odds an address simply can't be found, instead of returning no results, Geocodio will return a geocoded point based on the postal code or city but with a much lower accuracy score and accuracy type set to "place".

    Generally, accuracy scores that are larger than or equal to 0.8 are the most accurate, whereas results with lower accuracy scores might be very rough matches.

    An accuracy type is also returned with all results. The accuracy types are different for forward and reverse geocoding results.

    We recommend using a combination of the accuracy score and accuracy type to evaluate and filter the returned results.

    Forward geocoding

    Value Description
    rooftop The exact point was found with rooftop level accuracy
    point The exact point was found from address range interpolation where the range contained a single point
    range_interpolation The point was found by performing address range interpolation
    nearest_rooftop_match The exact house number was not found, so a close, neighboring house number was used instead
    intersection The result is an intersection between two streets
    street_center The result is a geocoded street centroid
    place The point is a city/town/place zip code centroid
    county The point is a county centroid
    state The point is a state centroid

    Visual guide to the most common accuracy types

    Visual guide to the most common accuracy types

    Reverse geocoding

    Value Description
    rooftop We found the exact point with rooftop level accuracy
    nearest_street Nearest match for a specific street with estimated street number
    nearest_place Closest city/town/place

    Address formats

    Geocodio supports geocoding the following address components:

    If a city is provided without a state, Geocodio will automatically guess and add the state based on what it is most likely to be. Geocodio also understands shorthands for both streets and cities, for example NYC, SF, etc., are acceptable city names.

    Geocoding queries can be formatted in various ways:

    If a country is not specified in the query, the Geocodio engine will assume the country to be USA.

    Examples of Canadian lookups:

    Intersections

    You can also geocode intersections. Just specify the two streets that you want to geocode in your query. We support various formats:

    An extra address_components_secondary property will be exposed for intersection results, but otherwise, the schema format is the same.

    {
      ...
      "results": [
        {
          "address_components": {
            "street": "4th",
            "suffix": "St",
            "formatted_street": "4th St",
            "city": "San Francisco",
            "county": "San Francisco County",
            "state": "CA",
            "zip": "94103"
          },
          "address_components_secondary": {
            "street": "Market",
            "suffix": "St",
            "formatted_street": "Market St",
            "city": "San Francisco",
            "county": "San Francisco County",
            "state": "CA",
            "zip": "94103"
          },
          "formatted_address": "4th St and Market St, San Francisco, CA 94103",
          "location": {
            "lat": 37.785725,
            "lng": -122.405807
          },
          "accuracy": 1,
          "accuracy_type": "intersection",
          "source": "TIGER/Line® dataset from the US Census Bureau"
        }
      ]
      ...
    }
    

    Errors

    Here is an example of a 422 Unprocessable Entity response:

    {
      "error": "Could not geocode address, zip code or city/state are required"
    }
    

    This error message is returned with a 403 HTTP status code when you exceed the free tier with no payment method on file:

    {
      "error": "You can't make this request as it is above your daily maximum. You can configure billing at https://dash.enterprise.geocod.io"
    }
    

    The Geocodio API employs semantic HTTP status codes:

    Error Code Meaning
    200 OK Hopefully you will see this most of the time. Note that this status code will also be returned even though no geocoding results were available.
    403 Forbidden Invalid API key, or other reason why access is forbidden.
    422 Unprocessable Entity A client error prevented the request from executing successfully (e.g. invalid address provided). A JSON object will be returned with an error key containing a full error message.
    429 Too Many Requests You've reached the Pay as You Go rate limit. Please inspect the following HTTP headers: X-RateLimit-Remaining, X-RateLimit-Limit, X-RateLimit-Period and stop making requests until the end of the X-RateLimit-Period value.
    500 Server Error Hopefully you will never see this...it means that something went wrong in our end. Whoops.

    If you encounter any unexpected errors, please check status.geocod.io for the latest platform status updates.

    Warnings

    The Geocodio API implements the concept of "warnings". This is meant to assist and guide developers when implementing our API.

    Warnings are represented with a _warnings key, and it can be applied to either an individual geocoding result or an overall geocoding query.

    If no warnings have been triggered, the _warnings key will not be part of the JSON output at all.

    Here's an example where the query parameter postalcode accidentally was used instead of postal_code

    {
      "input": {
        ...
      },
      "results": [
        ...
      ],
      "_warnings": [
        "Ignoring parameter \"postalcode\" as it was not expected. Did you mean \"postal_code\"? See full list of valid parameters here: https://www.geocod.io/docs/"
      ]
    }
    

    Warnings can also be triggered for individual results, such as when an ACS field append was specified for a city-level query:

    {
      "input": {
        ...
      },
      "results": [
        {
          ...
          "_warnings": [
            "acs-demographics was skipped since result is not street-level"
          ]
        }
      ]
    }
    

    Client-side access

    To Geocode an address using a jQuery AJAX call.

    <script>
    var address = '1109 N Highland St, Arlington VA',
        apiKey = 'YOUR_API_KEY';
    
    $.get('https://api.enterprise.geocod.io/v1.7/geocode?q='+ encodeURIComponent(address) +'&api_key=' + encodeURIComponent(apiKey), function (response) {
      console.log(response.results);
    });
    </script>
    

    The Geocodio API supports CORS using the Access-Control-Allow-Origin HTTP header. This means that you will be able to make requests directly to the API using JavaScript.

    (See an example to the right.)

    Changelog

    The Geocodio API is continuously improved. Most updates require no changes for API users, but in some cases we might have to introduce breaking changes.

    Breaking changes are introduced with new API versions, allowing you to "upgrade" to the newest version at your own pace. Older API versions are guaranteed to be available for at least 12 months after they have been replaced by a newer version, but may be supported for longer.

    Major changes, that are not breaking are also documented here.

    v1.7

    Released on September 27, 2024

    Released on September 20, 2024

    Released on April 29, 2024

    Released on April 24, 2024

    Released on April 16, 2024

    Released on April 8, 2024

    Released on January 18, 2024

    Released on November 8, 2023

    Released on August 14, 2023

    Released on April 26, 2023

    Released on March 14, 2023

    Released on February 7, 2023

    Released on February 1, 2023

    Released on January 23, 2023

    Released on January 17, 2023

    Released on January 11, 2023

    Released on May 19, 2022

    Released on March 7, 2022

    Released on February 11, 2022

    Released on February 10, 2022

    Released on January 17, 2022

    Released on January 13, 2022

    Released on November 12, 2021

    v1.6

    Released on September 15, 2021

    Released on June 16, 2021

    Released on March 1, 2021

    Released on February 25, 2021

    Released on May 28, 2020

    The following ACS data tables have titles changed and/or values corrected:

    acs-families

    acs-demographics

    v1.5

    Released on May 13, 2020

    v1.4

    Released on September 18th, 2019

    census appends:

    v1.3

    Released on March 12th, 2018

    timezone appends:

    v1.2

    Released on January 20th, 2018

    cd (Congressional district) appends:

    v1.1

    Released on January 8th, 2018

    cd (Congressional district) appends:

    Contact & Support

    Have any questions? Feel free to tweet us @Geocodio or shoot us an email support@geocod.io.

    If you find an error in the documentation or want something to be clarified, please create a pull request or issue so we can correct it.