Markets - geo_contoursMarchés - geo_contours

Marchés - geo_contoursMarkets - geo_contours

APIExecutable4/7Query nowOpen workbench Subscribe🇫🇷France

This API provides country boundary geometries used as the cartographic base for mapping the geographic origin of public procurement contract holders, as shown in the Public Procurement ('Commande publique') dashboard published by the city of Strasbourg. It is a supporting geographic reference dataset rather than a procurement dataset itself, intended to enable visualization of contractor locations by country on maps within that dashboard.Contours des pays servant de base à la cartographie utilisée pour l'origine géographique des titulaires de marchés dans le tableau de bord Commande publique

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Trust score

How is this computed?

fair

Weighted across five axes. Tap a ring for what it measures.

Data schema (7 fields)

Filterable via the API (5)

typecodenomregionlien

Click a field to see example values.

Field	Type	Description
geo_point_2dGeo Point	geo_point_2d	Central geographic coordinates (latitude, longitude) of the area.Central geographic coordinates (latitude, longitude) of the area.
geo_shapeShape	geo_shape	Geographic boundary polygon of the area.Geographic boundary polygon of the area.
type	text	Type of administrative area, e.g. country or department.Type of administrative area, e.g. country or department.
code	text	Code identifying the country or department.Code identifying the country or department.
nom	text	Name of the country or department.Name of the country or department.
region	text	Geographic region grouping the country or department.Geographic region grouping the country or department.
lien	text	Internal reference code linking the area to related data.Internal reference code linking the area to related data.

Schema captured from opendatasoft 3 days ago.

Query the data

Pick columns and a sort, then fetch a live preview straight from the source. Choose an API-filterable column (marked ▾) under “Where” to pick from its list of values.

Where=

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Sample data (5 records)

Record 1nom: Tarn · code: 81

{
  "nom": "Tarn",
  "code": "81",
  "lien": "250_81",
  "type": "departement",
  "region": "Europe",
  "geo_shape": "[large value omitted]",
  "geo_point_2d": {
    "lat": 43.785381975,
    "lon": 2.16580839024
  }
}

Record 2nom: Lesotho · code: LS

{
  "nom": "Lesotho",
  "code": "LS",
  "lien": "426",
  "type": "pays",
  "region": "Afrique sub-saharienne",
  "geo_shape": {
    "type": "Feature",
    "geometry": {
      "type": "Polygon",
      "coordinates": [
        [
          [
            27.014720916748047,
            -29.641729354858395
          ],
          [
            27.32805061340332,
            -30.139450073242184
          ],
          [
            27.3952693939209,
            -30.12833023071289
          ],
          [
            27.38098907470703,
            -30.31600952148437
          ],
          [
            27.45970916748047,
            -30.311950683593754
          ],
          [
            27.564130783081055,
            -30.403409957885742
          ],
          [
            27.69083023071289,
            -30.54861068725586
          ],
          [
            27.738040924072266,
            -30.597780227661133
          ],
          [
            28.09777069091797,
            -30.65888977050781
          ],
          [
            28.09193992614746,
            -30.60334014892578
          ],
          [
            28.159990310668945,
            -30.498329162597656
          ],
          [
            28.144710540771484,
            -30.454170227050778
          ],
          [
            28.25749969482422,
            -30.326669692993164
          ],
          [
            28.21748924255371,
            -30.301120758056637
          ],
          [
            28.24165916442871,
            -30.263059616088864
          ],
          [
            28.544719696044922,
            -30.114450454711914
          ],
          [
            28.78527069091797,
            -30.103609085083004
          ],
          [
            29.161100387573242,
            -29.921119689941403
          ],
          [
            29.157489776611328,
            -29.851669311523438
          ],
          [
            29.124710083007812,
            -29.832229614257812
          ],
          [
            29.166929244995117,
            -29.672500610351566
          ],
          [
            29.312210083007812,
            -29.57611083984375
          ],
          [
            29.2933292388916,
            -29.504999160766598
          ],
          [
            29.357219696044922,
            -29.450559616088864
          ],
          [
            29.418050765991207,
            -29.43333053588867
          ],
          [
            29.455549240112305,
            -29.353340148925785
          ],
          [
            29.333049774169925,
            -29.092500686645508
          ],
          [
            29.073879241943356,
            -28.966669082641598
          ],
          [
            28.97610092163086,
            -28.88722038269043
          ],
          [
            28.700410842895508,
            -28.613670349121094
          ],
          [
            28.651100158691406,
            -28.569450378417965
          ],
          [
            28.146379470825195,
            -28.723049163818356
          ],
          [
            27.98055076599121,
            -28.883060455322266
          ],
          [
            27.929990768432617,
            -28.85334014892578
          ],
          [
            27.879989624023434,
            -28.912500381469723
          ],
          [
            27.731380462646484,
            -28.941110610961914
          ],
          [
            27.4566593170166,
            -29.291109085083004
          ],
          [
            27.34999084472656,
            -29.481950759887695
          ],
          [
            27.014720916748047,
            -29.641729354858395
          ]
        ]
      ]
    },
    "properties": {}
  },
  "geo_point_2d": {
    "lat": -29.5740697159,
    "lon": 28.2419026352
  }
}

Record 3nom: Kirghizistan · code: KG

{
  "nom": "Kirghizistan",
  "code": "KG",
  "lien": "417",
  "type": "pays",
  "region": "Asie",
  "geo_shape": "[large value omitted]",
  "geo_point_2d": {
    "lat": 41.4637884657,
    "lon": 74.554281901
  }
}

Record 4nom: Haute-Vienne · code: 87

{
  "nom": "Haute-Vienne",
  "code": "87",
  "lien": "250_87",
  "type": "departement",
  "region": "Europe",
  "geo_shape": "[large value omitted]",
  "geo_point_2d": {
    "lat": 45.8925002241,
    "lon": 1.23526925698
  }
}

Record 5nom: Saint-Christophe et Nevis · code: —

{
  "nom": "Saint-Christophe et Nevis",
  "code": null,
  "lien": null,
  "type": "pays",
  "region": "Caraïbes",
  "geo_shape": "[large value omitted]",
  "geo_point_2d": {
    "lat": 17.2630965879,
    "lon": -62.6954867403
  }
}

Live sample captured at profiling time — values may have changed upstream.

Verification Status

Using the API

Configuration

Base URL: https://data.strasbourg.eu/api/explore/v2.1/catalog/datasets/marches_geo_contours

Query examples

curl -s 'https://data.strasbourg.eu/api/explore/v2.1/catalog/datasets/marches_geo_contours/records?limit=20' -H 'Accept: application/json'

First 20 records of the dataset as JSON.

Uses the Opendatasoft Explore v2.1 syntax — supports select, where, group_by and order_by.

Full API documentation ↗

Rate limits

2 000 000 req/day

per ipmeasured

observed 3 days ago

Dataset

Volume & freshness

Records

303

Last upstream update

6 years ago

2021-05-20

License

No license declared upstream.

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Source: opendatasoft

Machine-readable & source

JSON

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