c0mm0.com — the continuously verified register of European data

Register record·DATASET·FR·AGENCYSTALE · checked 6d ago
M

Make Open Data - Real Estate Transactions on a Mutation Scale

DatasetDiscovered1/7blocked by verifiedPreviewSubscribe🇫🇷France

A dataset from Make Open Data, an open-source initiative that centralizes and transforms French public data, providing real estate transaction records (houses and apartments) grouped by mutation (transfer). For multi-sale transfers, the location (GPS coordinates, postal code, municipality code) corresponds to the main property, with priority given to houses over apartments, or the larger property when types are equal. Multi-sale records also aggregate total area and total number of rooms sold. The data derives from the French government's geolocated property value declarations (DVF) dataset and is maintained collaboratively via a public GitHub repository.[Make Open Data](https://make-open-data.fr/) is an open source initiative to facilitate the transformation of public data by centralizing logic. Here a table providing information on real estate transactions (House or apartment) grouped by mutation. In case of multi-sale transfer, the location (GPS, postal code, common code) will be that of the main good. House if House and Apartment. If you're the same guy, we'll pick the bigger one. Also in case of multisale, the table reports the total area and the total number of pieces of sales. Data catalogue: [Catalogue link Make Open Data](https://data.make-open-data.fr/#/model/model.makeopendata.grouper_mutations) source_url: https://files.data.gouv.fr/geo-dvf/latest/csv/2023/full.csv.gz source_reference: https://www.data.gouv.fr/en/datasets/demandes-de-valeurs-foncieres-geolocalisees/ This is a construction and collaborative project: [Repo Make Open Data link](https://github.com/make-open-data/make-open-data).

housingtradegeospatial
33
poor

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

Data schema (12 fields)

Click a field to see example values.

FieldTypeDescription
id_mutationId mutationtextUnique identifier of the property sale transaction.Unique identifier of the property sale transaction.
valeur_fonciereValeur fonciereintTotal sale price of the property, in euros.Total sale price of the property, in euros.
longitudeLongitudenumberLongitude coordinate of the property's location.Longitude coordinate of the property's location.
latitudeLatitudenumberLatitude coordinate of the property's location.Latitude coordinate of the property's location.
total_piecesTotal piecesintTotal number of rooms in the property.Total number of rooms in the property.
total_surfaceTotal surfaceintTotal floor surface area of the property, in square meters.Total floor surface area of the property, in square meters.
type_localType localtextType of property, house or apartment.Type of property, house or apartment.
code_postalPostal codeintPostal code of the property's location.Postal code of the property's location.
code_communeCommune codeintINSEE code of the municipality where the property is located.INSEE code of the municipality where the property is located.
geopointtextGeospatial point encoding the property's coordinates.Geospatial point encoding the property's coordinates.
prix_m2Prix m2numberSale price per square meter of the property.Sale price per square meter of the property.
prix_m2_knn_5Prix m2 knn 5numberEstimated price per square meter based on the 5 nearest similar sales.Estimated price per square meter based on the 5 nearest similar sales.

Schema inferred from the distribution file's first records 22 days ago. Column types are sampled estimates, not source-declared.

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.

=

Sample data (5 records)

Record 1prix_m2: 2757.1428571428573 · geopoint: 0101000020E61000009702D2FE07444840486AA1
{
  "prix_m2": "2757.1428571428573",
  "geopoint": "0101000020E61000009702D2FE07444840486AA164726A0440",
  "latitude": "48.531494",
  "longitude": "2.551976",
  "type_local": "Maison",
  "code_postal": "77310",
  "id_mutation": "2023-1000002",
  "code_commune": "77407",
  "total_pieces": "4",
  "prix_m2_knn_5": "2722.120342076225",
  "total_surface": "70",
  "valeur_fonciere": "193000"
}
Record 2prix_m2: 3409.090909090909 · geopoint: 0101000020E6100000DC12B9E00C5048407EC685
{
  "prix_m2": "3409.090909090909",
  "geopoint": "0101000020E6100000DC12B9E00C5048407EC6850321D90440",
  "latitude": "48.625393",
  "longitude": "2.60602",
  "type_local": "Maison",
  "code_postal": "77550",
  "id_mutation": "2023-1000006",
  "code_commune": "77296",
  "total_pieces": "5",
  "prix_m2_knn_5": "3411.8609903259517",
  "total_surface": "88",
  "valeur_fonciere": "300000"
}
Record 3prix_m2: 2500 · geopoint: 0101000020E6100000D102B4AD6633484060ADDA
{
  "prix_m2": "2500",
  "geopoint": "0101000020E6100000D102B4AD6633484060ADDA3521CD0540",
  "latitude": "48.401571",
  "longitude": "2.725161",
  "type_local": "Appartement",
  "code_postal": "77210",
  "id_mutation": "2023-1000008",
  "code_commune": "77014",
  "total_pieces": "2",
  "prix_m2_knn_5": "3463.929245971619",
  "total_surface": "52",
  "valeur_fonciere": "130000"
}
Record 4prix_m2: 2267.7083333333335 · geopoint: 0101000020E6100000B85851836934484066DD3F
{
  "prix_m2": "2267.7083333333335",
  "geopoint": "0101000020E6100000B85851836934484066DD3F16A2A30540",
  "latitude": "48.40947",
  "longitude": "2.704899",
  "type_local": "Appartement",
  "code_postal": "77300",
  "id_mutation": "2023-1000024",
  "code_commune": "77186",
  "total_pieces": "5",
  "prix_m2_knn_5": "4766.293666892044",
  "total_surface": "96",
  "valeur_fonciere": "217700"
}
Record 5prix_m2: 3260 · geopoint: 0101000020E6100000C39ACAA2B0534840B16B7B
{
  "prix_m2": "3260",
  "geopoint": "0101000020E6100000C39ACAA2B0534840B16B7BBB25190540",
  "latitude": "48.653828",
  "longitude": "2.637279",
  "type_local": "Maison",
  "code_postal": "77166",
  "id_mutation": "2023-1000028",
  "code_commune": "77175",
  "total_pieces": "2",
  "prix_m2_knn_5": "3473.23700006098",
  "total_surface": "50",
  "valeur_fonciere": "163000"
}

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

Verification Status

Using the API

Query examples

curl -sL 'https://make-open-data.fra1.digitaloceanspaces.com/grouper_mutations_enrichie.csv' -o data.csv

Full csv file download — the schema shown was inferred from the file's first records.

Dataset

Volume & freshness

Data size
121 MB
Last upstream update
2 years ago
2024-07-29

Coverage

First published
2024-06-08

License

No license declared upstream.

Documentation Data dictionary Versioning

Machine-readable & source

Make Open Data - Real Estate Transactions on a Mutation Scale — live verification badge

Embed this badge in a README or wiki — it always shows the latest verification state and quality tier.