Parking on public roads - Residential parking areas

DatasetDiscovered1/7blocked by verifiedPreviewSubscribe🇫🇷France

This dataset covers residential parking areas in Paris, a scheme designed to make it easier for local residents to park near their homes while encouraging the use of alternative modes of transport within the city. It is published by the Direction de la Voirie et des Déplacements of the City of Paris and includes a cartographic layer showing the boundaries of the various residential parking zones across the capital, with data current as of June 2023. The dataset supports municipal parking policy and complements information provided on the official paris.fr website regarding residential parking rules and permit procedures.**Residential parking makes it easier for Parisian residents to park near their homes and encourages them to use other means of transport in Paris.** For more information on residential parking: [paris.fr](https://www.paris.fr/pages/stationnement-residentiel-mode-d-emploi-2078) [ **Cartography of Residential Parking Areas**](https://capgeo.sig.paris.fr/Apps/Residential Parking Areas/) Data June 2023. [](http://www.paris.fr/practice/placements-voirie/parking/parking-residential-mode-d-emploi/rub_369_stand_11472_port_1169).

transport

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Trust score

How is this computed?

fair

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

Data schema (5 fields)

Click a field to see example values.

Field	Type	Description
NOM	text	Name or code of the residential parking area.Name or code of the residential parking area.
st_area(shape)St area(shape)	number	Area of the parking zone's geometric shape.Area of the parking zone's geometric shape.
st_perimeter(shape)St perimeter(shape)	number	Perimeter length of the parking zone's geometric shape.Perimeter length of the parking zone's geometric shape.
geo_shapeShape	text	Geographic boundary of the parking area as GeoJSON geometry.Geographic boundary of the parking area as GeoJSON geometry.
geo_point_2dCoordinates	text	Latitude and longitude of the parking area's center point.Latitude and longitude of the parking area's center point.

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

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Sample data (5 records)

NOM	st_area(shape)	st_perimeter(shape)	geo_shape	geo_point_2d
20M	523934.07846590434	3437.1447455663297	{"coordinates": [[[2.4025323541918393, 48.87600201762109], [2.402788932191029, 48.87543300510487], [2.403166951556965, 48.874550307807155], [2.4031881827692705, 48.874501247179005], [2.403437060425384, 48.8739164378748], [2.403789522643514, 48.87306466410925], [2.403917769546744, 48.872758837011], [2.4042303593490786, 48.87205306729767], [2.4043195419823062, 48.87184976702196], [2.4043832623306853, 48.87170324082656], [2.4039129168357243, 48.87168420783213], [2.40237914415615, 48.87158659054556]…	48.87324436487608, 2.396512057589965
7N	372214.8592662264	3079.476209924493	{"coordinates": [[[2.327193129402435, 48.85162531552694], [2.3268661325822513, 48.85140841292512], [2.3266387802506765, 48.85126155459047], [2.325273664623704, 48.850696639775485], [2.324596672394049, 48.850418290864], [2.3241393796987433, 48.85023024278463], [2.323286129065592, 48.84982575362357], [2.322897838148653, 48.849634889178375], [2.3221331653477484, 48.84924972532446], [2.321034748534363, 48.84867692695126], [2.320540880534457, 48.848419936937844], [2.320483844077894, 48.84839013196003…	48.84945914565681, 2.3179850233826045
7J	432965.68116351694	2658.9121451333867	{"coordinates": [[[2.3034903576239927, 48.85879869535598], [2.3042559732487504, 48.85902576618648], [2.305099126233156, 48.85922911668064], [2.306293216715742, 48.859470623050704], [2.3073442394263224, 48.85964773210704], [2.3076398056703353, 48.85969009326639], [2.30781867493493, 48.85971571631409], [2.308845041633771, 48.85982773621029], [2.3096363429115163, 48.85989776766808], [2.3101755190553974, 48.85993857777788], [2.3113629551809023, 48.85994916705879], [2.312808497247254, 48.859952278427…	48.85655746745021, 2.3089005806207763
6E	1028882.3988860165	4550.822366851776	{"coordinates": [[[2.3329098194506774, 48.85934963337093], [2.3331312952404955, 48.85930376878205], [2.3366092392315143, 48.858582844007856], [2.3375470714935846, 48.85838858129074], [2.3403655520763955, 48.85683390112019], [2.3403817340828383, 48.856824978813854], [2.3404779730742487, 48.85677206977405], [2.3408553043431812, 48.85656290001958], [2.3409609163777274, 48.85647143301953], [2.3419377927722596, 48.85562565293582], [2.3426821480790427, 48.854982560681364], [2.3428047881387313, 48.8548…	48.852872917427845, 2.3357941986048676
19K	1227423.2330524265	4606.800120616695	{"coordinates": [[[2.379409348557588, 48.888368307581004], [2.382796266033323, 48.890049621967876], [2.3829318511297086, 48.890116717629645], [2.3845733758332193, 48.89093172127491], [2.384699591139668, 48.89099461184209], [2.3879129641447983, 48.892661223235585], [2.3916518555109483, 48.89453306765415], [2.3936569798867624, 48.895499227897744], [2.3948166010236864, 48.89577530196229], [2.396890049587456, 48.89603922504262], [2.3969947013915998, 48.89586887318571], [2.397018522390361, 48.8958306…	48.88914555285507, 2.390656230329271

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

Verification Status

Using the API

Query examples

curl -sL 'https://opendata.paris.fr/api/explore/v2.1/catalog/datasets/stationnement-sur-voie-publique-secteurs-residentiels/exports/csv?use_labels=true' -o data.csv

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