Parking on public roads - Residential parking areas

DatasetNational · FranceNo auth

**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

Trust score

How is this computed?

fair

Composite of 5 axes from our methodology (proof-based officialness, live verification, metadata completeness, license clarity, agent readiness).

Officialnessweight 25%50/100
Not public-sector → neutral score; not subject to the proof checker.
Availabilityweight 25%60/100
Last verification succeeded but is older than the staleness threshold.
Metadata completenessweight 20%46/100
6 of 13 recommended metadata fields populated.
License clarityweight 15%100/100
Normalised to odbl-1.0 — open, redistributable.
Agent readinessweight 15%40/100
Documentation present · 4 distribution(s) declared · Landing page present

Data schema (5 fields)

Field	Type	Description
NOM	text	—
st_area(shape)	number	—
st_perimeter(shape)	number	—
geo_shape	text	—
geo_point_2d	text	—

Schema inferred from the distribution file's first records 1 hour ago. Column types are sampled estimates, not source-declared.

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.