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Résultats élections municipales 2026 - 1er tour

Name: Résultats élections municipales 2026 - 1er tour
Creator: opendatasoft

APIQuery nowOpen workbench🇫🇷France

Résultats du premier tour des élections municipales du dimanche 15 mars 2026 pour la mairie de Toulouse. Les résultats sont présentés par bureaux de vote. Listes candidates : Nom de la liste Nom_court N° de la liste Nom tête de liste VIVRE MIEUX LA GAUCHE UNIE, ÉCOLOGISTE, CITOYENNE ET SOLIDAIRE...

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Data schema (36 fields)

Filterable via the API (36)

column_1column_2column_3column_4column_5column_6column_7column_8column_9column_10column_11column_12column_13column_14column_15column_16column_17column_18column_19column_20column_21column_22column_23column_24column_25column_26column_27column_28column_29column_30column_31column_32column_33column_34column_35column_36

Click a field to see example values.

Fill	Field	Type	Description
100%	column_1N° de séquence	int	—
100%	column_2Municipales	text	—
100%	column_3Année d'élection	text	—
100%	column_4Tour de scrutin	int	—
100%	column_5Département	int	—
100%	column_6Code Insee commune	int	—
100%	column_7n° de bureau de vote	text	—
100%	column_8Indicatif I	text	—
100%	column_9Nombre d'inscrits	int	—
100%	column_10Nombre d'abstentions	int	—
100%	column_11Nombre de votants	int	—
100%	column_12Nombre votants d'après émargement	int	—
100%	column_13Nombre bulletins blancs	int	—
100%	column_14Nombre bulletins nuls	int	—
100%	column_15Nombre d'exprimés	int	—
100%	column_16Nombre de listes	int	—
100%	column_17Liste 01 - F Briançon	text	VIVRE MIEUX LA GAUCHE UNIE, ÉCOLOGISTE, CITOYENNE ET SOLIDAIRE
100%	column_18Nombre de voix de la liste 01	int	—
100%	column_19Liste 02 - G Scalli	text	NPA RÉVOLUTIONNAIRES- TOULOUSE OUVRIÉRE ET RÉVOLUTIONNAIRE
100%	column_20Nombre de voix de la liste 02	int	—
100%	column_21Liste 03 - M Adrada	text	LUTTE OUVRIÈRE - LE CAMPS DES TRAVAILLEURS
100%	column_22Nombre de voix de la liste 03	int	—
100%	column_23Liste 04 - J Menendez	text	TOULOUSE POUR LES JEUNES, LES TRAVAILLEURS ET LES SERVICES PUBLICS, CONTRE LES BUDGETS DE GUERRE
100%	column_24Nombre de voix de la liste 04	int	—
100%	column_25Listes 05 - JL Moudenc	text	AVEC JEAN-LUC MOUDENC, PROTEGEONS L'AVENIR DE TOULOUSE
100%	column_26Nombre de voix de la liste 05	int	—
100%	column_27Liste 06 - J Leonardelli	text	LE BON SENS TOULOUSAIN
100%	column_28Nombre de voix de la liste 06	int	—
100%	column_29Liste 07 - A Cottrel	text	A LA RECONQUETE ! DE TOULOUSE
100%	column_30Nombre de voix de la liste 07	int	—
100%	column_31Liste 08 - L Meilhac	text	NOUVEL AIR
100%	column_32Nombre de voix de la liste 08	int	—
100%	column_33Liste 09 - F Piquemal	text	DEMAIN TOULOUSE À GAUCHE ET ÉCOLOGISTE
100%	column_34Nombre de voix de la liste 09	int	—
100%	column_35Liste 10 - V Pedinotti	text	UNE TRAVAILLEUSE AU CAPITOLE
100%	column_36Nombre de voix de la liste 10	int	—

Schema captured from opendatasoft 2 hours 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.

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Sample data (5 records)

Record 1column_1: 5 · column_2: MN

{
  "column_1": 5,
  "column_2": "MN",
  "column_3": "2026",
  "column_4": 1,
  "column_5": 31,
  "column_6": 555,
  "column_7": "0005",
  "column_8": "I",
  "column_9": 957,
  "column_10": 401,
  "column_11": 556,
  "column_12": 556,
  "column_13": 4,
  "column_14": 2,
  "column_15": 550,
  "column_16": 10,
  "column_17": "003",
  "column_18": 121,
  "column_19": "009",
  "column_20": 0,
  "column_21": "001",
  "column_22": 1,
  "column_23": "010",
  "column_24": 3,
  "column_25": "005",
  "column_26": 185,
  "column_27": "008",
  "column_28": 13,
  "column_29": "011",
  "column_30": 3,
  "column_31": "007",
  "column_32": 9,
  "column_33": "004",
  "column_34": 208,
  "column_35": "002",
  "column_36": 7
}

Record 2column_1: 7 · column_2: MN

{
  "column_1": 7,
  "column_2": "MN",
  "column_3": "2026",
  "column_4": 1,
  "column_5": 31,
  "column_6": 555,
  "column_7": "0007",
  "column_8": "I",
  "column_9": 892,
  "column_10": 384,
  "column_11": 508,
  "column_12": 508,
  "column_13": 2,
  "column_14": 1,
  "column_15": 505,
  "column_16": 10,
  "column_17": "003",
  "column_18": 98,
  "column_19": "009",
  "column_20": 0,
  "column_21": "001",
  "column_22": 1,
  "column_23": "010",
  "column_24": 0,
  "column_25": "005",
  "column_26": 233,
  "column_27": "008",
  "column_28": 15,
  "column_29": "011",
  "column_30": 15,
  "column_31": "007",
  "column_32": 2,
  "column_33": "004",
  "column_34": 134,
  "column_35": "002",
  "column_36": 7
}

Record 3column_1: 14 · column_2: MN

{
  "column_1": 14,
  "column_2": "MN",
  "column_3": "2026",
  "column_4": 1,
  "column_5": 31,
  "column_6": 555,
  "column_7": "0014",
  "column_8": "I",
  "column_9": 1159,
  "column_10": 513,
  "column_11": 646,
  "column_12": 646,
  "column_13": 3,
  "column_14": 3,
  "column_15": 640,
  "column_16": 10,
  "column_17": "003",
  "column_18": 165,
  "column_19": "009",
  "column_20": 2,
  "column_21": "001",
  "column_22": 8,
  "column_23": "010",
  "column_24": 2,
  "column_25": "005",
  "column_26": 173,
  "column_27": "008",
  "column_28": 27,
  "column_29": "011",
  "column_30": 6,
  "column_31": "007",
  "column_32": 6,
  "column_33": "004",
  "column_34": 245,
  "column_35": "002",
  "column_36": 6
}

Record 4column_1: 17 · column_2: MN

{
  "column_1": 17,
  "column_2": "MN",
  "column_3": "2026",
  "column_4": 1,
  "column_5": 31,
  "column_6": 555,
  "column_7": "0017",
  "column_8": "I",
  "column_9": 1131,
  "column_10": 362,
  "column_11": 769,
  "column_12": 769,
  "column_13": 3,
  "column_14": 1,
  "column_15": 765,
  "column_16": 10,
  "column_17": "003",
  "column_18": 223,
  "column_19": "009",
  "column_20": 0,
  "column_21": "001",
  "column_22": 2,
  "column_23": "010",
  "column_24": 0,
  "column_25": "005",
  "column_26": 276,
  "column_27": "008",
  "column_28": 8,
  "column_29": "011",
  "column_30": 7,
  "column_31": "007",
  "column_32": 10,
  "column_33": "004",
  "column_34": 229,
  "column_35": "002",
  "column_36": 10
}

Record 5column_1: 18 · column_2: MN

{
  "column_1": 18,
  "column_2": "MN",
  "column_3": "2026",
  "column_4": 1,
  "column_5": 31,
  "column_6": 555,
  "column_7": "0018",
  "column_8": "I",
  "column_9": 781,
  "column_10": 328,
  "column_11": 453,
  "column_12": 453,
  "column_13": 4,
  "column_14": 2,
  "column_15": 447,
  "column_16": 10,
  "column_17": "003",
  "column_18": 126,
  "column_19": "009",
  "column_20": 0,
  "column_21": "001",
  "column_22": 2,
  "column_23": "010",
  "column_24": 0,
  "column_25": "005",
  "column_26": 146,
  "column_27": "008",
  "column_28": 30,
  "column_29": "011",
  "column_30": 9,
  "column_31": "007",
  "column_32": 8,
  "column_33": "004",
  "column_34": 122,
  "column_35": "002",
  "column_36": 4
}

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

Using the API

Configuration

Base URL: https://data.toulouse-metropole.fr/api/explore/v2.1/catalog/datasets/resultats-elections-municipales-2026-1er-tour

License

Licence Ouverte 2.0 (France / Etalab)Open

✓ Redistributable
✓ Attribution required

Query examples

curl -s 'https://data.toulouse-metropole.fr/api/explore/v2.1/catalog/datasets/resultats-elections-municipales-2026-1er-tour/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

20 000 req/day

per ipmeasured

observed 2 hours ago

Dataset

Volume & freshness

Records

284

Last upstream update

4 months ago

2026-03-16

License

No license declared upstream.

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Source: opendatasoft

Machine-readable & source

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Résultats élections municipales 2026 - 1er tour

Trust score

Data schema (36 fields)

Query the data

Sample data (5 records)

Using the API

Configuration

License

Query examples

Rate limits

Dataset

Volume & freshness

License

Machine-readable & source