Commuting - Main Indicators (complete dataset)Déplacements domicile-travail - Principaux indicateurs (dossier complet)

Déplacements domicile-travail - Principaux indicateurs (dossier complet)Commuting - Main Indicators (complete dataset)

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Dataset published by INSEE, the French national statistics institute, providing detailed characteristics of commuters travelling to work, broken down by age and mode of transport. Data are available at both municipal (communal) and supra-municipal geographic levels, covering all of France except Mayotte. The dataset is part of INSEE's population census (Recensement de la population) outputs and can be used to analyse commuting patterns, transport mode choice, and demographic characteristics of the working population across French territories.Caractéristiques des navetteurs selon l'âge et le mode de transport pour aller travailler au niveau communal et supracommunal pour la France hors Mayotte.

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Data schema (9 fields)

Click a field to see example values.

Field	Type	Description
GEOTerritory	string	Geographic area code (commune or supra-communal zone).Geographic area code (commune or supra-communal zone).
WORK_AREAWork area	string	Code identifying the geographic area of the workplace.Code identifying the geographic area of the workplace.
FREQFrequency	string	Frequency of the data, e.g. annual.Frequency of the data, e.g. annual.
EMPSTA_ENQEmpsta enq	string	Employment status code as recorded in the survey.Employment status code as recorded in the survey.
TIME_PERIODPeriod	string	Reference year of the observation.Reference year of the observation.
RP_MEASURERp measure	string	Statistical measure type from the population census.Statistical measure type from the population census.
TRANS	string	Code for the mode of transport used to commute to work.Code for the mode of transport used to commute to work.
AGE	string	Age group code of the individuals.Age group code of the individuals.
OBS_VALUE_NIVEAUValue	number	Observed value, i.e. estimated number of people.Observed value, i.e. estimated number of people.

Schema captured from melodi 4 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 1AGE: Y_GE15 · GEO: 2026-AAV2020-001

{
  "AGE": "Y_GE15",
  "GEO": "2026-AAV2020-001",
  "FREQ": "A",
  "TRANS": "1",
  "WORK_AREA": "_T",
  "EMPSTA_ENQ": "1",
  "RP_MEASURE": "POP",
  "TIME_PERIOD": "2012",
  "OBS_VALUE_NIVEAU": 220847.09555
}

Record 2AGE: Y_GE15 · GEO: 2026-AAV2020-001

{
  "AGE": "Y_GE15",
  "GEO": "2026-AAV2020-001",
  "FREQ": "A",
  "TRANS": "2",
  "WORK_AREA": "_T",
  "EMPSTA_ENQ": "1",
  "RP_MEASURE": "POP",
  "TIME_PERIOD": "2012",
  "OBS_VALUE_NIVEAU": 416028.62459
}

Record 3AGE: Y_GE15 · GEO: 2026-AAV2020-001

{
  "AGE": "Y_GE15",
  "GEO": "2026-AAV2020-001",
  "FREQ": "A",
  "TRANS": "3T4",
  "WORK_AREA": "_T",
  "EMPSTA_ENQ": "1",
  "RP_MEASURE": "POP",
  "TIME_PERIOD": "2012",
  "OBS_VALUE_NIVEAU": 255875.89971
}

Record 4AGE: Y_GE15 · GEO: 2026-AAV2020-001

{
  "AGE": "Y_GE15",
  "GEO": "2026-AAV2020-001",
  "FREQ": "A",
  "TRANS": "5",
  "WORK_AREA": "_T",
  "EMPSTA_ENQ": "1",
  "RP_MEASURE": "POP",
  "TIME_PERIOD": "2012",
  "OBS_VALUE_NIVEAU": 2499736.59952
}

Record 5AGE: Y_GE15 · GEO: 2026-AAV2020-001

{
  "AGE": "Y_GE15",
  "GEO": "2026-AAV2020-001",
  "FREQ": "A",
  "TRANS": "6",
  "WORK_AREA": "_T",
  "EMPSTA_ENQ": "1",
  "RP_MEASURE": "POP",
  "TIME_PERIOD": "2012",
  "OBS_VALUE_NIVEAU": 2365077.41469
}

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

Verification Status

Using the API

Configuration

Base URL: https://api.insee.fr/melodi/data/DS_RP_NAVETTES_PRINC

Query examples

curl -s 'https://api.insee.fr/melodi/data/DS_RP_NAVETTES_PRINC?maxResult=20' -H 'Accept: application/json'

First 20 observations (dimensions + measures) as JSON.

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Machine-readable & source

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