# France Property Price Stats: €/m² by Town & Trends (DVF) (`datacraft-studio/france-property-price-stats`) Actor

Official French property price statistics from DVF (Etalab): median and mean price per m², number of sales for apartments, houses and commercial premises, monthly history and trend, by town, postcode, Paris/Lyon/Marseille district, EPCI, department or all France. Pay per area.

- **URL**: https://apify.com/datacraft-studio/france-property-price-stats.md
- **Developed by:** [Yahya Nouali](https://apify.com/datacraft-studio) (community)
- **Categories:** Real estate, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$4.00 / 1,000 area statistics

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## France Property Price Stats: €/m² by Town & Trends (DVF)

Official French property price statistics per m², ready to use: **median and mean price per m², number of sales and monthly trend** for apartments, houses and commercial premises, for any town, postcode, Paris/Lyon/Marseille district, intercommunality (EPCI), department or France as a whole.

The figures are the official *Statistiques DVF* computed by Etalab (data.gouv.fr) from the DGFiP land-value register (DVF). No individual sale or address is returned: only aggregated statistics, and prices based on fewer than 5 sales are hidden.

### Use cases

- Price per m² for a list of towns in one run (agents, investors, proptech, relocation, banks).
- Compare districts of Paris, Lyon or Marseille.
- Every town of a department for a market map.
- 12-month trend to spot rising or falling markets.

### Example output (shortened)

```json
{
  "code": "69123",
  "name": "Lyon",
  "level": "commune",
  "periodStart": "2021-07",
  "periodEnd": "2026-06",
  "residentialSales": 36953,
  "residentialMedianPriceM2": 4787,
  "apartmentMedianPriceM2": 4768,
  "houseMedianPriceM2": 5954,
  "residentialTrend": { "fromMonth": "2025-07", "toMonth": "2026-06", "earlierHalfPriceM2": 4527, "laterHalfPriceM2": 4427, "changePct": -2.2 },
  "monthly": [{ "month": "2026-06", "residentialSales": 666, "residentialMedianPriceM2": 4448, "...": "..." }]
}
```

*residential* = apartments + houses. *commercial* = commercial premises (locaux). The last row of each run is a summary with the period covered and the source date.

### Input

| Field | Meaning |
|---|---|
| `communes` | Town names or INSEE codes (`Lyon`, `Paris 15e Arrondissement`, `33063`) |
| `postcodes` | Returns every town or city district covered by the postcode |
| `departments` | Department-level statistics (`69`, `2A`, `974`) |
| `epcis` | Intercommunality SIREN (`200046977` = Métropole de Lyon) |
| `allCommunesOfDepartments` | Every town of the given departments |
| `allDepartments`, `includeFrance` | Add all departments / a national row |
| `monthsOfHistory` | Monthly history and trend window (default 12) |
| `minSales` | Minimum number of sales before a price is shown (default and minimum 5) |
| `maxItems` | Cap on delivered (and charged) areas |

### Pricing

Pay per event: **$0.004 per area delivered**, monthly history included. Areas not found and the summary row are free. Example: 50 towns = $0.20 plus the platform start.

### Source, licence and limits

Data: [Statistiques DVF](https://www.data.gouv.fr/datasets/statistiques-dvf) (Etalab, data.gouv.fr), computed from *Demandes de valeurs foncières* (DGFiP), under the [Licence Ouverte / Open Licence v2.0](https://www.etalab.gouv.fr/licence-ouverte-open-licence/). Each row carries the source, licence and file update date (`sourceDataDate`). DVF does not cover Alsace, Moselle and Mayotte. Only sales are counted (not exchanges or building plots). This Actor is not affiliated with the French administration.

# Changelog

This Actor's version history is a separate document: https://apify.com/datacraft-studio/france-property-price-stats/changelog.md

# Actor input Schema

## `communes` (type: `array`):

Town names or INSEE codes, e.g. Lyon, Bordeaux, Paris 15e Arrondissement, 33063.

## `postcodes` (type: `array`):

Each postcode returns every town (or Paris/Lyon/Marseille district) it covers.

## `departments` (type: `array`):

Department codes for department-level statistics, e.g. 69, 75, 2A, 974.

## `epcis` (type: `array`):

9-digit SIREN of a metropole or community of communes, e.g. 200046977 (Métropole de Lyon).

## `allCommunesOfDepartments` (type: `array`):

Department codes; returns every town of each department (one charged row per town found).

## `allDepartments` (type: `boolean`):

Add every French department.

## `includeFrance` (type: `boolean`):

Add a national row for comparison.

## `monthsOfHistory` (type: `integer`):

Monthly figures included per area (also used for the trend). 0 = none.

## `minSales` (type: `integer`):

Prices based on fewer sales are hidden (sales counts are kept). Never below 5.

## `maxItems` (type: `integer`):

Maximum number of areas delivered (and charged).

## Actor input object example

```json
{
  "communes": [
    "Lyon",
    "Bordeaux"
  ],
  "allDepartments": false,
  "includeFrance": false,
  "monthsOfHistory": 12,
  "minSales": 5,
  "maxItems": 100
}
```

# Actor output Schema

## `areas` (type: `string`):

One row per area with prices per m², sales counts, trend and monthly history.

## `summary` (type: `string`):

Counts, period covered and source date.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "communes": [
        "Lyon",
        "Bordeaux"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("datacraft-studio/france-property-price-stats").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "communes": [
        "Lyon",
        "Bordeaux",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("datacraft-studio/france-property-price-stats").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "communes": [
    "Lyon",
    "Bordeaux"
  ]
}' |
apify call datacraft-studio/france-property-price-stats --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datacraft-studio/france-property-price-stats"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/39hwy6i67pLOzgFTH/builds/F5Ymi5bb9d2U0ODXN/openapi.json