Datasets:

VALORISIMMO
/

valoris-french-real-estate-prices

Error code:   FeaturesError
Exception:    ParserError
Message:      Error tokenizing data. C error: Expected 1 fields in line 5, saw 7

Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 4195, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2533, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2711, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2249, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
                  for batch_idx, df in enumerate(csv_file_reader):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
                  return self.get_chunk()
                         ^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
                  return self.read(nrows=size)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1923, in read
                  ) = self._engine.read(  # type: ignore[attr-defined]
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
                  chunks = self._reader.read_low_memory(nrows)
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
                File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
                File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
              pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 5, saw 7

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French Real Estate Prices — VALORIS Observatory

Aggregated real estate median prices (€/m²) computed from the French open data source DVF (Demandes de Valeurs Foncières) published by DGFiP.

Covers 93 departments and their communes of metropolitan France (excluding Alsace-Moselle departments 57, 67, 68 — local Livre Foncier system).

🔗 Interactive visualization & drill-down: valoris-immo.fr/observatoire

🏠 Publisher homepage: valoris-immo.fr

📊 Dataset Overview

Dimension	Coverage
Temporal	2020 – 2025 (annual series)
Spatial	93 departments + ~35,000 communes
Property types	`appartement`, `maison`, `tous`
Metrics	Median €/m², transaction count, year-over-year evolution
Source	DVF — Demandes de Valeurs Foncières (DGFiP)

📁 Files

`france.csv` — National-level series

Median prices aggregated at country level, by property type and year.

Columns: annee, type_bien, prix_median_m2, nb_transactions, evolution_1an_pct

`departements.json` — Per-department breakdown

Detailed structure with metadata + per-department medians by type and year.

{
  "meta": {
    "generated_at": "2026-04-22T06:29:33Z",
    "source": "VALORIS — valoris-immo.fr",
    "licence": "Licence Ouverte 2.0",
    "annees": [2020, 2021, 2022, 2023, 2024, 2025]
  },
  "data": [
    {
      "code_departement": "75",
      "nom_departement": "Paris",
      "type_bien": "appartement",
      "annee": 2025,
      "prix_median_m2": 9420,
      "nb_transactions": 24180,
      "evolution_1an_pct": -2.8
    }
  ]
}

`communes/*.json` — Commune-level drill-down (93 files)

One JSON per department (e.g. 75.json for Paris), each containing all communes with their year-by-year medians by property type.

🧪 Methodology

Source: bi-annual DVF feed from DGFiP (transactions 2020-01-01 → 2025-12-31)
Cleaning:
- P5 / P95 outlier removal per commune × type × year
- Minimum 10 transactions threshold (below → marked as indisponible)
- Bulk sales excluded (nature_mutation = 'Vente en l'état futur d'achèvement' filtered)
Aggregation: median €/m² (not mean — more robust to outliers)
Evolution: (prix_N - prix_N-1) / prix_N-1 × 100

🔍 Example use cases

Regional real estate market analysis
Price prediction model training (feature: code_commune, type_bien, annee)
Geospatial visualization (choropleth maps)
Economic studies on French residential market 2020-2025
Tax & inheritance valuation baselines

🐍 Quick load (Python)

from datasets import load_dataset

# Load national-level data
ds = load_dataset("VALORISIMMO/valoris-french-real-estate-prices", data_files="france.csv")
print(ds["train"].to_pandas().head())

Or with pandas directly:

import pandas as pd

df = pd.read_csv("hf://datasets/VALORISIMMO/valoris-french-real-estate-prices/france.csv")

📜 License & Attribution

Upstream source: DGFiP — Licence Ouverte 2.0
This dataset: etalab-2.0 (Licence Ouverte 2.0) — attribution required

Citation suggestion:

VALORIS (2026). French Real Estate Prices — VALORIS Observatory (DVF 2020-2025).
Hugging Face Datasets. https://huggingface.co/datasets/VALORISIMMO/valoris-french-real-estate-prices
Source: DGFiP — Demandes de Valeurs Foncières (Licence Ouverte 2.0)

🌐 About VALORIS

VALORIS is a French residential real estate valuation service combining three convergent methods:

DVF comparables — real transactions from the present dataset
Revenue capitalization — ANIL rental data × DVF-observed yield rates
Callon method — professional reference grid

Explore the methodology: valoris-immo.fr/methodologie

🙏 Credits

Data source: DGFiP — data.gouv.fr/fr/datasets/demandes-de-valeurs-foncieres
Aggregation & cleaning: VALORIS team
Interactive visualization: valoris-immo.fr/observatoire

🔗 Related publications & identifiers

DOI (Zenodo) : 10.5281/zenodo.19704026 — academic citation, EU academic repository
figshare mirror : figshare.com/articles/dataset/32084997
data.gouv.fr reuse : observatoire-prix-immobiliers-valoris — official French open data portal
Kaggle mirror : valoris/french-real-estate-prices-dvf

📖 Citation

VALORIS (2026). French Real Estate Prices — VALORIS Observatory (DVF 2020-2025). Zenodo. https://doi.org/10.5281/zenodo.19704026 Wikidata: Q139545252 Hugging Face: VALORISIMMO/valoris-french-real-estate-prices Source: DGFiP — Demandes de Valeurs Foncières (Licence Ouverte 2.0)

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