fetch_electricity_forecasting#

skrub.datasets.fetch_electricity_forecasting(data_home=None)[source]#

Fetches the electricity usage dataset (forecasting), available at skrub-data/skrub-data-files

This dataset was generated from data obtained from the ENTSOE Open Data portal under the open source license (CC-BY 4.0): https://transparencyplatform.zendesk.com/hc/article_attachments/40921869376401

and the Open Meteo Historical Weather API: https://open-meteo.com/en/docs/historical-forecast-api in accordance with the licence described: https://open-meteo.com/en/licence

This is a time-series forecasting use case. This dataset gives the total electricity load in MW in France, covering a time range from March 23, 2021 to May 31, 2025. In addition, the dataset contains weather data for several cities within France.

It can be downloaded/loaded using the sklearn.datasets.fetch_electricity_forecasting function. Size on disk: 26MB.

Parameters:

data_home: str or path, default=None: The directory where to download and unzip the files.

Returns:

PathPosixPath: The path to the electricity usage CSV file. These include the electricity load and weather data for several cities in France.

Examples

>>> import pandas as pd
>>> from pathlib import Path
>>> from skrub.datasets import fetch_electricity_forecasting
>>> path = fetch_electricity_forecasting()
>>> bayonne = pd.read_csv(path / "weather_bayonne.csv")
>>> bayonne.shape
(38688, 7)

For more detailed instructions on how to use this dataset, please refer to the example here: EuroSciPy2025