yohou.datasets¶
Remote time series dataset fetchers and related utilities.
User guide: See the Core Concepts section for data format details.
Loaders¶
Each function downloads data from Monash/Zenodo (CC BY 4.0) and returns a sklearn.utils.Bunch with a .frame attribute containing a polars.DataFrame with a "time" column. Data is cached locally after the first download.
| Name | Description |
|---|---|
fetch_dominick |
Fetch the Dominick dataset from Monash/Zenodo. |
fetch_electricity_demand |
Fetch the Australian Electricity Demand dataset from Monash/Zenodo. |
fetch_hospital |
Fetch the Hospital dataset from Monash/Zenodo. |
fetch_kdd_cup |
Fetch the KDD Cup 2018 air quality dataset from Monash/Zenodo. |
fetch_pedestrian_counts |
Fetch the Melbourne Pedestrian Counts dataset from Monash/Zenodo. |
fetch_sunspot |
Fetch the Sunspot dataset (without missing values) from Monash/Zenodo. |
fetch_tourism_monthly |
Fetch the Tourism Monthly dataset from Monash/Zenodo. |
fetch_tourism_quarterly |
Fetch the Tourism Quarterly dataset from Monash/Zenodo. |
fetch_air_quality_classification |
Fetch a categorical air quality dataset derived from KDD Cup 2018. |
fetch_demand_classification |
Fetch a categorical electricity demand dataset from Monash/Zenodo. |
Utilities¶
| Name | Description |
|---|---|
clear_data_home |
Delete all the content of the data home cache. |
get_data_home |
Return the path of the yohou data directory. |
parse_tsf |
Parse a Monash .tsf file into a wide polars DataFrame. |
Synthetic generators¶
Parameterized generators that create synthetic time series with all three exogenous feature types (X_actual, X_future, X_forecast). No download required.
| Name | Description |
|---|---|
make_exogenous_regression |
Generate synthetic regression data with exogenous features. |
make_exogenous_classification |
Generate synthetic classification data with exogenous features. |