README.md

---
pretty_name: Chronos datasets (extra)
annotations_creators:
- no-annotation
source_datasets:
- original
task_categories:
- time-series-forecasting
task_ids:
- univariate-time-series-forecasting
- multivariate-time-series-forecasting
license: apache-2.0
dataset_info:
- config_name: ETTh
  features:
  - name: id
    dtype: string
  - name: timestamp
    sequence: timestamp[ns]
  - name: HUFL
    sequence: float64
  - name: HULL
    sequence: float64
  - name: MUFL
    sequence: float64
  - name: MULL
    sequence: float64
  - name: LUFL
    sequence: float64
  - name: LULL
    sequence: float64
  - name: OT
    sequence: float64
  splits:
  - name: train
    num_bytes: 2229840
    num_examples: 2
  download_size: 0
  dataset_size: 2229840
- config_name: ETTm
  features:
  - name: id
    dtype: string
  - name: timestamp
    sequence: timestamp[ms]
  - name: HUFL
    sequence: float64
  - name: HULL
    sequence: float64
  - name: MUFL
    sequence: float64
  - name: MULL
    sequence: float64
  - name: LUFL
    sequence: float64
  - name: LULL
    sequence: float64
  - name: OT
    sequence: float64
  splits:
  - name: train
    num_bytes: 8919120
    num_examples: 2
  download_size: 0
  dataset_size: 8919120
- config_name: brazilian_cities_temperature
  features:
  - name: id
    dtype: string
  - name: timestamp
    sequence: timestamp[ms]
  - name: temperature
    sequence: float32
  splits:
  - name: train
    num_bytes: 109234
    num_examples: 12
  download_size: 0
  dataset_size: 109234
- config_name: spanish_energy_and_weather
  features:
  - name: timestamp
    sequence: timestamp[ms]
  - name: generation_biomass
    sequence: float64
  - name: generation_fossil_brown_coal/lignite
    sequence: float64
  - name: generation_fossil_gas
    sequence: float64
  - name: generation_fossil_hard_coal
    sequence: float64
  - name: generation_fossil_oil
    sequence: float64
  - name: generation_hydro_pumped_storage_consumption
    sequence: float64
  - name: generation_hydro_run-of-river_and_poundage
    sequence: float64
  - name: generation_hydro_water_reservoir
    sequence: float64
  - name: generation_nuclear
    sequence: float64
  - name: generation_other
    sequence: float64
  - name: generation_other_renewable
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  - name: generation_wind_onshore
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  - name: price_actual
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  - name: Barcelona_temp
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  - name: Bilbao_temp
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  - name: Madrid_temp
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  - name: Seville_temp
    sequence: float64
  - name: Valencia_temp
    sequence: float64
  - name: Barcelona_temp_min
    sequence: float64
  - name: Bilbao_temp_min
    sequence: float64
  - name: Madrid_temp_min
    sequence: float64
  - name: Seville_temp_min
    sequence: float64
  - name: Valencia_temp_min
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  - name: Barcelona_temp_max
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  - name: Madrid_temp_max
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  - name: Seville_temp_max
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  - name: Valencia_temp_max
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  - name: Barcelona_pressure
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  - name: Bilbao_pressure
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  - name: Madrid_pressure
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  - name: Seville_pressure
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  - name: Valencia_pressure
    sequence: float64
  - name: Barcelona_humidity
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  - name: Bilbao_humidity
    sequence: float64
  - name: Madrid_humidity
    sequence: float64
  - name: Seville_humidity
    sequence: float64
  - name: Valencia_humidity
    sequence: float64
  - name: Barcelona_wind_speed
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  - name: Bilbao_wind_speed
    sequence: float64
  - name: Madrid_wind_speed
    sequence: float64
  - name: Seville_wind_speed
    sequence: float64
  - name: Valencia_wind_speed
    sequence: float64
  - name: Barcelona_wind_deg
    sequence: float64
  - name: Bilbao_wind_deg
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  - name: Madrid_wind_deg
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    sequence: float64
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  - name: Barcelona_rain_1h
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  - name: Bilbao_snow_3h
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  - name: Madrid_snow_3h
    sequence: float64
  - name: Seville_snow_3h
    sequence: float64
  - name: Valencia_snow_3h
    sequence: float64
  - name: Barcelona_clouds_all
    sequence: float64
  - name: Bilbao_clouds_all
    sequence: float64
  - name: Madrid_clouds_all
    sequence: float64
  - name: Seville_clouds_all
    sequence: float64
  - name: Valencia_clouds_all
    sequence: float64
  splits:
  - name: train
    num_bytes: 18794572
    num_examples: 1
  download_size: 0
  dataset_size: 18794572
---

# Chronos datasets

Time series datasets used for training and evaluation of the [Chronos](https://github.com/amazon-science/chronos-forecasting) forecasting models.

This repository contains scripts for constructing datasets that cannot be hosted in the [main Chronos datasets repository](https://huggingface.co/datasets/autogluon/chronos_datasets) due to license restrictions.


## Usage

Datasets can be loaded using the 🤗 [`datasets`](https://huggingface.co/docs/datasets/en/index) library
```python
import datasets

ds = datasets.load_dataset("autogluon/chronos_datasets_extra", "ETTh", split="train", trust_remote_code=True)
ds.set_format("numpy")  # sequences returned as numpy arrays
```

For more information about the data format and usage please refer to [`autogluon/chronos_datasets`](https://huggingface.co/datasets/autogluon/chronos_datasets).


## License
Different datasets available in this collection are distributed under different open source licenses. Please see `ds.info.license` and `ds.info.homepage` for each individual dataset.

The dataset script provided in this repository (`chronos_datasets_extra.py`) is available under the Apache 2.0 License.