Convert to Parquet format for datasets>=3.0 compatibility

ETTh.parquet

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+oid sha256:d9f0a073652ec2416b6ad5ec9a3fe996dca0410506562fa9eef53ab38b4f222b
+size 570693

ETTm.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9ab5c02f4279e935484a874535b7e04d0ce56968a40a26c27dbf455305773e6a
+size 2069471

README.md

@@ -1,247 +1,55 @@
 ---
-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
-    sequence: float64
-  - name: generation_solar
-    sequence: float64
-  - name: generation_waste
-    sequence: float64
-  - name: generation_wind_onshore
-    sequence: float64
-  - name: total_load_actual
-    sequence: float64
-  - name: price_actual
-    sequence: float64
-  - name: Barcelona_temp
-    sequence: float64
-  - name: Bilbao_temp
-    sequence: float64
-  - name: Madrid_temp
-    sequence: float64
-  - 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
-    sequence: float64
-  - name: Barcelona_temp_max
-    sequence: float64
-  - name: Bilbao_temp_max
-    sequence: float64
-  - name: Madrid_temp_max
-    sequence: float64
-  - name: Seville_temp_max
-    sequence: float64
-  - name: Valencia_temp_max
-    sequence: float64
-  - name: Barcelona_pressure
-    sequence: float64
-  - name: Bilbao_pressure
-    sequence: float64
-  - name: Madrid_pressure
-    sequence: float64
-  - name: Seville_pressure
-    sequence: float64
-  - name: Valencia_pressure
-    sequence: float64
-  - name: Barcelona_humidity
-    sequence: float64
-  - name: Bilbao_humidity
-    sequence: float64
-  - name: Madrid_humidity
-    sequence: float64
-  - name: Seville_humidity
-    sequence: float64
-  - name: Valencia_humidity
-    sequence: float64
-  - name: Barcelona_wind_speed
-    sequence: float64
-  - 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
-    sequence: float64
-  - name: Madrid_wind_deg
-    sequence: float64
-  - name: Seville_wind_deg
-    sequence: float64
-  - name: Valencia_wind_deg
-    sequence: float64
-  - name: Barcelona_rain_1h
-    sequence: float64
-  - name: Bilbao_rain_1h
-    sequence: float64
-  - name: Madrid_rain_1h
-    sequence: float64
-  - name: Seville_rain_1h
-    sequence: float64
-  - name: Valencia_rain_1h
-    sequence: float64
-  - name: Barcelona_snow_3h
-    sequence: float64
-  - name: Bilbao_snow_3h
-    sequence: float64
-  - 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
+task_categories:
+  - time-series-forecasting
+tags:
+  - chronos
+  - time-series
+pretty_name: Chronos Datasets Extra (Parquet)
+configs:
+  - config_name: ETTh
+    data_files: ETTh.parquet
+  - config_name: ETTm
+    data_files: ETTm.parquet
+  - config_name: brazilian_cities_temperature
+    data_files: brazilian_cities_temperature.parquet
+  - config_name: spanish_energy_and_weather
+    data_files: spanish_energy_and_weather.parquet
 ---
 
-# Chronos datasets
+# Chronos Datasets Extra (Parquet Format)
 
-Time series datasets used for training and evaluation of the [Chronos](https://github.com/amazon-science/chronos-forecasting) forecasting models.
+This dataset is a Parquet-format version of the original `autogluon/chronos_datasets_extra` dataset.
+It does not require `trust_remote_code` and works with `datasets>=3.0`.
 
-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.
+## Datasets
 
+- **ETTh**: Electricity Transformer Temperature (hourly) - 2 regions
+- **ETTm**: Electricity Transformer Temperature (minutely) - 2 regions
+- **brazilian_cities_temperature**: Monthly temperature data for Brazilian cities
+- **spanish_energy_and_weather**: Spanish energy consumption and weather data
 
 ## Usage
 
-Datasets can be loaded using the 🤗 [`datasets`](https://huggingface.co/docs/datasets/en/index) library
 ```python
-import datasets
+from datasets import load_dataset
+
+# Load ETTh dataset
+ds = load_dataset("autogluon/chronos_datasets_extra", "ETTh", split="train")
 
-ds = datasets.load_dataset("autogluon/chronos_datasets_extra", "ETTh", split="train", trust_remote_code=True)
-ds.set_format("numpy")  # sequences returned as numpy arrays
+# Load Brazilian temperature dataset
+ds = load_dataset("autogluon/chronos_datasets_extra", "brazilian_cities_temperature", split="train")
 ```
 
-For more information about the data format and usage please refer to [`autogluon/chronos_datasets`](https://huggingface.co/datasets/autogluon/chronos_datasets).
+## Original Source
 
+- ETT datasets: https://github.com/zhouhaoyi/ETDataset
+- Spanish energy: https://www.kaggle.com/datasets/nicholasjhana/energy-consumption-generation-prices-and-weather
+- Brazilian temperature: https://www.kaggle.com/datasets/volpatto/temperature-timeseries-for-some-brazilian-cities
 
 ## 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.
+The datasets have various licenses from their original sources:
+- ETT: CC BY-ND 4.0
+- Brazilian temperature: Database Contents License (DbCL) v1.0
+- Spanish energy: See original Kaggle dataset

brazilian_cities_temperature.parquet

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+size 32275

spanish_energy_and_weather.parquet

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+size 3228290