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ts-arena/electricity

electricity Time series dataset: electricity Dataset Summary Property Value Frequency 1H Validation samples 1 Train samples 1 Test samples 1 Supported Tasks Time series forecasting Anomaly detection Classification (if applicable) Languages N/A (numerical data) Dataset Structure Data Instances { "item_id": "example_series_0", "start": "2020-01-01T00:00:00", "target":… See the full description on the dataset page: https://huggingface.co/datasets/ts-arena/electricity.

sourceHugging Faceunknownupdated 9mo agoView on Hugging Face
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Dataset Card

electricity

Time series dataset: electricity

Dataset Description

  • Homepage:
  • Repository:
  • Paper:
  • License: Unknown

Dataset Summary

PropertyValue
Frequency1H
Validation samples1
Train samples1
Test samples1

Supported Tasks

  • Time series forecasting
  • Anomaly detection
  • Classification (if applicable)

Languages

N/A (numerical data)

Dataset Structure

Data Instances

json
{
    "item_id": "example_series_0",
    "start": "2020-01-01T00:00:00",
    "target": [1.0, 2.0, 3.0, ...],
    "frequency": "1H",
    "metadata": "{...}"
}

Data Fields

FieldTypeDescription
item_idstringUnique identifier for the time series
startstringISO 8601 timestamp of the first observation
targetlist[float]Time series values
frequencystringPandas frequency string (e.g., '1H', '1D')
featdynamicreallist[list[float]]Time-varying covariates (optional)
featstaticcatlist[int]Static categorical features (optional)
metadatastringJSON string with normalization params, etc.

Data Splits

SplitExamples
validation1
train1
test1

Dataset Creation

Source Data

Download Method: unknown

Preprocessing

  1. 1.Data downloaded from original source
  2. 2.Missing values filled using forward-fill method
  3. 3.Standard normalization applied (mean=0, std=1)
  4. 4.Split into train/validation/test sets (70/10/20)
  5. 5.Converted to Parquet format for efficient streaming

Considerations for Using the Data

Social Impact

This dataset is intended for research purposes in time series forecasting.

Limitations

  • Normalization parameters are computed on training data only
  • Missing value handling may introduce artifacts
  • Temporal alignment assumes regular intervals

Additional Information

Citation

bibtex
@misc{unknown_dataset,
    title = {Unknown Dataset},
    url = {},
    year = {2024},
}

Contributions

This dataset was processed and uploaded as part of the TS Arena benchmarking project.


Generated automatically by TS Arena streaming pipeline on 2026-01-03