| ---
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| license: cc-by-4.0
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| annotations_creators:
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| - no-annotation
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| language_creators:
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| - found
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| multilinguality:
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| - monolingual
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| source_datasets:
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| - original
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| task_categories:
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| - time-series-forecasting
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| task_ids:
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| - univariate-time-series-forecasting
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| tags:
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| - time-series
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| - forecasting
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| - benchmark
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| - monash-time-series-forecasting-repository
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| - monash-tsf
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| - tsfile
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| - apache-tsfile
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| - modality:timeseries
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| - Time-series
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| - format:tsfile
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| pretty_name: wind_4_seconds (TsFile format)
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| configs:
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| - config_name: default
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| data_files:
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| - split: train
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| path: "*.tsfile"
|
| ---
|
|
|
| # wind_4_seconds (TsFile format)
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|
|
| A single very long daily time series representing the wind power production in MW recorded per every 4 seconds starting from 01/08/2019.
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|
|
| This repository contains the full source `.tsf` series from the Monash Time Series Forecasting Repository converted to [Apache TsFile](https://tsfile.apache.org/) format.
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|
|
| ## Summary
|
|
|
| - Source dataset: [`Monash-University/monash_tsf`](https://huggingface.co/datasets/Monash-University/monash_tsf)
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| - Original source: https://zenodo.org/record/4656032
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| - Monash subset: `wind_4_seconds`
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| - Modalities: Time-series
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| - Source series: 1
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| - Rows: 7,397,147 flattened timestamped observations
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| - Frequency: `4_seconds`
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| - Forecast horizon metadata: not specified
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| - Missing-values metadata: False
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| - Equal-length metadata: True
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| - Missing target values preserved as NaN: 0
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| - Series length range: 7,397,147 to 7,397,147
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| - TsFile output: 8 files (wind_4_seconds_1.tsfile .. wind_4_seconds_8.tsfile)
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|
|
| ## Files
|
|
|
| - `wind_4_seconds_1.tsfile`
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| - `wind_4_seconds_2.tsfile`
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| - `wind_4_seconds_3.tsfile`
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| - `wind_4_seconds_4.tsfile`
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| - `wind_4_seconds_5.tsfile`
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| - `wind_4_seconds_6.tsfile`
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| - `wind_4_seconds_7.tsfile`
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| - `wind_4_seconds_8.tsfile`
|
|
|
| ## TsFile Schema
|
|
|
| | Column | Role | TsFile type |
|
| |---|---|---|
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| | `Time` | TIME | INT64 |
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| | `series_id` | TAG | STRING |
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| | `series_name` | TAG | STRING |
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| | `start_timestamp` | TAG | STRING |
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| | `target` | FIELD | FLOAT |
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|
|
| ## Conversion Notes
|
|
|
| - Each source `.tsf` data row is stored as one TsFile device.
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| - Source `.tsf` attributes are stored as TAG columns.
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| - The `target` series values are flattened into timestamped rows and stored as a FLOAT FIELD.
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| - `Time` is synthesized from the source start timestamp and the `.tsf` frequency metadata, with millisecond precision.
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| - Large outputs may be sharded by the TsFile conversion tool; all listed shards belong to the same logical table `wind_4_seconds`.
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|
|
| ## Reading Example
|
|
|
| ```python
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| from tsfile import TsFileReader
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|
|
| reader = TsFileReader("wind_4_seconds_1.tsfile")
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| schemas = reader.get_all_table_schemas()
|
| ```
|
|
|
