| --- |
| license: cc-by-4.0 |
| task_categories: |
| - time-series-forecasting |
| language: |
| - en |
| - es |
| tags: |
| - tsfile |
| - timeseries |
| - electricity |
| - energy |
| - spain |
| - iberia |
| - generation |
| - demand |
| - time-series |
| - renewables |
| - power-grid |
| - format:tsfile |
| pretty_name: REE Iberian Peninsula Electricity Generation (2008–2026) (TsFile) |
| size_categories: |
| - 1M<n<10M |
| configs: |
| - config_name: default |
| data_files: |
| - split: ree_data_1 |
| path: ree_data_1.tsfile |
| - split: ree_data_2 |
| path: ree_data_2.tsfile |
| - split: ree_data_3 |
| path: ree_data_3.tsfile |
| - split: ree_data_4 |
| path: ree_data_4.tsfile |
| --- |
| |
| # REE Iberian Peninsula Electricity Generation (2008–2026) (TsFile) |
|
|
| Apache TsFile version of [`daniel-dona/ree-data`](https://huggingface.co/datasets/daniel-dona/ree-data). |
|
|
| ## Overview |
|
|
| Electricity **demand and generation by source** for the Iberian Peninsula, sourced from [REE (Red Eléctrica de España)](https://www.ree.es/). Covers **2008–present** at **5-minute resolution**, fully deduplicated. |
|
|
| - **Tables:** `ree_data` |
| - **Rows:** 1,931,443 across 1 TsFile table(s). |
| - `ree_data`: 1,931,443 rows, 2007-12-31 21:00:00 → 2026-05-14 11:15:00 (UTC) |
|
|
| ## Schema (TsFile structure) |
|
|
| ### `ree_data.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `ts` timestamp as INT64 milliseconds. |
| - **TAG**: none — the table is a single device / single series. |
| - **FIELD** (37): `dem` (int64), `eol` (int64), `nuc` (int64), `gf` (int64), `car` (int64), `cc` (int64), `hid` (int64), `aut` (int64), `inter` (int64), `icb` (int64), `sol` (int64), `solFot` (int64), `solTer` (int64), `termRenov` (int64), `cogenResto` (int64), `expAnd` (int64), `expMar` (int64), `expPor` (int64), `expFra` (int64), `expTot` (int64), `impFra` (int64), `impPor` (int64), `impMar` (int64), `impAnd` (int64), `impTot` (int64), `conb` (int64), `turb` (int64), `gnhd` (int64), `bat` (int64), `consBat` (int64), `dif` (int64), `vap` (int64), `year` (int32), `month` (int32), `day` (int32), `hour` (int32), `date` (string) |
| |
| ## Conversion notes |
| |
| - The source is a single `train` split stored as two Parquet shards; both shards are concatenated into the single TsFile `ree_data.tsfile` (the split is preserved, not mixed with any other split). |
| - Time is the source `ts` timestamp (hourly, Spanish peninsular time) as INT64 milliseconds. The redundant calendar columns `year`/`month`/`day`/`hour`/`date` are kept as FIELDs. |
| - Single device (the Spanish peninsular system), no TAG column; all 38 source columns kept. |
|
|
| ## Usage |
|
|
| Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file: |
|
|
| ```python |
| from pathlib import Path |
| from tsfile import TsFileReader |
| |
| path = Path("ree_data_1.tsfile") |
| with TsFileReader(str(path)) as reader: |
| schemas = reader.get_all_table_schemas() |
| print("tables:", list(schemas)) |
| table_name = next(iter(schemas)) |
| table = schemas[table_name] |
| columns = [column.get_column_name() for column in table.get_columns()] |
| print("columns:", columns) |
| field_names = [ |
| column.get_column_name() |
| for column in table.get_columns() |
| if column.get_column_name() not in {"Time", "time"} |
| ] |
| if field_names: |
| with reader.query_table(table_name, field_names[:3], batch_size=1024) as result: |
| batch = result.read_arrow_batch() |
| if batch is not None: |
| print(batch.to_pandas().head()) |
| ``` |
|
|
| ## Source & license |
|
|
| - Original dataset: [`daniel-dona/ree-data`](https://huggingface.co/datasets/daniel-dona/ree-data) |
| - Source card title / publisher: REE Iberian Peninsula Electricity Generation (2008–2026) |
| - License: cc-by-4.0 (as declared by the original dataset). |
|
|
