Datasets:
File size: 3,657 Bytes
7e6785f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 | ---
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).
|