| --- |
| license: cc-by-4.0 |
| task_categories: |
| - time-series-forecasting |
| tags: |
| - tsfile |
| - timeseries |
| - time-series |
| - air-quality |
| - pm25 |
| - environment |
| - europe |
| - eea |
| - format:tsfile |
| pretty_name: EEA PM2.5 Air Quality Dataset (Europe) |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: "eea_pm25_forecasting_series*.tsfile" |
| --- |
| |
| # EEA PM2.5 Air Quality Dataset - Europe (TsFile) |
|
|
| Apache TsFile version of |
| [`cosuleabianca/eea-pm25-forecasting`](https://huggingface.co/datasets/cosuleabianca/eea-pm25-forecasting). |
|
|
| ## Overview |
|
|
| Hourly air-quality and meteorology measurements from European Environment |
| Agency (EEA) monitoring sites prepared for PM2.5 forecasting research: |
| 1,945,152 hourly rows (one per country + site + UTC hour) with PM2.5, NO2 and |
| PM10 concentrations, ERA5-style meteorology (temperature, humidity, dew |
| point, precipitation, pressure, wind components) and engineered calendar, |
| lag (1-168 h) and rolling (3-24 h) features for the three pollutants. The |
| repo's station reference table `site_metadata.csv` (EEA sampling-point |
| metadata) and `config.yaml` have no time axis and are mirrored unmodified |
| into this repository. |
|
|
| - **Rows:** 1,945,152 hourly observations; ~hundreds of EEA sites across |
| countries (sample: 2018-01-08 start). |
| - Column names containing `.`/`-` (e.g. `PM2.5`, `PM2.5_lag_1h`, |
| `StationArea_rural-nearcity`) are stored with `_` instead |
| (PM2_5, PM2_5_lag_1h, StationArea_rural_nearcity). |
|
|
| ## Schema (TsFile structure) |
|
|
| - **Time** (INT64, milliseconds) — `dt_utc` (explicit UTC offsets) as epoch. |
| - **Country, SiteNumber** (TAG, STRING) — one device per monitoring site. |
| - **dt_local, Start** (FIELD, STRING) — source wall-clock labels kept as-is. |
| - All other columns FIELD: PM2_5 / NO2 / PM10 (+ their lag/rolling features), |
| meteorology columns, calendar/cyclical features (hour, day_of_week, ... |
| season, hour_sin ...), and the station-type/area boolean flags. |
| |
| ## 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("eea_pm25_forecasting_series_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: <https://huggingface.co/datasets/cosuleabianca/eea-pm25-forecasting> |
| - License: CC-BY-4.0 |
| |
