{
 "id": "AkshayKarthick/india-weather-air-quality",
 "owner": "AkshayKarthick",
 "name": "india-weather-air-quality",
 "downloads": 923,
 "likes": 0,
 "last_modified": "2026-10-31T08:39:54.000Z",
 "stated_licence": "cc-by-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "time-series-forecasting",
  "tabular-regression"
 ],
 "citation": "**CC BY 4.0.** Please credit:\n- Weather data by [Open-Meteo.com](https://open-meteo.com/), with ERA5 from the Copernicus\n  Climate Change Service.\n- Air quality data by [Open-Meteo.com](https://open-meteo.com/) and the\n  Copernicus Atmosphere Monitoring Service (CAMS).\n- Indian AQI calculation and dataset by [AkshayKarthick](https://huggingface.co/AkshayKarthick).\n\nThe pipeline code (`update.py`, `naqi.py`, `cities.py`, `publish.py`) is included.\n\n```python\nfrom datasets import load_dataset\n\nweather = load_dataset(\"AkshayKarthick/india-weather-air-quality\", \"weather\", split=\"train\").to_pandas()\naq = load_dataset(\"AkshayKarthick/india-weather-air-quality\", \"air_quality\", split=\"train\").to_pandas()\ndf = weather.merge(aq, on=[\"city\", \"date\"])\n```",
 "signal": "permissive",
 "reason": "The declared licence (cc-by-4.0) is classified as permissive.",
 "revision": "a33b92e17e6a7a9a47a39ca1870ab178430caa4f",
 "stated_evidence": "https://huggingface.co/datasets/AkshayKarthick/india-weather-air-quality/blob/a33b92e17e6a7a9a47a39ca1870ab178430caa4f/README.md",
 "file_evidence": "https://huggingface.co/datasets/AkshayKarthick/india-weather-air-quality/tree/a33b92e17e6a7a9a47a39ca1870ab178430caa4f",
 "card_nc": false
}