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electricsheepasia/asia-owid-natural-disasters-by-yearly-impact

Natural Disasters By Yearly Impact | Asia (Our World in Data) 🌏 1,684 observations · 47 Asia countries · 1900–2025 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 1,684 observations of Natural Disasters By Yearly Impact data across 47 Asia countries, spanning 1900–2025. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Natural Disasters By Yearly Impact Geographic… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-owid-natural-disasters-by-yearly-impact.

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Dataset Card

Natural Disasters By Yearly Impact | Asia (Our World in Data)

🌏 1,684 observations · 47 Asia countries · 1900–2025 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years license

TL;DR

This dataset contains 1,684 observations of Natural Disasters By Yearly Impact data across 47 Asia countries, spanning 1900–2025.

About the source

Geographic coverage

47 Asia countries · top rows shown below, sorted by row count:

CountryRowsFirst yearLast year
JPN10219002025
CHN9819022025
IND9219002025
PHL8819052025
TUR8119002025
IDN8119132025
IRN8019032025
BGD7819042025
TWN6919042025
PAK6919092025
KOR6419362025
NPL5819342025
VNM5519522025
LKA5419572025
AFG5019542025
...32 more countries

Schema

ColumnTypeDescriptionExample
country_namestring—Afghanistan
country_iso3string—AFG
yearint64—1954
Smallint64—0
Mediumint64—0
Largeint64—1
Unknownint64—0

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-owid-natural-disasters-by-yearly-impact")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python
indonesia = df[df["country_iso3"] == "IDN"]

Time-series for a single indicator

python
sample = df.sort_values("year")
sample.plot(x="year", y="Small")

Citation

bibtex
@misc{asia_owid_natural_disasters_by_yearly_impact_2025,
  title        = {Natural Disasters By Yearly Impact | Asia (Our World in Data)},
  author       = {Our World in Data},
  year         = {2025},
  url          = {https://ourworldindata.org/grapher/natural-disasters-by-yearly-impact},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-owid-natural-disasters-by-yearly-impact}}
}

License

Released under cc-by-4.0.

Original data © Our World in Data. When using this dataset, please cite both the original source above and the Electric Sheep Asia repackaging.

About Electric Sheep

Electric Sheep Asia is part of the Electric Sheep mission: a unified, ML-ready data layer for Asia on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepasia


Provenance: ingested 2026-06-06 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/natural-disasters-by-yearly-impact