electricsheepasia/asia-who-proportion-of-population-with-primary-reliance-on-polluting
Proportion of population with primary reliance on polluting fuels and technologies for cooking (%) | Asia (WHO GHO) π 4,692 observations Β· 46 Asia countries Β· 1990β2023 Β· Repackaged by Electric Sheep Asia TL;DR This dataset contains 4,692 observations of Proportion of population with primary reliance on polluting fuels and technologies for cooking (%) data across 46 Asia countries, spanning 1990β2023, covering 1 distinct indicators. About theβ¦ See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-who-proportion-of-population-with-primary-reliance-on-polluting.
Proportion of population with primary reliance on polluting fuels and technologies for cooking (%) | Asia (WHO GHO)
π 4,692 observations Β· 46 Asia countries Β· 1990β2023 Β· Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)
TL;DR
This dataset contains 4,692 observations of Proportion of population with primary reliance on polluting fuels and technologies for cooking (%) data across 46 Asia countries, spanning 1990β2023, covering 1 distinct indicators.
About the source
- Source: WHO Global Health Observatory
- Publisher: World Health Organization
- License: cc-by-4.0
- Topic: Proportion of population with primary reliance on polluting fuels and technologies for cooking (%)
Geographic coverage
46 Asia countries Β· top rows shown below, sorted by row count:
Indicators (sample)
PHE_HHAIR_PROP_POP_POLLUTING_FUELS
Schema
Disaggregation dimensions
The following columns provide disaggregation dimensions:
- `dim1_type` (1 unique values):
RESIDENCEAREATYPE - `dim1` (3 unique values):
RESIDENCEAREATYPE_RUR,RESIDENCEAREATYPE_TOTL,RESIDENCEAREATYPE_URB
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepasia/asia-who-proportion-of-population-with-primary-reliance-on-polluting")
df = ds["train"].to_pandas()
print(df.head())Filter to one country
indonesia = df[df["country_iso3"] == "IDN"]Time-series for a single indicator
sample = (df[df["indicator_code"] == "PHE_HHAIR_PROP_POP_POLLUTING_FUELS"]
.sort_values("year"))
sample.plot(x="year", y="value_numeric", title="PHE_HHAIR_PROP_POP_POLLUTING_FUELS")Pivot to country Γ year matrix
matrix = (df[df["indicator_code"] == "PHE_HHAIR_PROP_POP_POLLUTING_FUELS"]
.pivot_table(index="year", columns="country_iso3", values="value_numeric"))
print(matrix.tail())Citation
@misc{asia_who_proportion_of_population_with_primary_reliance_on_polluting_2023,
title = {Proportion of population with primary reliance on polluting fuels and technologies for cooking (%) | Asia (WHO GHO)},
author = {World Health Organization},
year = {2023},
url = {https://www.who.int/data/gho},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-who-proportion-of-population-with-primary-reliance-on-polluting}}
}License
Released under cc-by-4.0.
Original data Β© World Health Organization. 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 2026-05-29 via the Electric Sheep pipeline. Source URL: https://www.who.int/data/gho
