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electricsheepasia/asia-who-uhc-service-coverage-sub-index-on-noncommunicable-diseases

UHC Service Coverage sub-index on noncommunicable diseases | Asia (WHO GHO) 🌏 1,152 observations Β· 48 Asia countries Β· 2000–2023 Β· Repackaged by Electric Sheep Asia TL;DR This dataset contains 1,152 observations of UHC Service Coverage sub-index on noncommunicable diseases data across 48 Asia countries, spanning 2000–2023, covering 1 distinct indicators. About the source Source: WHO Global Health Observatory Publisher: World Health… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-who-uhc-service-coverage-sub-index-on-noncommunicable-diseases.

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Dataset Card

UHC Service Coverage sub-index on noncommunicable diseases | Asia (WHO GHO)

🌏 1,152 observations Β· 48 Asia countries Β· 2000–2023 Β· Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 1,152 observations of UHC Service Coverage sub-index on noncommunicable diseases data across 48 Asia countries, spanning 2000–2023, covering 1 distinct indicators.

About the source

Geographic coverage

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

CountryRowsFirst yearLast year
AFG2420002023
ARE2420002023
ARM2420002023
AZE2420002023
BGD2420002023
BHR2420002023
BRN2420002023
BTN2420002023
CHN2420002023
CYP2420002023
GEO2420002023
IDN2420002023
IND2420002023
IRN2420002023
IRQ2420002023
...33 more countries

Indicators (sample)

  • β€”UHC_SCI_NCD

Schema

ColumnTypeDescriptionExample
indicator_codeobjectβ€”UHC_SCI_NCD
country_iso3objectβ€”AFG
who_regionobjectβ€”EMR
yearint64β€”2000
value_numericfloat64β€”41.0
value_lowobjectβ€”β€”
value_highobjectβ€”β€”
value_displayobjectβ€”41
last_updatedobjectβ€”2025-12-05T11:39:13.277+01:00

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-who-uhc-service-coverage-sub-index-on-noncommunicable-diseases")
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[df["indicator_code"] == "UHC_SCI_NCD"]
          .sort_values("year"))
sample.plot(x="year", y="value_numeric", title="UHC_SCI_NCD")

Pivot to country Γ— year matrix

python
matrix = (df[df["indicator_code"] == "UHC_SCI_NCD"]
          .pivot_table(index="year", columns="country_iso3", values="value_numeric"))
print(matrix.tail())

Citation

bibtex
@misc{asia_who_uhc_service_coverage_sub_index_on_noncommunicable_diseases_2023,
  title        = {UHC Service Coverage sub-index on noncommunicable diseases | 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-uhc-service-coverage-sub-index-on-noncommunicable-diseases}}
}

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