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electricsheepeurope/europe-who-births-attended-by-skilled-health-personnel-sba

Births attended by skilled health personnel (in the two or three years preceding the survey) (%) | Europe (WHO GHO) πŸ‡ͺπŸ‡Ί 596 observations Β· 8 Europe countries Β· 2002–2019 Β· Repackaged by Electric Sheep Europe TL;DR This dataset contains 596 observations of Births attended by skilled health personnel (in the two or three years preceding the survey) (%) data across 8 Europe countries, spanning 2002–2019, covering 1 distinct indicators. About the… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepeurope/europe-who-births-attended-by-skilled-health-personnel-sba.

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Dataset Card

Births attended by skilled health personnel (in the two or three years preceding the survey) (%) | Europe (WHO GHO)

πŸ‡ͺπŸ‡Ί 596 observations Β· 8 Europe countries Β· 2002–2019 Β· Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)

rows countries years indicators license

TL;DR

This dataset contains 596 observations of Births attended by skilled health personnel (in the two or three years preceding the survey) (%) data across 8 Europe countries, spanning 2002–2019, covering 1 distinct indicators.

About the source

  • β€”Source: WHO Global Health Observatory
  • β€”Publisher: World Health Organization
  • β€”License: cc-by-4.0
  • β€”Topic: Births attended by skilled health personnel (in the two or three years preceding the survey) (%)

Geographic coverage

8 Europe countries Β· top rows shown below, sorted by row count:

CountryRowsFirst yearLast year
SRB9620052019
ALB9220022017
UKR9220052012
MKD8220052018
BLR7920052019
MNE6520052018
MDA4720052012
BIH4320062011

Indicators (sample)

  • β€”sba

Schema

ColumnTypeDescriptionExample
indicator_codeobjectβ€”sba
country_iso3objectβ€”ALB
who_regionobjectβ€”EUR
yearint64β€”2002
dim1_typeobjectβ€”DHSMICSGEOREGION
dim1objectβ€”DHSMICSGEOREGION_ALBRHS200201
value_numericfloat64β€”80.1964
value_lowfloat64β€”75.99748
value_highfloat64β€”83.81718
value_displayobjectβ€”80.2 [76.0-83.8]
last_updatedobjectβ€”2022-05-26T14:10:33+02:00

Disaggregation dimensions

The following columns provide disaggregation dimensions:

  • β€”`dim1_type` (6 unique values): DHSMICSGEOREGION, EDUCATIONLEVEL, RESIDENCEAREATYPE, WEALTHQUINTILE, WEALTHDECILE
  • β€”`dim1` (162 unique values): DHSMICSGEOREGION_ALBRHS200201, DHSMICSGEOREGION_ALBRHS200202, DHSMICSGEOREGION_ALBRHS200203, EDUCATIONLEVEL_PRLM, EDUCATIONLEVEL_SHLM

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepeurope/europe-who-births-attended-by-skilled-health-personnel-sba")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python
germany = df[df["country_iso3"] == "DEU"]

Time-series for a single indicator

python
sample = (df[df["indicator_code"] == "sba"]
          .sort_values("year"))
sample.plot(x="year", y="value_numeric", title="sba")

Pivot to country Γ— year matrix

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

Citation

bibtex
@misc{europe_who_births_attended_by_skilled_health_personnel_sba_2019,
  title        = {Births attended by skilled health personnel (in the two or three years preceding the survey) (%) | Europe (WHO GHO)},
  author       = {World Health Organization},
  year         = {2019},
  url          = {https://www.who.int/data/gho},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-who-births-attended-by-skilled-health-personnel-sba}}
}

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 Europe repackaging.

About Electric Sheep

Electric Sheep Europe is part of the Electric Sheep mission: a unified, ML-ready data layer for Europe 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/electricsheepeurope


Provenance: ingested 2026-05-31 via the Electric Sheep pipeline. Source URL: https://www.who.int/data/gho