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) πͺπΊ 596 observations Β· 8 Europe countries Β· 2002β2019 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 2002β2019, covering 1 distinct indicators. About theβ¦ See the full description on the dataset page: https://huggingface.co/datasets/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)
πͺπΊ 596 observations Β· 8 Europe countries Β· 2002β2019 Β· Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)
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 2002β2019, covering 1 distinct indicators.
About the source
- Source: WHO Global Health Observatory
- Publisher: World Health Organization
- License: cc-by-4.0
- 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:
Indicators (sample)
sba
Schema
Disaggregation dimensions
The following columns provide disaggregation dimensions:
- `dim1_type` (6 unique values):
DHSMICSGEOREGION,EDUCATIONLEVEL,RESIDENCEAREATYPE,WEALTHQUINTILE,WEALTHDECILE - `dim1` (162 unique values):
DHSMICSGEOREGION_ALBRHS200201,DHSMICSGEOREGION_ALBRHS200202,DHSMICSGEOREGION_ALBRHS200203,EDUCATIONLEVEL_PRLM,EDUCATIONLEVEL_SHLM
Usage
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
germany = df[df["country_iso3"] == "DEU"]Time-series for a single indicator
sample = (df[df["indicator_code"] == "sba"]
.sort_values("year"))
sample.plot(x="year", y="value_numeric", title="sba")Pivot to country Γ year matrix
matrix = (df[df["indicator_code"] == "sba"]
.pivot_table(index="year", columns="country_iso3", values="value_numeric"))
print(matrix.tail())Citation
@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
