electricsheepeurope/europe-who-adolescent-mortality-rate-mortado
Adolescent mortality rate (per 1 000 age specific cohort) | Europe (WHO GHO) πͺπΊ 13,158 observations Β· 43 Europe countries Β· 1990β2023 Β· Repackaged by Electric Sheep Europe TL;DR This dataset contains 13,158 observations of Adolescent mortality rate (per 1 000 age specific cohort) data across 43 Europe countries, spanning 1990β2023, covering 1 distinct indicators. About the source Source: WHO Global Health Observatory Publisher: World Healthβ¦ See the full description on the dataset page: https://huggingface.co/datasets/electricsheepeurope/europe-who-adolescent-mortality-rate-mortado.
Adolescent mortality rate (per 1 000 age specific cohort) | Europe (WHO GHO)
πͺπΊ 13,158 observations Β· 43 Europe countries Β· 1990β2023 Β· Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)
TL;DR
This dataset contains 13,158 observations of Adolescent mortality rate (per 1 000 age specific cohort) data across 43 Europe 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: Adolescent mortality rate (per 1 000 age specific cohort)
Geographic coverage
43 Europe countries Β· top rows shown below, sorted by row count:
Indicators (sample)
MORTADO
Schema
Disaggregation dimensions
The following columns provide disaggregation dimensions:
- `dim1_type` (1 unique values):
SEX - `dim1` (3 unique values):
SEX_BTSX,SEX_FMLE,SEX_MLE - `dim2_type` (1 unique values):
AGEGROUP - `dim2` (3 unique values):
AGEGROUP_YEARS10-14,AGEGROUP_YEARS10-19,AGEGROUP_YEARS15-19
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepeurope/europe-who-adolescent-mortality-rate-mortado")
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"] == "MORTADO"]
.sort_values("year"))
sample.plot(x="year", y="value_numeric", title="MORTADO")Pivot to country Γ year matrix
matrix = (df[df["indicator_code"] == "MORTADO"]
.pivot_table(index="year", columns="country_iso3", values="value_numeric"))
print(matrix.tail())Citation
@misc{europe_who_adolescent_mortality_rate_mortado_2023,
title = {Adolescent mortality rate (per 1 000 age specific cohort) | Europe (WHO GHO)},
author = {World Health Organization},
year = {2023},
url = {https://www.who.int/data/gho},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-who-adolescent-mortality-rate-mortado}}
}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 2026-05-29 via the Electric Sheep pipeline. Source URL: https://www.who.int/data/gho
