electricsheepeurope/europe-who-alcohol-0000001400
Alcohol, recorded per capita (15+) consumption (in litres of pure alcohol), by beverage type | Europe (WHO GHO) πͺπΊ 9,866 observations Β· 40 Europe countries Β· 1960β2022 Β· Repackaged by Electric Sheep Europe TL;DR This dataset contains 9,866 observations of Alcohol, recorded per capita (15+) consumption (in litres of pure alcohol), by beverage type data across 40 Europe countries, spanning 1960β2022, covering 1 distinct indicators. About theβ¦ See the full description on the dataset page: https://huggingface.co/datasets/electricsheepeurope/europe-who-alcohol-0000001400.
Alcohol, recorded per capita (15+) consumption (in litres of pure alcohol), by beverage type | Europe (WHO GHO)
πͺπΊ 9,866 observations Β· 40 Europe countries Β· 1960β2022 Β· Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)
TL;DR
This dataset contains 9,866 observations of Alcohol, recorded per capita (15+) consumption (in litres of pure alcohol), by beverage type data across 40 Europe countries, spanning 1960β2022, covering 1 distinct indicators.
About the source
- Source: WHO Global Health Observatory
- Publisher: World Health Organization
- License: cc-by-4.0
- Topic: Alcohol, recorded per capita (15+) consumption (in litres of pure alcohol), by beverage type
Geographic coverage
40 Europe countries Β· top rows shown below, sorted by row count:
Indicators (sample)
SA_0000001400
Schema
Disaggregation dimensions
The following columns provide disaggregation dimensions:
- `dim1_type` (1 unique values):
ALCOHOLTYPE - `dim1` (5 unique values):
ALCOHOLTYPE_SA_BEER,ALCOHOLTYPE_SA_SPIRITS,ALCOHOLTYPE_SA_TOTAL,ALCOHOLTYPE_SA_WINE,ALCOHOLTYPE_SA_OTHER_ALCOHOL
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepeurope/europe-who-alcohol-0000001400")
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"] == "SA_0000001400"]
.sort_values("year"))
sample.plot(x="year", y="value_numeric", title="SA_0000001400")Pivot to country Γ year matrix
matrix = (df[df["indicator_code"] == "SA_0000001400"]
.pivot_table(index="year", columns="country_iso3", values="value_numeric"))
print(matrix.tail())Citation
@misc{europe_who_alcohol_0000001400_2022,
title = {Alcohol, recorded per capita (15+) consumption (in litres of pure alcohol), by beverage type | Europe (WHO GHO)},
author = {World Health Organization},
year = {2022},
url = {https://www.who.int/data/gho},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-who-alcohol-0000001400}}
}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
