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electricsheepeurope/europe-owid-dentistry-personnel-per-1000

Dentistry Personnel Per 1000 | Europe (Our World in Data) šŸ‡ŖšŸ‡ŗ 877 observations Ā· 41 Europe countries Ā· 2000–2023 Ā· Repackaged by Electric Sheep Europe TL;DR This dataset contains 877 observations of Dentistry Personnel Per 1000 data across 41 Europe countries, spanning 2000–2023. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Dentistry Personnel Per 1000 Geographic coverage 41… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepeurope/europe-owid-dentistry-personnel-per-1000.

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Dataset Card

Dentistry Personnel Per 1000 | Europe (Our World in Data)

šŸ‡ŖšŸ‡ŗ 877 observations Ā· 41 Europe countries Ā· 2000–2023 Ā· Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)

rows countries years license

TL;DR

This dataset contains 877 observations of Dentistry Personnel Per 1000 data across 41 Europe countries, spanning 2000–2023.

About the source

  • —Source: Our World in Data
  • —Publisher: Our World in Data
  • —License: cc-by-4.0
  • —Topic: Dentistry Personnel Per 1000

Geographic coverage

41 Europe countries Ā· top rows shown below, sorted by row count:

CountryRowsFirst yearLast year
AUT2420002023
BLR2420002023
BEL2420002023
POL2420002023
NOR2420002023
MDA2420002023
IRL2420002023
LTU2420002023
ISL2420002023
SVN2320002022
PRT2320002022
SVK2320002022
DEU2320002022
BGR2320002022
AND2320002023
...26 more countries

Schema

ColumnTypeDescriptionExample
country_namestring—Andorra
country_iso3string—AND
yearint64—2000
Health worker density, by type of occupation (per 10,000 population) - Dentistsfloat64—6.55

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepeurope/europe-owid-dentistry-personnel-per-1000")
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.sort_values("year")
sample.plot(x="year", y="Health worker density, by type of occupation (per 10,000 population) - Dentists")

Citation

bibtex
@misc{europe_owid_dentistry_personnel_per_1000_2023,
  title        = {Dentistry Personnel Per 1000 | Europe (Our World in Data)},
  author       = {Our World in Data},
  year         = {2023},
  url          = {https://ourworldindata.org/grapher/dentistry-personnel-per-1000},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-owid-dentistry-personnel-per-1000}}
}

License

Released under cc-by-4.0.

Original data Ā© Our World in Data. 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 2026-06-03 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/dentistry-personnel-per-1000