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electricsheepeurope/europe-owid-private-investment-in-artificial-intelligence-cset

Private Investment In Artificial Intelligence Cset | Europe (Our World in Data) πŸ‡ͺπŸ‡Ί 335 observations Β· 38 Europe countries Β· 2016–2025 Β· Repackaged by Electric Sheep Europe TL;DR This dataset contains 335 observations of Private Investment In Artificial Intelligence Cset data across 38 Europe countries, spanning 2016–2025. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Private Investment In… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepeurope/europe-owid-private-investment-in-artificial-intelligence-cset.

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Dataset Card

Private Investment In Artificial Intelligence Cset | Europe (Our World in Data)

πŸ‡ͺπŸ‡Ί 335 observations Β· 38 Europe countries Β· 2016–2025 Β· Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)

rows countries years license

TL;DR

This dataset contains 335 observations of Private Investment In Artificial Intelligence Cset data across 38 Europe countries, spanning 2016–2025.

About the source

  • β€”Source: Our World in Data
  • β€”Publisher: Our World in Data
  • β€”License: cc-by-4.0
  • β€”Topic: Private Investment In Artificial Intelligence Cset

Geographic coverage

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

CountryRowsFirst yearLast year
AUT1020162025
BEL1020162025
DNK1020162025
DEU1020162025
CZE1020162025
CHE1020162025
UKR1020162025
POL1020162025
NOR1020162025
NLD1020162025
ESP1020162025
EST1020162025
FIN1020162025
FRA1020162025
GBR1020162025
...23 more countries

Schema

ColumnTypeDescriptionExample
country_namestringβ€”Albania
country_iso3stringβ€”ALB
yearint64β€”2016
Estimated funding raised by privately held AI companies - Field: Allint64β€”2258017

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepeurope/europe-owid-private-investment-in-artificial-intelligence-cset")
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="Estimated funding raised by privately held AI companies - Field: All")

Citation

bibtex
@misc{europe_owid_private_investment_in_artificial_intelligence_cset_2025,
  title        = {Private Investment In Artificial Intelligence Cset | Europe (Our World in Data)},
  author       = {Our World in Data},
  year         = {2025},
  url          = {https://ourworldindata.org/grapher/private-investment-in-artificial-intelligence-cset},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-owid-private-investment-in-artificial-intelligence-cset}}
}

License

Released under cc-by-4.0.

Original data Β© 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 2026-06-07 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/private-investment-in-artificial-intelligence-cset