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electricsheepeurope/europe-owid-fish-catch-by-fishing-sector

Fish Catch By Fishing Sector | Europe (Our World in Data) 🇪🇺 2,001 observations · 29 Europe countries · 1950–2018 · Repackaged by Electric Sheep Europe TL;DR This dataset contains 2,001 observations of Fish Catch By Fishing Sector data across 29 Europe countries, spanning 1950–2018. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Fish Catch By Fishing Sector Geographic coverage… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepeurope/europe-owid-fish-catch-by-fishing-sector.

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Dataset Card

Fish Catch By Fishing Sector | Europe (Our World in Data)

🇪🇺 2,001 observations · 29 Europe countries · 1950–2018 · Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)

TL;DR

This dataset contains 2,001 observations of Fish Catch By Fishing Sector data across 29 Europe countries, spanning 1950–2018.

About the source

—Source: Our World in Data
—Publisher: Our World in Data
—License: cc-by-4.0
—Topic: Fish Catch By Fishing Sector

Geographic coverage

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

Country	Rows	First year	Last year
`ALB`	69	1950	2018
`BEL`	69	1950	2018
`BGR`	69	1950	2018
`BIH`	69	1950	2018
`DEU`	69	1950	2018
`DNK`	69	1950	2018
`ESP`	69	1950	2018
`EST`	69	1950	2018
`FIN`	69	1950	2018
`FRA`	69	1950	2018
`GBR`	69	1950	2018
`GRC`	69	1950	2018
`HRV`	69	1950	2018
`IRL`	69	1950	2018
`ISL`	69	1950	2018
...	14 more countries

Schema

Column	Type	Description	Example
`country_name`	`string`	—	`Albania`
`country_iso3`	`string`	—	`ALB`
`year`	`int64`	—	`1950`
`Industrial`	`float64`	—	`1029.1421`
`Artisanal`	`float64`	—	`120.81609`
`Subsistence`	`float64`	—	`5.865919`
`Recreational`	`float64`	—	`1.8`

Data quality & caveats

—Industrial column has 3.1% null values (filtered to non-null in this dataset).

Usage

python

from datasets import load_dataset

ds = load_dataset("electricsheepeurope/europe-owid-fish-catch-by-fishing-sector")
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="Industrial")

Citation

bibtex

@misc{europe_owid_fish_catch_by_fishing_sector_2018,
  title        = {Fish Catch By Fishing Sector | Europe (Our World in Data)},
  author       = {Our World in Data},
  year         = {2018},
  url          = {https://ourworldindata.org/grapher/fish-catch-by-fishing-sector},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-owid-fish-catch-by-fishing-sector}}
}

License

Released under cc-by-4.0.

Original data © 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 2026-06-08 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/fish-catch-by-fishing-sector