European Fisheries Catches
Fishery catches for every European country, split by species group - total, freshwater & diadromous fish, shellfish and finfish - in live-weight tonnes across all fishing areas. Cleaned from Eurostat's fisheries statistics into one tidy annual panel: the catch-volume signal for seafood traders, aquaculture firms and marine-policy researchers.
- Source
- Eurostat
- Licence
- Redistributable open data
- Updates
- Annual
- Data through
- 2024-01-01
- Quality
- QC clean · 0 failures
- Format
- Apache Parquet + dictionary
Safe to train on
Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.
What's included
- Fishery catches by species group - total, freshwater/diadromous, shellfish, finfish
- Live-weight tonnes, all fishing areas, per country
- Every European country, annual, 2000→present
- Buyers: seafood traders, aquaculture firms, marine-policy NGOs
- Source: Eurostat (CC-BY-4.0) - EU/EFTA + candidate geos
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| zone | str | Country (ISO-2) | 100.0% | 27 |
| ts | timestamp (UTC) | Year | 100.0% | 25 |
| indicator | str | Catches - total / freshwater & diadromous / shellfish / finfish | 100.0% | 4 |
| value | float | Catches (tonnes live weight) | 100.0% | 2,337 |
| unit | str | Unit | 100.0% | 1 |
| res_min | int | Native resolution (annual) | 100.0% | 1 |
Sample & preview
Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: Eurostat (redistributable open data; attribution passes through - see our Licence).
Don't trust screenshots - drop the sample into your notebook right now.
import pandas as pd df = pd.read_parquet("european-fisheries_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
Coverage: 27 zones
AL · BE · BG · CY · DE · DK · EE · EL · ES · FI · FR · HR · IE · IS · IT · LT · LV · MT · NL · NO · PL · PT · RO · SE · SI · TR · UK
Related datasets
Agri Positioning Matrix (crop condition × COT)
Physical crop reality vs paper positioning: USDA Good+Excellent condition momentum joined to CFTC speculative-positioning z-score per crop, weekly, across 8 crops - corn, soybeans, wheat, cotton, rice, oats (all with both condition and the dominant CFTC futures market) plus barley and sorghum (condition only, no listed futures). Crops deteriorating while funds are net-short flags short-squeeze setups in food commodities.
EU CAP Subsidy Flows
Common Agricultural Policy expenditure, cleaned to analysis-ready Parquet: EUR paid per EU member state x CAP instrument (direct payments, market measures, rural development) x year, 2003-2022. Fully aggregated (member-state level, no beneficiary individuals) - the GDPR-safe view of where CAP money goes. Source: DG AGRI 'Financing the CAP' indicators.
European Agricultural Output Prices
The real output-price index of Europe's major crops - cereals, wheat, barley, grain maize, industrial crops and oilseeds - deflated to 2020=100, per country, annual. Cleaned from Eurostat's agricultural price statistics into one tidy panel: the farm-gate price signal, in real terms, that agri-commodity traders, food manufacturers and ag-lenders track. Distinct from our global crop-production volumes - this is PRICE, not tonnage.