Grape production by country: the vineyard supply tape, delivered as rows

One record owns this question and Datadory delivers it as plain typed rows: FAOSTAT - Crops and Livestock Products, the UN Food and Agriculture Organization's production account. Each row is one country-commodity-element-year cell, and grapes sit among 312 commodity items alongside wheat, maize, rice, almonds and tobacco leaf. The full domain packs roughly 4.2 million observations spanning 244 countries and territories over 64 reference years - which is why it loads into your warehouse rather than a spreadsheet.

Three elements matter for anyone sizing vineyard supply. Area harvested counts the hectares of vines picked in the reference year. Production counts tonnes of grapes harvested. Yield is the derived ratio in kilograms per hectare. All three sit on every grape country-year where an official observation exists, which is what makes the series usable for supply sizing rather than single-number rankings.

Identity is fixed by code, never by name string. Grape rows key to an item code with a UN CPC mapping; areas key to M49 codes that cover sovereign states plus aggregates such as World and the regional groupings. A panel built on those codes survives commodity renames and area re-basing intact.

The honest ranking method is to pull the latest reference year and read it, because the series is revised historically and each annual build replaces the last wholesale. What the frame fixes precisely is the geography your ranking lives in: 244 areas, M49-coded, including aggregates that sit in the same column as sovereign states.

Two rules keep a country table out of trouble. First, state the year beside any figure you quote - a series starting in 1961 means the same country can shift thousands of hectares on revision alone. Second, decide whether World belongs in the denominator before computing shares, or the aggregates will contaminate every percentage you publish.

Datadory ships the extract pre-filtered to the element columns you asked for, aggregates tagged so you can drop them with one predicate, and the reference year recorded beside every value. Your ranking arrives consistent; nobody argues about whose market numbers are current.

Reliability is graded per observation, not per dataset, and this is the part most country comparisons skip. Every row carries a provenance flag: A marks an official figure reported by the country, E an estimated value, I a value imputed by a receiving agency, X a figure contributed by an external organization, and M a missing value where no data can exist.

That flag column is what separates a defensible vintage comparison from a smooth lie. Filter on A when a client deliverable needs official figures only; treat E, I and X stretches as modelled inputs rather than history when building vintage-cycle features. Six decades of annual yield lets you separate trend from weather shocks - provided imputed runs are dropped instead of left to masquerade as continuity.

The production series measures raw agricultural output only. It carries no wine volume, no must or juice conversion, and no crush split between table grapes, drying grapes and wine grapes at the country level. A country pressing most of its crop into bottles and one shipping table grapes look identical in tonnes - which is exactly why the neighboring records exist.

OIV Statistics Database - World & Country Statistics adds the processing side: country-year vineyard area under vines, wine production and consumption in hectolitres, separate table-grape and dried-grape volumes, and export and import flows. Series reach through online yearbooks covering 1999-2014 plus thematic briefs and outlook reports referencing the 2024/2025 campaigns.

Prices are the other blind spot. The production record holds no price series at all; FAOSTAT Food and Agriculture Data adds producer price indexes and food balance sheets for more than 245 countries from 1961, which turns a tonnage story into a value story. No dedicated duty-sales or category-shipment series exists anywhere in this six-record slice - substitutes get assembled from these adjacent domains, and Datadory does the assembling.

Wine-economics analysts and quants build vintage-cycle features off the three elements - planted-area momentum, yield volatility, weather-shock separation - and restrict backtests to A-flagged cells so point-in-time discipline survives an audit.

Sales growth teams read harvested area as a territory map, because production geography predicts where buyers are next season. Yield converts the map into productivity screening: high tonnage on low yield reads as extensification, small area on high yield reads as intensive and capital-hungry - two very different pitches for irrigation, trellising or cellar equipment.

Procurement and sourcing desks watch each new reference-year drop as a trigger: a yield collapse in a sourcing region is a call worth making first, and the 1961-starting span means every desk works from the same history.

Market researchers and strategy teams pair country tonnage with the OIV hectolitre balances to say whether a market grows what it drinks, then use shelf-level product records to see which markets the grapes actually end up on.

All four jobs run off the same normalized rows - which is why they arrive keyed by year, geography and element rather than as charts you have to reverse-engineer.

Datadory handles that so the rows just arrive: elements pivoted into columns, units kept beside amounts so hectares, tonnes and kg/ha never mix, item and area codes resolved to names, provenance flags preserved as a first-class field, and aggregates tagged separately from sovereign states. Delivered daily, weekly, or hourly - your call - into your warehouse, your notebook or your dashboard.

Start with a sample: tell us the countries, years and elements you need and we will route the extract before you finish scoping the schema.

This page is one thread of a broader guide. Start with the distillers-vintners data guide for the full pooled-industry landscape, then go deeper on the neighboring workflows: global grape harvest time series for the full 1961-2024 history, grape yield per hectare data for the productivity element on its own terms, and the Datadory distillers-vintners data hub for the complete dataset index behind this page.