# FAO Agricultural Statistics Intelligence (`wakey7dev/fao-agriculture-normalizer`) Actor

Extract FAO agricultural data — crop production, livestock, trade, food security. Global food system research, policy analysis, market intelligence.

- **URL**: https://apify.com/wakey7dev/fao-agriculture-normalizer.md
- **Developed by:** [Chris Wakefield](https://apify.com/wakey7dev) (community)
- **Categories:** Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

![Chris The Dev](https://raw.githubusercontent.com/chriswakefield87/appstore-screenshot-translator/main/assets/actor-banner.png)

## FAO Agriculture Production Normalizer

Clean, analysis-ready crop-production data from the Food and Agriculture Organization (FAOSTAT). Retrieve production, yield, or harvested-area observations for one or more countries and commodities, with normalized labels, consistent units, deduplication, and year-over-year change calculations.

### Why this Actor

FAOSTAT data is authoritative but its coded dimensions and inconsistent raw exports slow down research. This Actor resolves FAO codes to human-readable names, standardizes units, preserves provenance, and adds comparable year-over-year percentage changes.

### Input parameters

| Parameter | Type | Description | Default |
|---|---|---|---|
| `areaCodes` | string | Comma-separated FAO area codes (`231` United States, `229` United Kingdom, `68` France, `5000` World) | `231,229` |
| `itemCodes` | string | Comma-separated item codes (`15` Wheat, `56` Maize, `27` Rice) | `15,56` |
| `elementCodes` | string | `5510` Production, `5419` Yield, `5312` Area harvested | `5510` |
| `startYear` / `endYear` | integer | Inclusive year range | `2018` / `2023` |
| `maxResults` | integer | Maximum records | `100` |

### Example input

```json
{"areaCodes":"231,229","itemCodes":"15,56","elementCodes":"5510","startYear":2018,"endYear":2023,"maxResults":100}
```

### Example output

```json
{"area":"United States of America","item":"Wheat","element":"Production","year":2023,"value":49500.0,"unit":"tonnes","previousYearValue":...,"yearOverYearPercent":...}
```

### Use cases

- Agricultural market intelligence and commodity research
- Food-security and sustainability dashboards
- Supply-chain and procurement analysis
- Academic and policy research
- Country and crop benchmarking

### Data source and attribution

Source: [FAOSTAT](https://www.fao.org/faostat/en/#data/QCL), accessed through the [DBnomics FAO provider](https://api.db.nomics.world/v22/series/FAO/QCL). FAO data is subject to the source's licensing and revision policies.

The Actor stores full records in the default dataset, a readable table in the `OUTPUT` key, and machine-readable run metrics in `STATS`.

# Actor input Schema

## `areaCodes` (type: `string`):

Comma-separated FAO area codes. Examples: 231 United States, 229 United Kingdom, 68 France, 79 Germany, 5000 World.

## `itemCodes` (type: `string`):

Comma-separated FAO crop/item codes. Examples: 15 Wheat, 56 Maize, 27 Rice, 486 Bananas, 1717 Cereals Total.

## `elementCodes` (type: `string`):

Comma-separated FAO element codes: 5510 Production, 5419 Yield, 5312 Area harvested.

## `startYear` (type: `integer`):

First year, inclusive.

## `endYear` (type: `integer`):

Last year, inclusive.

## `maxResults` (type: `integer`):

Maximum normalized records to return.

## Actor input object example

```json
{
  "areaCodes": "231,229",
  "itemCodes": "15,56",
  "elementCodes": "5510",
  "startYear": 2018,
  "endYear": 2023,
  "maxResults": 100
}
```

# Actor output Schema

## `results` (type: `string`):

Full normalized observations.

## `summary` (type: `string`):

Human-readable formatted result table.

## `stats` (type: `string`):

Machine-readable run statistics.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("wakey7dev/fao-agriculture-normalizer").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("wakey7dev/fao-agriculture-normalizer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call wakey7dev/fao-agriculture-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,wakey7dev/fao-agriculture-normalizer"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/hS5lNEoXaVUtHm0fL/builds/lSaAe8dVtyGvHVova/openapi.json