# NL Vehicle Registration Cohorts — by Make/Model, Per Record (`nexgensignal/nl-vehicle-registration-cohort-records`) Actor

RDW Netherlands vehicle register (m9d7-ebf2) as clean, per-record registration cohorts — registered-vehicle counts by vehicle type, make, trade name and first-admission date. No licence plate or owner data. CC0, $0.05 per record.

- **URL**: https://apify.com/nexgensignal/nl-vehicle-registration-cohort-records.md
- **Developed by:** [NexGen Signal](https://apify.com/nexgensignal) (community)
- **Categories:** Business, Developer tools, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $33.50 / 1,000 vehicle cohort records

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## 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

## NL Vehicle Registration Cohorts — by Make/Model, Per Record

Turn the Netherlands' full vehicle-registration register into clean, per-record fleet-size cohorts — one row per (vehicle-type, make, trade-name, first-admission-date) group with a registered-vehicle count, ready to size registered fleets without ever touching a licence plate or owner.

Each source row becomes **one clean, flat record** with numeric fields coerced to real numbers, a stable
source-native `record_id`, and provenance stamped on every row: source, resource id, the licence notice,
the required attribution, a UTC retrieval timestamp and an interpretation caveat.

### What one record represents

The source is **`m9d7-ebf2`** — *Open Data RDW: Gekentekende\_voertuigen* on the RDW open-data portal (opendata.rdw.nl). Each record is **one registration cohort**: a distinct combination of vehicle type, make, trade name and first-admission date, together with `registered_count` — the number of registered vehicles in that cohort. The count is the *only* computed value; the licence plate (`kenteken`) and any owner field are never read, grouped, or delivered.

For each record you get a composite `record_id` built from the source-native key, the analytic columns
listed below (reproduced verbatim, numbers as numbers), and the provenance block. The group columns are `voertuigsoort` (vehicle type), `merk` (make), `handelsbenaming` (trade name) and `datum_eerste_toelating` (first-admission date, YYYYMMDD), plus `registered_count`.

### Coverage and volume

The register underlying these cohorts holds roughly 16.8 million registered vehicles; grouped to this cohort shape it yields a large, precise set of distinct cohorts. Each record is an anonymous registration fact — a count of vehicles, never a person.

**Live count: 5,037,015 grouped cohort records (pinned live via a SODA group-count); the Wave-3 index stated only '>=2,500', so this is the exact figure. The capacity line is the grouped-row count, not the 16.8M source rows.**

The Actor pages the source with keyless SODA `$query` requests ordered by the source-native key for a
stable total order, and stops as soon as your **Maximum records** cap is met. The Actor groups server-side with a SODA `$query` (`SELECT ... , count(*) GROUP BY ...`) and never selects the plate or any owner field.

### Licence and attribution

RDW open vehicle data is published as **public-domain / CC0** open government data. The full notice travels on every record:

> RDW (Netherlands Vehicle Authority) open vehicle data - CC0 / public domain. Aggregated registration counts only; the licence plate (kenteken) and any owner/holder field are never read, grouped, or delivered.

The required attribution — `RDW - Netherlands Vehicle Authority (Dienst Wegverkeer)` — travels on every record.

### Interpretation caveat

`registered_count` is the number of registered vehicles sharing the (vehicle-type, make, trade-name, first-admission-date) cohort. A count of one is an anonymous registration fact, not a person. First-admission date is the date the vehicle was first admitted to the road, not necessarily the Dutch registration date.

Values are reproduced verbatim: the Actor never rescales, re-derives or editorialises a number.

### Person-data policy

By construction this Actor reads only aggregate cohort keys and a count. The licence plate (`kenteken`) and any owner/holder field are **never in the query and never in a record** — a structural guard rejects any source row that even contains a plate/owner field. No natural-person data is processed.

### Data quality and freshness

Numeric fields are coerced from the source's string encoding into real numbers (integers where whole,
floats otherwise); genuinely missing cells are delivered as `null`, never as zero. Text is passed
through verbatim. Every run re-reads the live source, so the data is as fresh as the portal itself, and
each record's `observed_at` stamp records exactly when the row was retrieved. Delivery order is fixed by
the source-native key, so a capped sample and a later full pull agree on their overlap and a repeated
run returns rows in the same order. The `RUN_RECEIPT` reports source rows scanned and records delivered
and charged for a per-run reconciliation.

### Provenance, licensing and compliance

Every run begins with a live source-preflight: the Actor reads the exact host's `robots.txt` at runtime
and refuses to proceed if the crawl policy disallows the data path. The gate result — URL, HTTP status,
byte length and a SHA-256 of the policy — is written to the run's `RUN_RECEIPT`, so each run carries its
own audit trail. The Actor identifies itself with a transparent, non-impersonating User-Agent and never
bypasses a block, solves a challenge, or fetches through a cache or mirror. When the door is genuinely
unavailable the run fails loudly and bills nothing.

### Inputs

- **Maximum records** (`maxRecords`) — hard cap on records delivered and billed. Raise it to pull the
  full set; lower it to sample cheaply. Records arrive in a stable, source-native order.

### Output

Records land in the Actor's default dataset and export as JSON, CSV, Excel or via the Apify API. A
tabular **overview view** surfaces the most useful columns for quick inspection while the full record
retains every selected field and provenance stamp.

### Fields in detail

The record leads with `record_id` — a stable composite key drawn from the source's own grain — followed
by the analytic columns described above and closed by a provenance block: `source`, `source_dataset`
(the Socrata resource id), `licence`, `attribution`, `caveat` and `observed_at`. Every one of those
provenance fields is present on every record, so a single row is self-describing: hand it to a colleague
or a downstream system and it carries its own origin, licence and retrieval time without reference back
to this page. Because delivery is ordered by the source-native key, the same record always carries the
same `record_id` across runs, which makes the dataset safe to diff, deduplicate, or upsert into a
warehouse. Nothing in the record is computed or inferred beyond the explicit count where one is stated —
every other value is the source's own, reproduced byte-for-byte.

### Sibling Actors

This Actor is the **registration-cohort** view; its sibling **`nl-vehicle-type-approval-records`** groups the same register by a finer **type-approval / variant** key. Two distinct group shapes, two distinct products. Both are distinct from the fleet's **`eu-vehicle-co2-records`** cell, which carries CO2 emission values (not registration counts). This Actor also shares its engineering — the runtime robots gate, push-then-charge
billing and verbatim-value discipline — with the fleet's other public-data records Actors.

### Pricing

This Actor uses Apify's pay-per-event model: a flat **$0.05 per record** actually delivered to the
dataset, and nothing else — no monthly rental, no per-run base fee, no compute charge. Deliver 40
records and you pay $2.00; deliver 10,000 and you pay $500.00. Billing is wired *after* delivery — each
record is pushed first and only then does the per-record event fire — so a mid-run failure can only
ever under-charge you, never over-charge. Use **Maximum records** to cap spend precisely.

### Scaling and limits

Set **Maximum records** low to sample the leading slice cheaply, or high to pull the full set. The Actor
paginates server-side and delivers incrementally, so memory stays flat regardless of how many records
you request, and you are billed only for what is actually delivered. Because the source is a live public
API, extremely deep pagination is ultimately bounded by the source's own paging behaviour; for the vast
majority of uses — sampling, a full refresh, or a scheduled top-up — the default paging is more than
sufficient. Schedule the Actor on Apify to keep a downstream table current: each run re-reads the live
source and re-stamps `observed_at`, so a nightly or weekly run gives you a dated, reproducible snapshot.

### Typical uses

Size registered fleets by make, model and admission cohort; track how a model's registrations build over time; benchmark market share of a make within a vehicle type; or feed an automotive-market, parts-demand or residual-value model with clean cohort counts — all without any owner or plate data.

### What this Actor does not do

It does not forecast or model, does not merge multiple source tables into one record, and it never reads or delivers a licence plate or owner field. It
gives you faithful, analysis-ready records — with a provenance trail you can audit on every run.

# Actor input Schema

## `maxRecords` (type: `integer`):

Maximum records delivered and billed. You are billed only for records actually delivered. Raise it to pull the full set.

## Actor input object example

```json
{
  "maxRecords": 500
}
```

# Actor output Schema

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

The delivered NL vehicle registration cohort record.

# 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 = {
    "maxRecords": 500
};

// Run the Actor and wait for it to finish
const run = await client.actor("nexgensignal/nl-vehicle-registration-cohort-records").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 = { "maxRecords": 500 }

# Run the Actor and wait for it to finish
run = client.actor("nexgensignal/nl-vehicle-registration-cohort-records").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 '{
  "maxRecords": 500
}' |
apify call nexgensignal/nl-vehicle-registration-cohort-records --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgensignal/nl-vehicle-registration-cohort-records"
        }
    }
}

```

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/izobB571bDg9OwgGE/builds/CuCGL8X6Z9RmnMvID/openapi.json