# UK House Prices by Region and Property Type (`scrapemint/uk-house-prices`) Actor

Average sale price, index, monthly and annual change and sales volume for any UK region from HM Land Registry's official House Price Index, split by property type, first time buyer, cash or mortgage and new build. Keyless, no browser and no proxy.

- **URL**: https://apify.com/scrapemint/uk-house-prices.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Real estate, 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/platform/actors/running/actors-in-store#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

## UK House Prices

Average sale price, house price index, monthly and annual change and sales volume for any UK region, straight from HM Land Registry's official UK House Price Index.

This is the government's own measure, not an estate agent estimate or a portal asking price. It covers the whole United Kingdom down to individual local authorities.

No login, no API key, no proxy.

### What you get

One row per region per month:

```json
{
  "region": "London",
  "regionSlug": "london",
  "month": "2026-05",
  "averagePrice": 544814,
  "housePriceIndex": 95.4,
  "percentageChangeMonth": -1.2,
  "percentageChangeYear": -3.7,
  "salesVolume": null,
  "currency": "GBP",
  "averagePriceDetached": 1138974,
  "averagePriceFirstTimeBuyer": 465145,
  "percentageChangeYearDetached": -2.9
}
```

Every row also carries the same figures split by segment: detached, semi detached, terraced, flat or maisonette, new build, existing property, first time buyer, former owner occupier, cash buyer and mortgage buyer.

### Input

| Field | Description |
| --- | --- |
| `regions` | Region slugs, e.g. `["england","london","manchester"]` |
| `mode` | `latest` (newest published month) or `history` |
| `monthFrom` / `monthTo` | `YYYY-MM`. History range. Empty history means the last 12 published months |
| `breakdowns` | Limit the per segment columns. Empty returns all |
| `maxRows` | Total rows returned (default 200) |

Region slugs are lowercase with hyphens: `united-kingdom`, `england`, `scotland`, `wales`, `northern-ireland`, `london`, `manchester`, `city-of-bristol` and so on.

### Examples

Latest month for the four nations:

```json
{ "regions": ["england","scotland","wales","northern-ireland"] }
```

Two years of London history:

```json
{ "mode": "history", "regions": ["london"], "monthFrom": "2024-06", "monthTo": "2026-05" }
```

First time buyer prices across several cities:

```json
{ "regions": ["manchester","leeds","city-of-bristol"], "breakdowns": ["FirstTimeBuyer"] }
```

### Things worth knowing

The index is published roughly two months in arrears, so the newest available month is not last month. Leaving the dates empty finds the newest month that actually has data rather than guessing from today.

**Sales volume lags further than prices**, by about five months, so recent months return `averagePrice` with `salesVolume` as `null`. That is the source, not a gap in this actor.

Not every breakdown exists at every level. The United Kingdom total has no first time buyer figure, for example, while England does. Anything the Land Registry does not publish comes back as `null` and never as a zero, so a missing figure can never be mistaken for a price of nothing.

Prices are in pounds sterling. The index is set so that January 2015 equals 100, which is why a region can show an index below 100 while prices are far above their 2015 level in cash terms.

### Who it's for

Property investors and developers comparing regions, estate agencies and portals showing local trends, mortgage and proptech dashboards, journalists and analysts tracking the UK housing market. Pairs with **US Rent and Home Price Index** for the same question in the United States.

### Pricing

Pay per region row. The first 2 rows of every run are free so you can validate the output before you pay.

# Actor input Schema

## `regions` (type: `array`):

Land Registry region slugs, e.g. \["england","london","manchester"]. Countries, regions and local authorities all work. Use lowercase with hyphens, e.g. "city-of-bristol".

## `mode` (type: `string`):

latest = the newest published month per region. history = a range of months.

## `monthFrom` (type: `string`):

YYYY-MM. History mode uses this as the start. Empty means the last 12 published months.

## `monthTo` (type: `string`):

YYYY-MM. History mode end month.

## `breakdowns` (type: `array`):

Limit the per-segment columns. Choices: Detached, SemiDetached, Terraced, FlatMaisonette, NewBuild, ExistingProperty, FirstTimeBuyer, FormerOwnerOccupier, Cash, Mortgage. Empty returns all of them.

## `maxRows` (type: `integer`):

Total rows to return.

## Actor input object example

```json
{
  "regions": [
    "scotland",
    "wales",
    "manchester"
  ],
  "mode": "latest",
  "monthFrom": "2025-01",
  "monthTo": "2026-05",
  "breakdowns": [
    "Detached",
    "FirstTimeBuyer"
  ],
  "maxRows": 200
}
```

# Actor output Schema

## `rows` (type: `string`):

Average sale price, index, monthly and annual change and sales volume for each requested UK region and month.

# 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 = {
    "regions": [
        "united-kingdom",
        "england",
        "london"
    ],
    "breakdowns": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/uk-house-prices").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 = {
    "regions": [
        "united-kingdom",
        "england",
        "london",
    ],
    "breakdowns": [],
}

# Run the Actor and wait for it to finish
run = client.actor("scrapemint/uk-house-prices").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 '{
  "regions": [
    "united-kingdom",
    "england",
    "london"
  ],
  "breakdowns": []
}' |
apify call scrapemint/uk-house-prices --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapemint/uk-house-prices"
        }
    }
}

```

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/rJS9DTGdTNSJOY4wP/builds/Tuj4TN3Ck66AwGQQw/openapi.json