# Canada Economic Data: Prices, Housing, Jobs and GDP (`scrapemint/canada-economic-data`) Actor

Monthly Canadian statistics from Statistics Canada: consumer price index, new housing prices, housing starts, employment and GDP, for Canada or by province and city. Keyless, no browser and no proxy.

- **URL**: https://apify.com/scrapemint/canada-economic-data.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Business, News
- **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

## Canada Economic Data

Monthly Canadian statistics straight from Statistics Canada: consumer prices, new housing prices, housing starts, employment and GDP. For Canada as a whole, or broken down by province and city.

This is the government's own data, not a third party aggregator.

No login, no API key, no proxy.

### What you get

One row per series per geography per month:

```json
{
  "dataset": "housingPrices",
  "label": "New housing price index",
  "geography": "Ontario",
  "referencePeriod": "2026-06-01",
  "value": 117.8,
  "unit": "index, 2016 = 100",
  "productId": 18100205
}
```

### Datasets

| Key | Series | Unit |
| --- | --- | --- |
| `cpi` | Consumer price index | index, 2002 = 100 |
| `housingPrices` | New housing price index | index, 2016 = 100 |
| `housingStarts` | Housing starts | units |
| `employment` | Labour force characteristics | persons or percent |
| `gdp` | GDP at basic prices by industry | chained 2017 dollars |

### Input

| Field | Description |
| --- | --- |
| `datasets` | Which series to pull, e.g. `["cpi","housingPrices"]` |
| `geographies` | Names to match, e.g. `["Canada"]` or `["Ontario","Quebec"]` |
| `periods` | How many recent months per series and geography |
| `maxRows` | Total rows returned (default 200) |

### Examples

Latest headline figures for Canada:

```json
{ "datasets": ["cpi","housingPrices","housingStarts"], "geographies": ["Canada"] }
```

A year of housing prices by province:

```json
{ "datasets": ["housingPrices"], "geographies": ["Ontario","British Columbia","Alberta"], "periods": 12 }
```

### Things worth knowing

Geography matching is partial by design, so asking for `Ontario` also returns the metro areas that carry Ontario in their name, such as the Ontario part of Ottawa-Gatineau. Ask for `Canada` if you only want the national figure.

Each series is pinned to its headline total. The housing index, for example, returns house and land combined rather than the separate house only and land only measures.

Statistics Canada suppresses some figures for confidentiality and returns them as empty. Those come back as `null` and never as a zero, so a suppressed housing start count cannot be read as a month when nothing was built.

Tables publish on their own schedule, so the newest month can differ between series. GDP typically runs one month behind the price and housing figures.

### Who it's for

Analysts and journalists tracking the Canadian economy, property investors comparing provinces, fintech and proptech dashboards, and anyone who needs Canadian figures without a subscription data terminal. Pairs with **US Rent and Home Price Index**, **UK House Prices** and **Europe House Prices** for the same questions elsewhere.

### Pricing

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

# Actor input Schema

## `datasets` (type: `array`):

Which series to pull. Choices: cpi, housingPrices, housingStarts, employment, gdp.

## `geographies` (type: `array`):

Names to match, e.g. \["Canada"], \["Ontario","Quebec"] or \["Toronto"]. Matching is partial, so "Ontario" also picks up Ontario sub regions. Leave empty for every geography the table publishes.

## `periods` (type: `integer`):

How many recent reference periods to return per series and geography. These tables are monthly.

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

Total rows to return.

## Actor input object example

```json
{
  "datasets": [
    "cpi",
    "employment"
  ],
  "geographies": [
    "Ontario",
    "British Columbia"
  ],
  "periods": 1,
  "maxRows": 200
}
```

# Actor output Schema

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

Consumer price index, new housing prices, housing starts, employment and GDP by geography and month, each with its unit, product and vector id and a link back to the Statistics Canada table.

# 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 = {
    "datasets": [
        "cpi",
        "housingPrices",
        "housingStarts"
    ],
    "geographies": [
        "Canada"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/canada-economic-data").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 = {
    "datasets": [
        "cpi",
        "housingPrices",
        "housingStarts",
    ],
    "geographies": ["Canada"],
}

# Run the Actor and wait for it to finish
run = client.actor("scrapemint/canada-economic-data").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 '{
  "datasets": [
    "cpi",
    "housingPrices",
    "housingStarts"
  ],
  "geographies": [
    "Canada"
  ]
}' |
apify call scrapemint/canada-economic-data --silent --output-dataset

```

## MCP server setup

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

```

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/54bboqBjKG2BeMth4/builds/cwF253leOPCCDJfMW/openapi.json