> ## Documentation Index > Fetch the complete documentation index at: https://docs.northaxiumdata.ca/llms.txt > Use this file to discover all available pages before exploring further. # How to Track Political Contributions > Query 6.2M+ Elections Canada reviewed contributions to track political financing by party, contributor, province, and election cycle. The NorthAxium Data contributions API exposes the full Elections Canada reviewed contributions dataset — 6.2M+ records covering contributions to parties, candidates, electoral district associations, leadership contestants, and nomination contestants from 2000 to present. ## Prerequisites * A NorthAxium Data API key ([get one here](https://northaxiumdata.ca) or use the [free demo key](/authentication)) * Python 3.8+ with the `requests` library installed (`pip install requests`) ## Search contributions by party and year The most common starting point — aggregate contributions to a party in a given election year. ```python theme={null} import requests API_KEY = "your_api_key_here" BASE_URL = "https://api.northaxiumdata.ca/api/v1" headers = {"X-API-Key": API_KEY} # get contributions to a party in a specific year params = { "party": "Conservative", # partial match on party name "year": 2021, "limit": 20, } response = requests.get( f"{BASE_URL}/contributions", headers=headers, params=params ) data = response.json() print(f"Total contributions matching filter: {data['meta']['total']}") print() for c in data["data"]: print(f"Contributor: {c['contributor_name']} ({c.get('contributor_province', 'N/A')})") print(f"Party: {c['political_party']}") print(f"Amount: ${c['monetary_amount']:,.2f}") print(f"Type: {c['contributor_type']}") print("---") ``` ## Get party-level contribution statistics Aggregate total contributions and donor counts by party across a full election cycle. ```python theme={null} params = { "group_by": "party", "sum_field": "monetary_amount", } response = requests.get( f"{BASE_URL}/contributions/stats", headers=headers, params=params ) stats = response.json()["data"] print("Contributions by party (all time):") for row in stats[:8]: print(f" {row['party']}: ${row['total']:,.0f} from {row['count']:,} contributions") ``` ## Track a contributor's full donation history Look up how much a named individual or organization has contributed and to which parties. ```python theme={null} # search for a contributor by name contributor = "Pierre Poilievre" response = requests.get( f"{BASE_URL}/contributors/{contributor}", headers=headers ) profile = response.json()["data"] print(f"Contributor: {profile['contributor_name']}") print(f"Total donated: ${profile['total_amount']:,.2f} across {profile['contribution_count']} contributions") print("\nBy party:") for row in profile["party_breakdown"]: print(f" {row['party']}: ${row['total']:,.2f} ({row['count']} contributions)") print("\nBy year:") for row in profile["year_breakdown"]: print(f" {row['year']}: ${row['total']:,.2f}") ``` ## Compare contributions by province Break down contributions to a specific party by province of origin. ```python theme={null} params = { "group_by": "province", "sum_field": "monetary_amount", } response = requests.get( f"{BASE_URL}/contributions/stats", headers=headers, params=params ) stats = response.json()["data"] print("Contributions by province (all parties, all time):") for row in stats: if row.get("province"): print(f" {row['province']}: ${row['total']:,.0f} from {row['count']:,} contributions") ``` ## Filter by contributor type Elections Canada tracks several contributor types. Filter to corporate contributions to identify organizational donors. ```python theme={null} # contributor_type options: Individuals, Corporations, # Businesses / Commercial organizations, Unincorporated organizations or associations params = { "contributor_type": "Corporations", "year": 2019, "min_amount": 1000, "limit": 20, } response = requests.get( f"{BASE_URL}/contributions", headers=headers, params=params ) data = response.json() print(f"Corporate contributions over $1,000 in 2019: {data['meta']['total']}") for c in data["data"]: print(f" {c['contributor_name']} → {c['political_party']}: ${c['monetary_amount']:,.2f}") ``` ## What's happening here **`party` parameter** — partial match. `"Liberal"` matches `Liberal Party of Canada`, `Alberta Liberal Party`, and similar. For a precise match, use the full party name string from the stats endpoint. **`contributor_type`** — exact match on Elections Canada's classification. The most common values are `Individuals` (by far the largest group at \~99% of records) and `Corporations`. Use the stats endpoint grouped by `contributor_type` to see the full breakdown. **`electoral_event`** — exact match on the Elections Canada event label, e.g. `44th General Election`, `43rd General Election`. Use this to isolate contributions within a specific election campaign rather than a calendar year. **Contributor profiles** — the profile endpoint uses partial name matching. For common names, you may get multiple contributors in the result. The `year_breakdown` in the profile is useful for understanding whether a contributor's giving pattern changed around a specific election. **Data coverage note** — Elections Canada publishes reviewed contributions on a per-election cycle basis. The most recent election cycle may not yet be reviewed and published. Check the [Coverage](/data-coverage) page for the current data state. ## Next steps Full parameter reference for the contributions endpoint Aggregated contribution history for any named contributor Cross-reference donors with lobbying records Ask Claude to analyse contributions in natural language