Canadian retail-trade intelligence (monthly)
Monthly Canadian retail-trade intelligence from Statistics Canada (table 20-10-0056-01, 2017-01 onward): province/territory/CMA x month sales momentum (MoM, YoY, 3-month-annualized) with a documented 0-100 retail strength score and provincial ranks, expanding/contracting and 12-month record-high flags, plus — on the Canada rows — an additive decomposition of total YoY growth into the 9 top-level NAICS retail groups' contribution points (they sum exactly to the published total), the top growth driver, ex-auto and ex-auto-and-gasoline headline variants, and industry breadth. Caveats: values in thousands of dollars (kept verbatim); the latest month is preliminary and may be revised. Statistics Canada Open Licence (commercial reuse allowed); source: Statistics Canada.
- Source
- Statistics Canada
- Rows
- 1,955
- Columns
- 22
- Source cadence
- Monthly
- Last refreshed
- Sep 26, 2026
- Theme
- economy
| Column | Type | Description |
|---|---|---|
| month | string | Reference month: first day of the month, ISO date. (unit: ISO date) |
| country_code | string | ISO alpha-3 country code (CAN for every row). (unit: ISO 3166-1 alpha-3) |
| geo_name | string | Provider-verbatim geography: Canada, a province, a territory, or one of the Montréal, Toronto and Vancouver CMAs. |
| geo_code | string | Short geography code (CA/NL/PE/NS/NB/QC/MTL/ON/TOR/MB/SK/AB/BC/VAN/YT/NT/NU); primary join key with month. |
| is_national | integer | 1 for the Canada aggregate row, 0 otherwise. (unit: binary) |
| sales_thousands | float | Total retail sales, seasonally adjusted, as published: in thousands of Canadian dollars (multiply by 1,000 for dollar amounts). Non-negative float; genuine upstream gaps are missing, never zero-filled; the latest month is preliminary and may be revised. (unit: thousands of CAD, seasonally adjusted) |
| mom_pct | float | Month-over-month percent change in sales. (unit: percent) |
| yoy_pct | float | Year-over-year percent change in sales. (unit: percent) |
| ann_3m_pct | float | 3-month change annualized: ((sales_t / sales_{t-3}) ^ 4 - 1) * 100. (unit: percent, annualized) |
| retail_strength_score | float | Documented 0-100 composite: 100 * (0.50 * min-max(winsorized YoY, +/-30pp) + 0.30 * min-max(winsorized 3m-annualized, +/-30pp) + 0.20 * min-max(winsorized MoM, +/-15pp)), min-maxed within each month across the 17 geographies. Higher = stronger retail momentum. (unit: 0-100 score) |
| retail_rank | integer | Per-month rank of retail_strength_score across the 10 provinces (1 = strongest). Null for territories, CMAs and the Canada row. (unit: rank) |
| expanding_flag | integer | 1 when mom_pct is positive. (unit: binary) |
| contracting_flag | integer | 1 when mom_pct is negative. (unit: binary) |
| record_high_12m_flag | integer | 1 when sales equal the trailing-12-month maximum (inclusive). (unit: binary) |
| top_driver_industry | string | NAICS code of the top-level industry contributing most to total YoY growth (Canada rows only; deterministic: earliest NAICS code wins ties). (unit: NAICS code) |
| top_driver_industry_label | string | Provider-verbatim label of the top driver industry (Canada rows only). |
| top_driver_contrib_pp | float | The top driver's contribution to total YoY growth, in percentage points (Canada rows only). (unit: pp) |
| ex_auto_yoy_pct | float | Year-over-year percent change of retail sales excluding motor vehicle and parts dealers [441] (Canada rows only). (unit: percent) |
| ex_gasauto_yoy_pct | float | Year-over-year percent change of retail sales excluding motor vehicle and parts dealers [441] and gasoline stations and fuel vendors [457] (Canada rows only). (unit: percent) |
| industry_breadth_share | float | Share of the 9 top-level industries with YoY growth above zero (Canada rows only; null when fewer than 7 have data). (unit: share) |
| source_table | string | StatCan product ID behind the row (20100056). |
| row_hash | string | Deterministic 16-hex row hash of geo_code + month (idempotency). |
First 10 sample rows — a preview, not the complete dataset.
| month | country_code | geo_name | geo_code | is_national | sales_thousands | mom_pct | yoy_pct | ann_3m_pct | retail_strength_score | retail_rank | expanding_flag | contracting_flag | record_high_12m_flag | top_driver_industry | top_driver_industry_label | top_driver_contrib_pp | ex_auto_yoy_pct | ex_gasauto_yoy_pct | industry_breadth_share | source_table | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017-01-01 | CAN | Canada | CA | 1 | 50,417,235 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | 6be1fcbb3551660c |
| 2017-01-01 | CAN | Newfoundland and Labrador | NL | 0 | 800,919 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | c87262663b81cca2 |
| 2017-01-01 | CAN | Prince Edward Island | PE | 0 | 199,509 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | 7968c7cb8e29fcdc |
| 2017-01-01 | CAN | Nova Scotia | NS | 0 | 1,338,447 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | 049b2bbf14bfb0a5 |
| 2017-01-01 | CAN | New Brunswick | NB | 0 | 1,049,815 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | 2c2c46a43a81ee36 |
| 2017-01-01 | CAN | Quebec | QC | 0 | 10,709,589 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | 8d6dc49c69c68d90 |
| 2017-01-01 | CAN | Montréal, Quebec | MTL | 0 | 4,846,808 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | 9542014dd029f6f0 |
| 2017-01-01 | CAN | Ontario | ON | 0 | 18,742,688 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | eb4a47069466ff1e |
| 2017-01-01 | CAN | Toronto, Ontario | TOR | 0 | 8,071,889 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | a7144e28475f8ba7 |
| 2017-01-01 | CAN | Manitoba | MB | 0 | 1,749,096 | — | — | — | — | — | 0 | 0 | 0 | — | — | — | — | — | — | 20100056 | e3d8f3437b7315af |
- Current
20260926T095300Z-cc1608127291 · sha256 cc1608127291…
1,955 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/statcan_retail_trade_intel/ca_retail_trade_intel_monthly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/statcan_retail_trade_intel/ca_retail_trade_intel_monthly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/statcan_retail_trade_intel/ca_retail_trade_intel_monthly
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20260926T095300Z-cc1608127291 and its content hash, so readers get exactly the data you used.
Statistics Canada. (2026). Canadian retail-trade intelligence (monthly) [Data set, snapshot 20260926T095300Z-cc1608127291, sha256 cc1608127291]. Datazimuts. Retrieved 2026-09-26, from https://datazimuts.com/en/datasets/statcan_retail_trade_intel/ca_retail_trade_intel_monthly?snapshot=20260926T095300Z-cc1608127291
@misc{dz_statcan_retail_trade_intel_ca_retail_tra_cc160812,
title = {{Canadian retail-trade intelligence (monthly)}},
author = {{Statistics Canada}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/statcan_retail_trade_intel/ca_retail_trade_intel_monthly?snapshot=20260926T095300Z-cc1608127291}},
note = {Snapshot 20260926T095300Z-cc1608127291, sha256 cc1608127291bf94611518f9fd3c3a0b805b14a98eb95a6d3f373a550bf9ecf0; accessed 2026-09-26}
}Embed a table or a chart
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