Agent-curated quarterly intelligence from Statistics Canada's keyless Web Data Service: tourism demand (millions of CAD, current prices, unadjusted) decomposed into domestic demand and tourism exports (foreign demand) across 15 tourism products (table 36100230, 1986-Q1 -> present). Fail-loud demand==domestic+foreign identity gate; foreign share and foreign-led-growth flag; year-over-year momentum; recovery index vs the same quarter of 2019 (=100); a documented 0-100 tourism-momentum score ranked per quarter as momentum_rank; record-high and below-2019 flags; quarter-level context (total demand, aggregate foreign share, top product, positive-momentum breadth). Trailing 40 quarters published. Primary key: product_key + quarter. Cadence: quarterly.

Source: Canadian tourism demand intelligence (agent-curated)
Rows: 600
Columns: 25
Source cadence: Quarterly
Last refreshed: Sep 29, 2026
Theme: economy

Column	Type	Description
quarter	string	Quarter start (ISO date); the quarter's demand window. (unit: date)
country_code	string	Constant CAN.
product	string	Canonical tourism product name (StatCan verbatim).
product_key	string	Short product key (join key).
demand_mcad	float	Tourism demand, millions of CAD (current prices, unadjusted). (unit: MCAD)
domestic_mcad	float	Domestic tourism demand, millions of CAD. (unit: MCAD)
foreign_mcad	float	Tourism exports (foreign/visitor demand), millions of CAD. (unit: MCAD)
foreign_share_pct	float	100 * foreign_mcad / demand_mcad. (unit: %)
domestic_share_pct	float	100 * domestic_mcad / demand_mcad. (unit: %)
yoy_pct	float	Year-over-year % change of demand_mcad (same quarter a year earlier; null for the panel's first year). (unit: %)
momentum_mcad	float	Absolute YoY change of demand_mcad, millions of CAD. (unit: MCAD)
demand_index_2019q	float	Recovery index: demand vs the same quarter of 2019 (=100). (unit: index)
recovery_gap_pp	float	demand_index_2019q - 100 (pp above/below the 2019 baseline). (unit: pp)
tourism_momentum_score	float	0-100 per-quarter score: 0.60 min-max of winsorized (+/-40) yoy_pct + 0.40 min-max of winsorized (+/-60) recovery_gap_pp across the 15 products. (unit: 0-100)
momentum_rank	integer	Deterministic per-quarter rank: tourism_momentum_score desc, yoy_pct desc, product_key asc. (unit: rank)
record_high	integer	1 when demand_mcad is the product's max over the published 10-year panel. (unit: 0/1)
below_2019	integer	1 when demand_index_2019q < 100. (unit: 0/1)
foreign_led	integer	1 when foreign YoY growth exceeds headline YoY growth and is positive. (unit: 0/1)
quarter_total_mcad	float	Quarter-level context: total tourism demand across the 15 products. (unit: MCAD)
quarter_foreign_share_pct	float	Quarter-level context: aggregate foreign share of demand. (unit: %)
quarter_top_product	string	Quarter-level context: product_key with the largest demand that quarter.
quarter_breadth_pct	float	Quarter-level context: share of the 15 products with positive yoy_pct. (unit: %)
asof_quarter	string	Latest complete quarter in the panel. (unit: date)
source_table	string	StatCan table PID behind the row.
row_hash	string	Deterministic 16-hex row hash.

First 10 sample rows — a preview, not the complete dataset.

quarter	country_code	product	product_key	demand_mcad	domestic_mcad	foreign_mcad	foreign_share_pct	domestic_share_pct	yoy_pct	momentum_mcad	demand_index_2019q	recovery_gap_pp	tourism_momentum_score	momentum_rank	below_2019	foreign_led	quarter_total_mcad	quarter_foreign_share_pct	quarter_top_product	quarter_breadth_pct	asof_quarter	source_table	row_hash
2016-07-01	CAN	Accommodation	accommodation	4,965	3,005	1,960	39.48	60.52	8.81	402	80.2	-19.8	45.87	6	1	1	37,862	26.64	air	86.7	2026-04-01	36100230	0171c0444f66080f
2016-07-01	CAN	Passenger air transport	air	5,915	4,074	1,841	31.12	68.88	6.4	356	80.3	-19.7	39.31	11	1	1	37,862	26.64	air	86.7	2026-04-01	36100230	36d0854a0a538478
2016-07-01	CAN	Interurban, charter and tour bus transport	bus	311	176	135	43.41	56.59	-0.32	-1	106.9	6.9	54.42	2	0	1	37,862	26.64	air	86.7	2026-04-01	36100230	fb1917125f741e57
2016-07-01	CAN	Convention fees	convention	255	157	98	38.43	61.57	8.97	21	75.2	-24.8	39.99	10	1	1	37,862	26.64	air	86.7	2026-04-01	36100230	1fc83218ced6dbf8
2016-07-01	CAN	Food and beverage services	food_beverage	4,743	3,352	1,391	29.33	70.67	6.94	308	87.1	-12.9	49.45	4	1	1	37,862	26.64	air	86.7	2026-04-01	36100230	18856ea913ff2aea
2016-07-01	CAN	Vehicle fuel	fuel	2,359	2,110	249	10.56	89.44	-5.56	-139	86.9	-13.1	14.78	15	1	0	37,862	26.64	air	86.7	2026-04-01	36100230	2fe7eddc50d74b14
2016-07-01	CAN	Other products	other_products	5,207	3,530	1,677	32.21	67.79	3.66	184	89.8	-10.2	43.77	7	1	1	37,862	26.64	air	86.7	2026-04-01	36100230	11c8f2ff35d33019
2016-07-01	CAN	Other tourism products	other_tourism	5,886	4,743	1,143	19.42	80.58	3.97	225	87.4	-12.6	41.57	8	1	1	37,862	26.64	air	86.7	2026-04-01	36100230	52eae731ac4baf2e
2016-07-01	CAN	Other transportation	other_transport	352	204	148	42.05	57.95	1.15	4	90.7	-9.3	38.06	13	1	1	37,862	26.64	air	86.7	2026-04-01	36100230	c43cfe0e8eedc4a1
2016-07-01	CAN	Pre-trip expenses	pre_trip	1,086	1,086	0	0	100	3.92	41	86.7	-13.3	40.57	9	1	0	37,862	26.64	air	86.7	2026-04-01	36100230	8bedc830f0537822

Sep 29, 2026Current
20260929T030051Z-7e88adabce69 · sha256 7e88adabce69…
600 rows · first snapshot

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/ca_tourism_demand_intel/ca_tourism_demand_quarterly" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/ca_tourism_demand_intel/ca_tourism_demand_quarterly").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/ca_tourism_demand_intel/ca_tourism_demand_quarterly

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.

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Pinned to snapshot 20260929T030051Z-7e88adabce69 and its content hash, so readers get exactly the data you used.

APA

Canadian tourism demand intelligence (agent-curated). (2026). Canadian tourism demand intelligence (quarterly) [Data set, snapshot 20260929T030051Z-7e88adabce69, sha256 7e88adabce69]. Datazimuts. Retrieved 2026-09-30, from https://datazimuts.com/en/datasets/ca_tourism_demand_intel/ca_tourism_demand_quarterly?snapshot=20260929T030051Z-7e88adabce69

BibTeX

@misc{dz_ca_tourism_demand_intel_ca_tourism_deman_7e88adab,
  title        = {{Canadian tourism demand intelligence (quarterly)}},
  author       = {{Canadian tourism demand intelligence (agent-curated)}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/ca_tourism_demand_intel/ca_tourism_demand_quarterly?snapshot=20260929T030051Z-7e88adabce69}},
  note         = {Snapshot 20260929T030051Z-7e88adabce69, sha256 7e88adabce697e5bb643acc8349b25260440153112d714d6bebe6c5805619912; accessed 2026-09-30}
}

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Canadian tourism demand intelligence (quarterly)

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