Canadian manufacturing-pulse intelligence (monthly)
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Monthly Canadian manufacturing-pulse intelligence from Statistics Canada's Monthly Survey of Manufacturing: total sales for the 13 provinces and territories (table 16-10-0048-01) plus the Canada industry breakdown — the headline total, durable and non-durable aggregates, and the 21 NAICS 3-digit subsectors (table 16-10-0047-01), all seasonally adjusted. Sales momentum (MoM, 3-month-annualized, YoY), 60-month growth z-scores, shares of the national total, and a documented 0-100 manufacturing-pulse score with per-month ranks for provinces and subsectors. An additive decomposition attributes headline YoY growth to the 21 subsectors (they sum exactly to the published total), with the top driver, industry breadth, and the durable-vs-non-durable cycle gap on the headline rows. Caveats: thousands of Canadian dollars (kept verbatim); every series starts 1992-01; the territories publish with intermittent upstream gaps (kept null, never filled); the latest months are preliminary and may be revised. Statistics Canada Open Licence (commercial reuse allowed); source: Statistics Canada.
- Source
- Statistics Canada
- Rows
- 15,355
- Columns
- 28
- 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) |
| segment_kind | string | 'province' for the 13 provinces/territories (table 16-10-0048-01), 'industry' for the Canada industry breakdown (table 16-10-0047-01). |
| segment_code | string | Segment key: provider-verbatim geography for provinces; 'total' for the headline 'Manufacturing [31-33]' aggregate, 'durable' / 'nondurable' for the publisher's own aggregates, else the NAICS 3-digit subsector code. Primary join key with segment_kind + month. |
| segment_label | string | Provider-verbatim segment label (geography name, or the NAICS industry label). |
| is_headline | integer | 1 for the Canada headline aggregate row ('Manufacturing [31-33]'), 0 otherwise. (unit: binary) |
| is_leaf | integer | 1 for the peer sets that carry pulse scores and ranks: the 13 provinces and the 21 NAICS subsectors. 0 for the headline and the durable/non-durable aggregates. (unit: binary) |
| sales_thousands | float | Sales of goods manufactured (shipments), 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) |
| share_of_total_pct | float | The segment's sales as a share of the Canada headline total that month (the industry table's headline series doubles as the national denominator for provinces). Null when the headline total is missing. (unit: percent) |
| sales_mom_pct | float | Month-over-month percent change in sales. (unit: percent) |
| sales_ann_3m_pct | float | 3-month change in sales annualized: ((sales_t / sales_{t-3}) ^ 4 - 1) * 100. (unit: percent, annualized) |
| sales_yoy_pct | float | Year-over-year percent change in sales. (unit: percent) |
| growth_z_60m | float | Z-score of sales_yoy_pct against its trailing 60-month mean/std (minimum 24 observations; null when the window std is 0). Positive = growing faster than its own 5-year norm. (unit: z-score) |
| manufacturing_pulse_score | float | Documented 0-100 composite: 100 * (0.50 * min-max(winsorized sales_yoy_pct, +/-15pp) + 0.50 * min-max(winsorized sales_ann_3m_pct, +/-10pp)), min-maxed within each month across the peer set (the 13 provinces, or the 21 subsectors). Higher = stronger sales momentum versus peers this month. Null for aggregates and the headline. (unit: 0-100 score) |
| manufacturing_pulse_rank | integer | Per-month rank of manufacturing_pulse_score within the peer set (1 = strongest pulse). Null for aggregates and the headline. (unit: rank) |
| surging_flag | integer | 1 when growth_z_60m exceeds +1.0 (YoY growth more than one std above its 5-year norm). (unit: binary) |
| slumping_flag | integer | 1 when growth_z_60m is below -1.0. (unit: binary) |
| expanding_flag | integer | 1 when sales_mom_pct is positive. (unit: binary) |
| contracting_flag | integer | 1 when sales_mom_pct is negative. (unit: binary) |
| record_high_12m_flag | integer | 1 when sales equal the trailing-12-month maximum (inclusive). (unit: binary) |
| contribution_yoy_pp | float | The segment's additive contribution to headline sales YoY growth, in percentage points: (sales_{g,t} - sales_{g,t-12}) / sales_{total,t-12} * 100. The 21 subsectors' contributions sum exactly to the headline YoY rate (identity-gated); so do durable + non-durable. Null for province rows. (unit: pp) |
| top_driver_industry | string | Month-level national context, repeated on every row of the month: NAICS code of the subsector contributing most to headline sales YoY. Deterministic: earliest NAICS code wins ties. (unit: NAICS code) |
| top_driver_industry_label | string | Month-level national context, repeated on every row: provider-verbatim label of the top driver subsector. |
| top_driver_contrib_pp | float | Month-level national context, repeated on every row: the top driver's contribution to headline sales YoY growth, in percentage points. (unit: pp) |
| industry_breadth_share | float | Month-level national context, repeated on every row: share of the 21 subsectors with sales YoY growth above zero among those with data (null when fewer than 15 have data). (unit: share) |
| durable_nondurable_gap_pp | float | Month-level national context, repeated on every row: durable-goods YoY minus non-durable-goods YoY — the goods-cycle divergence gauge. Positive = durables outrunning non-durables. (unit: pp) |
| source_table | string | StatCan product IDs behind the row (16100048 provinces + 16100047 industries). |
| row_hash | string | Deterministic 16-hex row hash of segment_kind + segment_code + month (idempotency). |
First 10 sample rows — a preview, not the complete dataset.
| month | country_code | segment_kind | segment_code | segment_label | is_headline | is_leaf | sales_thousands | share_of_total_pct | sales_mom_pct | sales_ann_3m_pct | sales_yoy_pct | growth_z_60m | manufacturing_pulse_score | manufacturing_pulse_rank | surging_flag | slumping_flag | expanding_flag | contracting_flag | record_high_12m_flag | contribution_yoy_pp | top_driver_industry | top_driver_industry_label | top_driver_contrib_pp | industry_breadth_share | durable_nondurable_gap_pp | source_table | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1992-01-01 | CAN | industry | total | Manufacturing [31-33] | 1 | 0 | 22,442,286 | 100 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | 086ae6e6f818f6a3 |
| 1992-01-01 | CAN | industry | durable | Durable goods industries | 0 | 0 | 11,711,538 | 52.185 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | 2012836666150cf0 |
| 1992-01-01 | CAN | industry | nondurable | Non-durable goods industries | 0 | 0 | 10,730,748 | 47.815 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | f3996141d3835803 |
| 1992-01-01 | CAN | industry | 311 | Food manufacturing [311] | 0 | 1 | 3,253,229 | 14.496 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | 7545c6854dc351b8 |
| 1992-01-01 | CAN | industry | 312 | Beverage and tobacco product manufacturing [312] | 0 | 1 | 729,328 | 3.25 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | b5d096d8ea8824b2 |
| 1992-01-01 | CAN | industry | 313 | Textile mills [313] | 0 | 1 | 222,785 | 0.993 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | bc2da17427227aaf |
| 1992-01-01 | CAN | industry | 314 | Textile product mills [314] | 0 | 1 | 148,489 | 0.662 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | 32e8d99bf4da0a6f |
| 1992-01-01 | CAN | industry | 315 | Apparel manufacturing [315] | 0 | 1 | 497,186 | 2.215 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | a40571ebab1ada8f |
| 1992-01-01 | CAN | industry | 316 | Leather and allied product manufacturing [316] | 0 | 1 | 74,071 | 0.33 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | ca31daac667c87f8 |
| 1992-01-01 | CAN | industry | 321 | Wood product manufacturing [321] | 0 | 1 | 1,069,139 | 4.764 | — | — | — | — | — | — | 0 | 0 | 0 | 0 | 0 | — | — | — | — | — | — | 16100048+16100047 | 21124584a804bf03 |
- Current
20260926T170219Z-3a327ba7b3db · sha256 3a327ba7b3db…
15,355 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/statcan_manufacturing_intel/ca_manufacturing_pulse_monthly" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/statcan_manufacturing_intel/ca_manufacturing_pulse_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_manufacturing_intel/ca_manufacturing_pulse_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 20260926T170219Z-3a327ba7b3db and its content hash, so readers get exactly the data you used.
APA
Statistics Canada. (2026). Canadian manufacturing-pulse intelligence (monthly) [Data set, snapshot 20260926T170219Z-3a327ba7b3db, sha256 3a327ba7b3db]. Datazimuts. Retrieved 2026-09-26, from https://datazimuts.com/en/datasets/statcan_manufacturing_intel/ca_manufacturing_pulse_monthly?snapshot=20260926T170219Z-3a327ba7b3db
BibTeX
@misc{dz_statcan_manufacturing_intel_ca_manufactu_3a327ba7,
title = {{Canadian manufacturing-pulse intelligence (monthly)}},
author = {{Statistics Canada}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/statcan_manufacturing_intel/ca_manufacturing_pulse_monthly?snapshot=20260926T170219Z-3a327ba7b3db}},
note = {Snapshot 20260926T170219Z-3a327ba7b3db, sha256 3a327ba7b3db36dfa126496d6b164badbcfad3151af66b0aa0c00b01514d9401; accessed 2026-09-26}
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