North America weekly rail freight intelligence
Usage commercial OKÀ jour
Interroger dans l’atelierLe jeu complet n’est pas encore publié — revenez après la prochaine actualisation.Télécharger l'exemple CSVTélécharger l'exemple JSONLignes d’exemple seulement (jusqu’à 20) — pas le jeu de données complet.
Weekly rail traffic panel for the United States, Canada, Mexico, and North America (AAR reporting weeks 26-38 of 2026, weeks ending 2026-07-04 .. 2026-09-26), extracted from the Association of American Railroads' public weekly press releases. Each (week_end, region) row carries observed carloads, intermodal units, totals and year-over-year percent changes, year-to-date cumulative volumes, plus derived demand intelligence: intermodal share (a consumer-goods flow proxy), trailing 4-week y/y momentum, a fixed-cut demand regime (expanding/steady/soft/contracting), and a 0-100 freight pulse score. US rows add commodity-group breadth (share of 10 groups up y/y) and the top gaining/declining commodity group. Units are railcars / containers-and-trailers per week; y/y changes are percent. Caveat: weekly traffic is noisy (holiday weeks, weather); prefer momentum_4w_pct and demand_regime over single-week spikes. A coincident freight-demand signal, not a forecast.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 52
- Colonnes
- 29
- Cadence de la source
- Hebdomadaire
- Dernière actualisation
- 1 oct. 2026
- Thème
- economy
| Colonne | Type | Description |
|---|---|---|
| week_end | string | ISO date of the Saturday ending the AAR reporting week. |
| week_number | integer | AAR reporting week number within the calendar year. |
| region | string | Region label: United States, Canada, Mexico, North America. |
| country_code | string | ISO alpha-3 country code (USA/CAN/MEX); NAM is the curator aggregate code for the AAR North America total. |
| carloads | integer | Carloads originated in the week (railcars). |
| carloads_yoy_pct | float | Year-over-year percent change of carloads vs the same week last year. (unit: percent) |
| intermodal_units | integer | Intermodal containers and trailers originated in the week. |
| intermodal_yoy_pct | float | Year-over-year percent change of intermodal units. (unit: percent) |
| total_units | integer | Carloads + intermodal units in the week. |
| total_yoy_pct | float | Year-over-year percent change of total units. Release-quoted for the US and North America; reconstructed for Canada and Mexico from the quoted carload/intermodal y/y rates (see module docstring) — those rows are flagged by total_yoy_derived. (unit: percent) |
| total_yoy_derived | boolean | True when total_yoy_pct was reconstructed from the carload/intermodal y/y rates (Canada, Mexico); False when quoted directly in the release (US, North America). |
| intermodal_share_pct | float | 100 * intermodal_units / total_units — consumer-goods flow proxy. (unit: percent) |
| ytd_total_units | integer | Year-to-date cumulative carloads + intermodal units. |
| ytd_total_yoy_pct | float | Year-over-year percent change of the YTD cumulative total. (unit: percent) |
| ytd_carloads | float | Year-to-date cumulative carloads (US only; null elsewhere). |
| ytd_carloads_yoy_pct | float | Y/y change of YTD carloads (US only). (unit: percent) |
| ytd_intermodal_units | float | Year-to-date cumulative intermodal units (US only). |
| ytd_intermodal_yoy_pct | float | Y/y change of YTD intermodal units (US only). (unit: percent) |
| n_commodity_groups_up | float | Number of the 10 AAR carload commodity groups up y/y that week (US only). |
| top_gaining_group | string | Commodity group with the largest absolute carload gain that week (US only). |
| top_gaining_group_wow_change | float | Absolute carload change of the top gaining group (US only). |
| top_declining_group | string | Commodity group with the largest absolute carload decline that week (US only). |
| top_declining_group_wow_change | float | Absolute carload change of the top declining group, negative (US only). |
| momentum_4w_pct | float | Mean of total_yoy_pct over the trailing 4 weeks (null for the first 3 weeks). (unit: percent) |
| demand_regime | string | Fixed-cut regime from total_yoy_pct: expanding (>=3), steady (>= -1), soft (>= -4), contracting (< -4). |
| freight_pulse_score | integer | 0-100 per-region demand-strength gauge: 50 + 12 * z(total_yoy_pct) over the window, clipped. |
| source_url | string | AAR press-release URL the week's figures were extracted from. |
| collected_at | string | Date the release was collected (ISO). |
| row_hash | string | md5 over week_end|region|total_units|total_yoy_pct|freight_pulse_score. |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| week_end | week_number | region | country_code | carloads | carloads_yoy_pct | intermodal_units | intermodal_yoy_pct | total_units | total_yoy_pct | total_yoy_derived | intermodal_share_pct | ytd_total_units | ytd_total_yoy_pct | ytd_carloads | ytd_carloads_yoy_pct | ytd_intermodal_units | ytd_intermodal_yoy_pct | n_commodity_groups_up | top_gaining_group | top_gaining_group_wow_change | top_declining_group | top_declining_group_wow_change | momentum_4w_pct | demand_regime | freight_pulse_score | source_url | collected_at | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026-07-04 | 26 | Canada | CAN | 88 601 | 8,1 | 70 562 | -4,1 | 159 163 | 2,33 | true | 44,33 | 4 277 145 | 0,6 | — | — | — | — | — | — | — | — | — | — | steady | 47 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-4-2026/ | 2026-10-01 | 74c2d30c554939c1af5b53d0cce7bcb8 |
| 2026-07-04 | 26 | Mexico | MEX | 15 445 | 42,2 | 14 611 | 56 | 30 056 | 48,59 | true | 48,61 | 673 753 | 9,2 | — | — | — | — | — | — | — | — | — | — | expanding | 70 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-4-2026/ | 2026-10-01 | c368c9a6489c1d06c18a9448b12a21ae |
| 2026-07-04 | 26 | North America | NAM | 316 737 | 6,3 | 354 603 | 10,3 | 671 340 | 8,4 | false | 52,82 | 18 099 612 | 2,9 | — | — | — | — | — | — | — | — | — | — | expanding | 64 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-4-2026/ | 2026-10-01 | 8e4d9fd29a49ac6a2f19d6d149efcc5f |
| 2026-07-04 | 26 | United States | USA | 212 691 | 3,7 | 269 430 | 12,9 | 482 121 | 8,7 | false | 55,88 | 13 148 714 | 3,4 | 5 894 302 | 3,2 | 7 254 412 | 3,6 | 9 | grain | 2 490 | coal | -4 197 | — | expanding | 65 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-4-2026/ | 2026-10-01 | e7158cec2a48cdaf9ee89b8e28f13cf5 |
| 2026-07-11 | 27 | Canada | CAN | 89 784 | 1,9 | 73 506 | -1,4 | 163 290 | 0,39 | true | 45,02 | 4 440 435 | 0,6 | — | — | — | — | — | — | — | — | — | — | steady | 41 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-11-2026/ | 2026-10-01 | 2cc97528546ecd5f69549a4430ed6087 |
| 2026-07-11 | 27 | Mexico | MEX | 14 182 | 24,6 | 14 082 | 55,4 | 28 264 | 38,25 | true | 49,82 | 700 187 | 9,8 | — | — | — | — | — | — | — | — | — | — | expanding | 63 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-11-2026/ | 2026-10-01 | c88550cfdf6bd73a1e4e221731eb49af |
| 2026-07-11 | 27 | North America | NAM | 327 006 | 1,1 | 368 073 | 3,4 | 695 079 | 2,3 | false | 52,95 | 18 792 861 | 2,9 | — | — | — | — | — | — | — | — | — | — | steady | 43 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-11-2026/ | 2026-10-01 | caa020e6088463aaca565a2bc6ac5e83 |
| 2026-07-11 | 27 | United States | USA | 223 040 | -0,4 | 280 485 | 3 | 503 525 | 1,5 | false | 55,7 | 13 652 239 | 3,4 | 6 117 342 | 3,1 | 7 534 897 | 3,6 | 8 | metallic ores and metals | 1 627 | coal | -4 713 | — | steady | 42 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-11-2026/ | 2026-10-01 | 61b42ef525b81661badf3545d1d30474 |
| 2026-07-18 | 28 | Canada | CAN | 88 318 | 3,8 | 71 076 | -3,2 | 159 394 | 0,56 | true | 44,59 | 4 599 829 | 0,6 | — | — | — | — | — | — | — | — | — | — | steady | 42 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-18-2026/ | 2026-10-01 | 8f9c31c941fb1f94d435ef18c363bb4e |
| 2026-07-18 | 28 | Mexico | MEX | 13 058 | 12,2 | 14 408 | 53 | 27 466 | 30,45 | true | 52,46 | 727 653 | 10,5 | — | — | — | — | — | — | — | — | — | — | expanding | 58 | https://www.aar.org/news/aar-reports-weekly-rail-traffic-for-the-week-ending-july-18-2026/ | 2026-10-01 | 5d330f7c2014a3a6b67ce4ed8d35d07f |
Profilé le 1 oct. 2026 à partir de l’instantané 20261001T170411Z-4548a7ee3a55
Mesuré- Complétude
- 75,9 %
- Lignes
- 52
- Colonnes
- 29
- Colonnes incomplètes
- 10
| Colonne | Manquant | Distinctes | Plage | Distribution |
|---|---|---|---|---|
| week_endvarchar | 0 % | 15 | — |
|
| week_numberbigint | 0 % | 15 | 26 → 38médiane 32 | |
| regionvarchar | 0 % | 4 | — |
|
| country_codevarchar | 0 % | 4 | — |
|
| carloadsbigint | 0 % | 56 | 11 710 → 346 191médiane 153 811 | 2 hors du 1er–99e centile |
| carloads_yoy_pctdouble | 0 % | 58 | -16,8 → 42,2médiane 3,05 | 2 hors du 1er–99e centile |
| intermodal_unitsbigint | 0 % | 54 | 12 317 → 395 417médiane 173 393 | 2 hors du 1er–99e centile |
| intermodal_yoy_pctdouble | 0 % | 49 | -8,3 → 64,5médiane 5,45 | 2 hors du 1er–99e centile |
| total_unitsbigint | 0 % | 49 | 24 027 → 741 608médiane 326 484 | 2 hors du 1er–99e centile |
| total_yoy_pctdouble | 0 % | 47 | -7,39 → 48,59médiane 3,75 | 2 hors du 1er–99e centile |
| total_yoy_derivedboolean | 0 % | 2 | — |
|
| intermodal_share_pctdouble | 0 % | 55 | 42 → 56,69médiane 52,74 | 2 hors du 1er–99e centile |
| ytd_total_unitsbigint | 0 % | 43 | 673 753 → 26 678 211médiane 9 700 534 | 2 hors du 1er–99e centile |
| ytd_total_yoy_pctdouble | 0 % | 27 | 0,5 → 11,5médiane 3,3 | 1 hors du 1er–99e centile |
| ytd_carloadsdouble | 75 % | 12 | 5 894 302 → 8 679 882médiane 7 276 025 | 2 hors du 1er–99e centile |
| ytd_carloads_yoy_pctdouble | 75 % | 5 | 2,7 → 3,2médiane 2,7 | 1 hors du 1er–99e centile |
| ytd_intermodal_unitsdouble | 75 % | 14 | 7 254 412 → 10 778 696médiane 9 005 409 | 2 hors du 1er–99e centile |
| ytd_intermodal_yoy_pctdouble | 75 % | 7 | 3,6 → 4,2médiane 3,8 | 1 hors du 1er–99e centile |
| n_commodity_groups_updouble | 75 % | 6 | 3 → 9médiane 7 | 1 hors du 1er–99e centile |
| top_gaining_groupvarchar | 75 % | 3 | — |
|
| top_gaining_group_wow_changedouble | 75 % | 12 | 1 627 → 4 859médiane 2 261 | 2 hors du 1er–99e centile |
| top_declining_groupvarchar | 75 % | 4 | — |
|
| top_declining_group_wow_changedouble | 75 % | 13 | -5 894 → -1 031médiane -3 547 | 2 hors du 1er–99e centile |
| momentum_4w_pctdouble | 23,1 % | 44 | 0,62 → 40,59médiane 4,27 | 2 hors du 1er–99e centile |
| demand_regimevarchar | 0 % | 4 | — |
|
| freight_pulse_scorebigint | 0 % | 35 | 23 → 80médiane 48 | 2 hors du 1er–99e centile |
| source_urlvarchar | 0 % | 11 | — |
|
| collected_atvarchar | 0 % | 1 | — |
|
| row_hashvarchar | 0 % | 55 | — |
|
- Actuelle
20261001T170411Z-4548a7ee3a55 · sha256 4548a7ee3a55…
52 lignes · premier instantané
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/aar_rail_freight_intel/na_weekly_rail_freight_weekly" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/aar_rail_freight_intel/na_weekly_rail_freight_weekly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API : https://datazimuts.com/v1/datasets/aar_rail_freight_intel/na_weekly_rail_freight_weekly
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.
D’où viennent ces données et ce qui en a été fait. Le travail des autres apparaît sous forme de décomptes ; seuls les projets partagés sont nommés.
Citer cet instantané
Épinglé à l’instantané 20261001T170411Z-4548a7ee3a55 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
APA
AAR Weekly Rail Freight Intelligence. (2026). North America weekly rail freight intelligence [Data set, snapshot 20261001T170411Z-4548a7ee3a55, sha256 4548a7ee3a55]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/fr/datasets/aar_rail_freight_intel/na_weekly_rail_freight_weekly?snapshot=20261001T170411Z-4548a7ee3a55
BibTeX
@misc{dz_aar_rail_freight_intel_na_weekly_rail_fr_4548a7ee,
title = {{North America weekly rail freight intelligence}},
author = {{AAR Weekly Rail Freight Intelligence}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/aar_rail_freight_intel/na_weekly_rail_freight_weekly?snapshot=20261001T170411Z-4548a7ee3a55}},
note = {Snapshot 20261001T170411Z-4548a7ee3a55, sha256 4548a7ee3a5594de4059241a0185f96d67101cbd52c0eaf26171e8ab4bc4d041; accessed 2026-10-02}
}Intégrer un tableau ou un graphique
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HTML
<iframe src="https://datazimuts.com/embed/chart?dataset=aar_rail_freight_intel%2Fna_weekly_rail_freight_weekly&lang=fr&theme=auto&snapshot=20261001T170411Z-4548a7ee3a55&x=week_end&y=week_number&agg=avg" title="North America weekly rail freight intelligence" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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