Peak surcharge daily cost-pressure panel 2026-27
Derived daily panel (2026-09-26..2027-01-17, per carrier): on each date, how many surcharge lines are active, the headline standard-residential per-package fee in effect (NULL for USPS, which raises rate tables instead — flagged by rate_increase_active), whether the date is in the carrier's peak-of-peak window, and a documented 0-100 peak_cost_pressure = round(100 * (0.6 * active_line_count / carrier_line_total + 0.4 * residential_component)) where the residential component is fee / carrier_max_fee (UPS 0.75, FedEx 0.80, Amazon 0.75, OnTrac 1.00) or rate_increase_active for USPS. A shop joins this on ship date + carrier to budget the seasonal per-package premium; 570 rows, deterministic in code from the curated window table. Annual snapshot, yearly cadence.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 570
- Colonnes
- 11
- Cadence de la source
- Annuelle
- Dernière actualisation
- 30 sept. 2026
- Thème
- economy
| Colonne | Type | Description |
|---|---|---|
| panel_id | string | Deterministic primary key: <CARRIER>-<panel_date>. |
| panel_date | date | Calendar date the panel row describes (ISO date). Join key with ship/label date. |
| carrier | string | Carrier. Join key. |
| year | integer | Peak season anchor year. (unit: year) |
| active_line_count | integer | Number of surcharge-window rows active on panel_date. |
| residential_fee_usd | float | Headline standard-residential per-package demand fee in effect on panel_date (USD); NULL when no residential line is active (always NULL for USPS, which raises rate tables instead). (unit: USD) |
| rate_increase_active | integer | 1 when the USPS temporary holiday rate change is in effect on panel_date (2026-10-04..2027-01-17); 0 otherwise. |
| in_peak_window | integer | 1 when panel_date falls in the carrier's peak-of-peak window (the highest-amount residential window). |
| any_active | integer | 1 when any surcharge line is active on panel_date. |
| peak_cost_pressure | integer | 0-100 cost pressure = round(100*(0.6*active_line_count/carrier_line_total + 0.4*residential_component)); residential_component = fee/carrier_max_fee (UPS 0.75, FedEx 0.80, Amazon 0.75, OnTrac 1.00) or rate_increase_active for USPS. |
| row_hash | string | Deterministic row key: first 16 hex chars of sha256 over canonical row values. |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| panel_id | panel_date | carrier | year | active_line_count | residential_fee_usd | rate_increase_active | in_peak_window | any_active | peak_cost_pressure | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|
| ups-2026-09-26 | 2026-09-26 | UPS | 2 026 | 0 | — | 0 | 0 | 0 | 0 | fd7feb0e060b08f1 |
| fedex-2026-09-26 | 2026-09-26 | FedEx | 2 026 | 0 | — | 0 | 0 | 0 | 0 | 45a9b53dfdbf4931 |
| amazon-shipping-2026-09-26 | 2026-09-26 | Amazon Shipping | 2 026 | 0 | — | 0 | 0 | 0 | 0 | 96b031454ee48124 |
| ontrac-2026-09-26 | 2026-09-26 | OnTrac | 2 026 | 4 | 1 | 0 | 1 | 1 | 100 | 7b11b9580714ef6b |
| usps-2026-09-26 | 2026-09-26 | USPS | 2 026 | 0 | — | 0 | 0 | 0 | 0 | d1a3ce40ee79cb60 |
| ups-2026-09-27 | 2026-09-27 | UPS | 2 026 | 3 | — | 0 | 0 | 1 | 9 | 279096fc1cf3af8d |
| fedex-2026-09-27 | 2026-09-27 | FedEx | 2 026 | 0 | — | 0 | 0 | 0 | 0 | 25c0c750645a5607 |
| amazon-shipping-2026-09-27 | 2026-09-27 | Amazon Shipping | 2 026 | 3 | — | 0 | 0 | 1 | 15 | 2246c247172ab732 |
| ontrac-2026-09-27 | 2026-09-27 | OnTrac | 2 026 | 4 | 1 | 0 | 1 | 1 | 100 | 62bc6bca0c9d536d |
| usps-2026-09-27 | 2026-09-27 | USPS | 2 026 | 0 | — | 0 | 0 | 0 | 0 | 89f258bbcab0df49 |
- Actuelle
20260930T134258Z-74ddc7da7a2e · sha256 74ddc7da7a2e…
570 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 "https://datazimuts.com/v1/datasets/us_peak_surcharge_intel/us_peak_surcharge_daily_2026" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/us_peak_surcharge_intel/us_peak_surcharge_daily_2026").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/us_peak_surcharge_intel/us_peak_surcharge_daily_2026
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.
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Épinglé à l’instantané 20260930T134258Z-74ddc7da7a2e et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
US parcel carriers 2026-27 peak surcharges (agent-curated). (2026). Peak surcharge daily cost-pressure panel 2026-27 [Data set, snapshot 20260930T134258Z-74ddc7da7a2e, sha256 74ddc7da7a2e]. Datazimuts. Retrieved 2026-09-30, from https://datazimuts.com/fr/datasets/us_peak_surcharge_intel/us_peak_surcharge_daily_2026?snapshot=20260930T134258Z-74ddc7da7a2e
@misc{dz_us_peak_surcharge_intel_us_peak_surcharg_74ddc7da,
title = {{Peak surcharge daily cost-pressure panel 2026-27}},
author = {{US parcel carriers 2026-27 peak surcharges (agent-curated)}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/us_peak_surcharge_intel/us_peak_surcharge_daily_2026?snapshot=20260930T134258Z-74ddc7da7a2e}},
note = {Snapshot 20260930T134258Z-74ddc7da7a2e, sha256 74ddc7da7a2e55feda0afed36be92bab44cdad7729068a665fc8cbcf3c80a5ba; accessed 2026-09-30}
}Intégrer un tableau ou un graphique
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<iframe src="https://datazimuts.com/embed/chart?dataset=us_peak_surcharge_intel%2Fus_peak_surcharge_daily_2026&lang=fr&theme=auto&snapshot=20260930T134258Z-74ddc7da7a2e&x=panel_date&y=year&agg=avg" title="Peak surcharge daily cost-pressure panel 2026-27" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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