US freight-activity signals (goods-demand slowdown/surge gauges)
Monthly goods-demand signals derived from FRED US transport data (Cass shipments, freight transportation services index, rail carloads): month-on-month and year-on-year changes, 30-month change volatility, 3-sigma anomaly flags vs a trailing-12-month baseline, drift forecasts, per-month cross-series volatility ranks, and a composite freight-momentum z-score with slowdown/surge flags. The transport-flow companion to the industrial-production and trade signals. Country codes normalized to ISO alpha-3 (USA). Raw data: Cass Information Systems / Bureau of Transportation Statistics / Association of American Railroads via FRED.
Qualité
Attribution
Cass Information Systems / Bureau of Transportation Statistics / Association of American Railroads via FRED (derived signals by Frontier Data Hub)
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Observation date (month start). (unit: ISO date) |
| country | string | Country of the series (United States). |
| country_code | string | ISO 3166-1 alpha-3 country code (USA). |
| series_id | string | FRED series identifier: FRGSHPUSM649NCIS, TSIFRGHT, or RAILFRTCARLOADSD11. |
| series_label | string | FRED series title. |
| value | float | Series value in native units: Cass shipments index (January 1990 = 1.0), freight transportation services index (2000 = 100), or rail freight carloads (number of carloads). |
| volatility_30d | float | |
| momentum_3m | float | |
| yoy_change_pct | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| freight_momentum_z | float | |
| slowdown_flag | integer | |
| surge_flag | integer |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | volatility_30d | momentum_3m | yoy_change_pct | anomaly_flag | forecast_1m | rank | freight_momentum_z | slowdown_flag | surge_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2000-01-01 | United States | USA | RAILFRTCARLOADSD11 | Rail Freight Carloads | 1373789 | — | — | — | 0 | — | — | — | 0 | 0 |
| 2000-01-01 | United States | USA | TSIFRGHT | Freight Transportation Services Index | 104.9 | — | — | — | 0 | — | — | — | 0 | 0 |
| 2000-02-01 | United States | USA | RAILFRTCARLOADSD11 | Rail Freight Carloads | 1369630 | — | — | — | 0 | — | — | — | 0 | 0 |
| 2000-02-01 | United States | USA | TSIFRGHT | Freight Transportation Services Index | 103.1 | — | — | — | 0 | — | — | — | 0 | 0 |
| 2000-03-01 | United States | USA | RAILFRTCARLOADSD11 | Rail Freight Carloads | 1363186 | — | — | — | 0 | — | — | — | 0 | 0 |
Télécharger un échantillon
Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).
Utiliser avec un LLM
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/freight_activity_signals/us_freight_activity_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/freight_activity_signals/us_freight_activity_signals").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/freight_activity_signals/us_freight_activity_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.