Total credit to the private non-financial sector (quarterly, 48 economies)
Credit from all sectors to the private non-financial sector at market value, as a percentage of GDP, adjusted for breaks, from 1947. Bank for International Settlements, BIS Data Portal.
Source: Bank for International Settlements9,825 lignesMis à jour: 22/09/2026
creditdebtleveragefinancial-stabilitygdp
Qualité
97
Attribution
Bank for International Settlements
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Observation period (the TIME_PERIOD column of the BIS SDMX-CSV response). Monthly series use YYYY-MM; quarterly series use YYYY-QN, stored as the first day of the quarter. |
| series_id | string | BIS area code, e.g. 'US': the unique identifier of the series in the BIS Data Portal. |
| series_label | string | English economy name from the BIS's own CL_AREA codelist. |
| value | float | Observed credit stock for the economy and quarter (the OBS_VALUE column). Slice is borrowers = private non-financial sector, lenders = all sectors, market value, adjusted for breaks. Unit 770: percentage of GDP. |
Exemple de lignes
| date | series_id | series_label | value |
|---|---|---|---|
| 1996-10-01 | 4T | Emerging market economies (aggregate) | 55.5 |
| 1997-01-01 | 4T | Emerging market economies (aggregate) | 56.5 |
| 1997-04-01 | 4T | Emerging market economies (aggregate) | 57.4 |
| 1997-07-01 | 4T | Emerging market economies (aggregate) | 54.4 |
| 1997-10-01 | 4T | Emerging market economies (aggregate) | 53.2 |
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/bis/bis_total_credit_private_sector" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/bis/bis_total_credit_private_sector").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/bis/bis_total_credit_private_sector
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.