Global demographic transition signals (aging, dependency, urbanization gauges)
Yearly demographic-structure signals for 200+ economies (1960 ->, keyless World Bank API): 65+ and working-age population shares, urbanization, and fertility, with 10-year changes, OLS trend slopes, 3-sigma anomaly flags vs a trailing 5-year baseline, 5-year linear-extrapolation forecasts, cross-country ranks, old-age dependency ratios, aging-speed gauges, super-aged (>20% 65+) and demographic-dividend flags, urbanization momentum, and below-replacement fertility flags. All rows carry normalized ISO country codes so they join cleanly with other macro data. Raw data: World Bank, World Development Indicators.
Qualité
Attribution
World Bank, World Development Indicators (derived signals by Frontier Data Hub)
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Observation year (World Bank API field date; mapped to YYYY-01-01). |
| country | string | |
| country_code | string | |
| series_id | string | World Bank indicator code: one of SP.POP.65UP.TO, SP.POP.1564.TO, SP.URB.TOTL.IN.ZS, SP.DYN.TFRT.IN. |
| series_label | string | Official World Bank indicator name as published in the indicator metadata. |
| value | float | SP.POP.65UP.TO: Population ages 65 and above as a percentage of the total population. World Development Indicators, source 2.; SP.POP.1564.TO: Population ages 15-64 as a percentage of the total population. World Development Indicators, source 2.; SP.URB.TOTL.IN.ZS: Urban population as a percentage of the total population. World Development Indicators, source 2.; SP.DYN.TFRT.IN: Total fertility rate: the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year. World Development Indicators, source 2. |
| change_10y_pp | float | |
| trend_slope | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| old_age_dependency | float | |
| aging_speed_10y_pp | float | |
| super_aged_flag | integer | |
| demographic_dividend_flag | integer | |
| urbanization_momentum | float | |
| below_replacement_flag | integer |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | change_10y_pp | trend_slope | anomaly_flag | forecast_1m | rank | old_age_dependency | aging_speed_10y_pp | super_aged_flag | demographic_dividend_flag | urbanization_momentum | below_replacement_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1960-01-01 | Aruba | ABW | SP.DYN.TFRT.IN | Fertility rate, total (births per woman) | 4.567 | — | — | 0 | — | 69 | 5.229128478586902 | — | 1 | 1 | — | 0 |
| 1961-01-01 | Aruba | ABW | SP.DYN.TFRT.IN | Fertility rate, total (births per woman) | 4.422 | — | — | 0 | — | 67 | 5.222316809639185 | — | 1 | 1 | — | 0 |
| 1962-01-01 | Aruba | ABW | SP.DYN.TFRT.IN | Fertility rate, total (births per woman) | 4.262 | — | — | 0 | — | 64 | 5.256220664823507 | — | 1 | 1 | — | 0 |
| 1963-01-01 | Aruba | ABW | SP.DYN.TFRT.IN | Fertility rate, total (births per woman) | 4.107 | — | -0.15400000000000064 | 0 | 3.336999999999997 | 63 | 5.302170073176886 | — | 1 | 1 | — | 0 |
| 1964-01-01 | Aruba | ABW | SP.DYN.TFRT.IN | Fertility rate, total (births per woman) | 3.94 | — | -0.15690000000000032 | 0 | 3.155499999999998 | 61 | 5.382926753857094 | — | 1 | 1 | — | 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/wb_demographic_signals/wb_demographic_transition_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/wb_demographic_signals/wb_demographic_transition_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/wb_demographic_signals/wb_demographic_transition_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.