Global digital-adoption signals (World Bank connectivity)
Global digital-adoption signals from World Bank connectivity indicators (keyless API, annual, ~1990 -> 2024, 200+ economies): Internet use (% of population), mobile subscriptions and fixed broadband subscriptions (per 100 people), with 10-year changes, OLS adoption-velocity trends, 3-sigma anomaly flags, 5-year linear-extrapolation forecasts, per-year cross-country ranks, a 5-year catch-up momentum gauge, the digital-divide gap versus the global median, and a connectivity-laggard flag. The first tech/digital-domain value-added set: which countries are catching up and which are falling behind. World Bank API terms permit non-commercial use only — commercial_use flagged 'no' in the UI. All rows normalized to ISO alpha-3 country codes so they join cleanly with every other global dataset. Raw data: World Bank (via ITU).
Qualité
Attribution
World Bank (indicators via ITU); non-commercial use only per World Bank API Terms of Use; derived signals by Frontier Data Hub
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Reference year (World Bank API field date; YYYY, annual). |
| country | string | Country short name (World Bank API field country.value). |
| country_code | string | ISO 3166-1 alpha-3 country code (World Bank API field countryiso3code). |
| series_id | string | World Bank indicator code: IT.NET.USER.ZS (Individuals using the Internet, % of population), IT.CEL.SETS.P2 (Mobile cellular subscriptions per 100 people) or IT.NET.BBND.P2 (Fixed broadband subscriptions per 100 people). |
| series_label | string | Official World Bank indicator name as published in the API metadata. |
| value | float | Indicator value: percent of population (Internet use) or subscriptions per 100 people (mobile, fixed broadband); World Bank, sourced from the International Telecommunication Union (ITU). |
| change_10y_pp | float | |
| trend_slope | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| adoption_momentum_5y | float | |
| digital_divide_gap | float | |
| laggard_flag | integer |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | change_10y_pp | trend_slope | anomaly_flag | forecast_1m | rank | adoption_momentum_5y | digital_divide_gap | laggard_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1960-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | — | 0 | — | 1 | — | 0 | 0 |
| 1965-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | — | 0 | — | 1 | — | 0 | 0 |
| 1970-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | — | 0 | — | 1 | — | 0 | 0 |
| 1975-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | — | 0 | — | 1 | — | 0 | 0 |
| 1976-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | 0 | 0 | 0 | 1 | — | 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/digital_signals/wb_digital_adoption_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/digital_signals/wb_digital_adoption_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/digital_signals/wb_digital_adoption_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.