Global education-spending signals
Annual government education-expenditure signals from the World Bank World Development Indicators (UNESCO via WDI, 1970 ->, % of GDP, keyless): per-economy 5-year changes, 10-year OLS trend slopes, 3-sigma anomaly flags, linear-extrapolation forecasts, 10-year z-scores, per-year cross-country ranks, and high/low spender and investment-push flags. The education-investment lens — which governments are building human capital and which are disinvesting — not covered elsewhere in the catalog. Country labels normalized to ISO alpha-3. Raw data: World Bank WDI indicator SE.XPD.TOTL.GD.ZS.
Qualité
Attribution
World Bank, World Development Indicators (derived signals by Frontier Data Hub)
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Reference year (World Bank WDI, annual). |
| country | string | |
| country_code | string | |
| series_id | string | World Bank WDI indicator code: SE.XPD.TOTL.GD.ZS (government expenditure on education, total, as a percent of GDP). |
| series_label | string | Indicator title as published in the World Bank World Development Indicators. |
| value | float | General government expenditure on education (current, capital, and transfers) expressed as a percentage of GDP. Includes expenditure funded by transfers from international sources to government. General government usually refers to local, regional and central governments. |
| change_5y_pp | float | |
| trend_slope_10y | float | |
| anomaly_flag | integer | |
| forecast_5y | float | |
| spend_z_10y | float | |
| rank | integer | |
| high_edu_flag | integer | |
| low_edu_flag | integer | |
| rising_flag | integer |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | change_5y_pp | trend_slope_10y | anomaly_flag | forecast_5y | spend_z_10y | rank | high_edu_flag | low_edu_flag | rising_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1998-01-01 | Aruba | ABW | SE.XPD.TOTL.GD.ZS | Government expenditure on education, total (% of GDP) | 4.76316022872925 | — | — | 0 | — | — | 25 | 0 | 0 | 0 |
| 1999-01-01 | Aruba | ABW | SE.XPD.TOTL.GD.ZS | Government expenditure on education, total (% of GDP) | 4.39526987075806 | — | — | 0 | — | — | 54 | 0 | 0 | 0 |
| 2000-01-01 | Aruba | ABW | SE.XPD.TOTL.GD.ZS | Government expenditure on education, total (% of GDP) | 4.71468019485474 | — | — | 0 | — | — | 46 | 0 | 0 | 0 |
| 2001-01-01 | Aruba | ABW | SE.XPD.TOTL.GD.ZS | Government expenditure on education, total (% of GDP) | 4.79898023605347 | — | — | 0 | — | — | 47 | 0 | 0 | 0 |
| 2002-01-01 | Aruba | ABW | SE.XPD.TOTL.GD.ZS | Government expenditure on education, total (% of GDP) | 4.87220001220703 | — | 0.06217899322509663 | 0 | 5.183094978332513 | — | 46 | 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/education_spending_signals/global_education_spending_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/education_spending_signals/global_education_spending_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/education_spending_signals/global_education_spending_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.