Global carbon accountability signals (per-capita, intensity, historical responsibility)

Name: Global carbon accountability signals (per-capita, intensity, historical responsibility)
Creator: Global Carbon Accountability Signals (derived)
License: https://ourworldindata.org/
Keywords: co2, emissions, carbon, climate, decarbonization, owid, accountability, signals

Value-added carbon-accountability signals from free Our World in Data CO2 data: per-capita emissions, carbon intensity of GDP, global and cumulative emission shares with decarbonization trends, peaked-emissions flags, anomaly flags and cross-country ranks across ~200 countries. All computation is local pandas/numpy; no paid models or APIs.

Source: Global Carbon Accountability Signals (derived)84,436 lignesMis à jour: 22/09/2026Licence: CC-BY-4.0

co2emissionscarbonclimatedecarbonizationowidaccountabilitysignals

Qualité

99.7

Attribution

Our World in Data (https://ourworldindata.org); derived signals by Frontier Data Hub

Schéma

Colonne	Type	Description
date	string	Reference year of the observation (first day of the year), as published in the Our World in Data CO2 dataset.
country	string
country_code	string
series_id	string	Derived series identifier: CO2_PER_CAPITA (territorial CO2 per person), CO2_PER_GDP (CO2 intensity of GDP), SHARE_GLOBAL_CO2 (share of global annual CO2), or SHARE_CUMULATIVE_CO2 (share of cumulative CO2 since 1750).
series_label	string	Human-readable series label from the Our World in Data CO2 dataset documentation, naming the emissions indicator and its unit.
value	float	Indicator value as published by Our World in Data: territorial CO2 per capita in tonnes; CO2 intensity in kg per 2017 international-$ of GDP; global and cumulative emission shares in percent.
trend_10y	float
peaked_flag	integer
anomaly_flag	integer
rank	float

Exemple de lignes

date	country	country_code	series_id	series_label	value	trend_10y	rank
1750-01-01	Australia	AUS	CO2_PER_CAPITA	Territorial CO2 emissions per capita (tonnes per person, Our World in Data)	0	—	2
1750-01-01	United Kingdom	GBR	CO2_PER_CAPITA	Territorial CO2 emissions per capita (tonnes per person, Our World in Data)	1.002	—	1
1750-01-01	Norway	NOR	CO2_PER_CAPITA	Territorial CO2 emissions per capita (tonnes per person, Our World in Data)	0	—	2
1750-01-01	New Zealand	NZL	CO2_PER_CAPITA	Territorial CO2 emissions per capita (tonnes per person, Our World in Data)	0	—	2
1750-01-01	Taiwan	TWN	CO2_PER_CAPITA	Territorial CO2 emissions per capita (tonnes per person, Our World in Data)	0	—	2

Télécharger un échantillon

Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).

Télécharger l'exemple CSV Télécharger l'exemple JSON

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/carbon_accountability_signals/global_carbon_accountability_signals" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/carbon_accountability_signals/global_carbon_accountability_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/carbon_accountability_signals/global_carbon_accountability_signals

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.