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Files | Size | Format | Created | Updated | License | Source |
---|---|---|---|---|---|---|
2 | 45kB | csv zip | 6 years ago | 5 years ago | Open Data Commons Public Domain Dedication and License v1.0 | CDIAC |
Download files in this dataset
File | Description | Size | Last changed | Download |
---|---|---|---|---|
global | 7kB | csv (7kB) , json (37kB) | ||
co2-fossil-global_zip | Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. | 11kB | zip (11kB) |
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This is a preview version. There might be more data in the original version.
Field Name | Order | Type (Format) | Description |
---|---|---|---|
Year | 1 | year | Year |
Total | 2 | number | Total carbon emissions from fossil fuel consumption and cement production (million metric tons of C) |
Gas Fuel | 3 | number | Carbon emissions from gas fuel consumption |
Liquid Fuel | 4 | number | Carbon emissions from liquid fuel consumption |
Solid Fuel | 5 | number | Carbon emissions from solid fuel consumption |
Cement | 6 | number | Carbon emissions from cement production |
Gas Flaring | 7 | number | Carbon emissions from gas flaring |
Per Capita | 8 | number | Per capita carbon emissions (metric tons of carbon; after 1949 only) |
Use our data-cli tool designed for data wranglers:
data get https://datahub.io/core/co2-fossil-global
data info core/co2-fossil-global
tree core/co2-fossil-global
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/co2-fossil-global/datapackage.json | grep path
# Get resources
curl -L https://datahub.io/core/co2-fossil-global/r/0.csv
curl -L https://datahub.io/core/co2-fossil-global/r/1.zip
If you are using R here's how to get the data you want quickly loaded:
install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")
json_file <- 'https://datahub.io/core/co2-fossil-global/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))
# get list of all resources:
print(json_data$resources$name)
# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
if(json_data$resources$datahub$type[i]=='derived/csv'){
path_to_file = json_data$resources$path[i]
data <- read.csv(url(path_to_file))
print(data)
}
}
Note: You might need to run the script with root permissions if you are running on Linux machine
Install the Frictionless Data data package library and the pandas itself:
pip install datapackage
pip install pandas
Now you can use the datapackage in the Pandas:
import datapackage
import pandas as pd
data_url = 'https://datahub.io/core/co2-fossil-global/datapackage.json'
# to load Data Package into storage
package = datapackage.Package(data_url)
# to load only tabular data
resources = package.resources
for resource in resources:
if resource.tabular:
data = pd.read_csv(resource.descriptor['path'])
print (data)
For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):
pip install datapackage
To get Data Package into your Python environment, run following code:
from datapackage import Package
package = Package('https://datahub.io/core/co2-fossil-global/datapackage.json')
# print list of all resources:
print(package.resource_names)
# print processed tabular data (if exists any)
for resource in package.resources:
if resource.descriptor['datahub']['type'] == 'derived/csv':
print(resource.read())
If you are using JavaScript, please, follow instructions below:
Install data.js
module using npm
:
$ npm install data.js
Once the package is installed, use the following code snippet:
const {Dataset} = require('data.js')
const path = 'https://datahub.io/core/co2-fossil-global/datapackage.json'
// We're using self-invoking function here as we want to use async-await syntax:
;(async () => {
const dataset = await Dataset.load(path)
// get list of all resources:
for (const id in dataset.resources) {
console.log(dataset.resources[id]._descriptor.name)
}
// get all tabular data(if exists any)
for (const id in dataset.resources) {
if (dataset.resources[id]._descriptor.format === "csv") {
const file = dataset.resources[id]
// Get a raw stream
const stream = await file.stream()
// entire file as a buffer (be careful with large files!)
const buffer = await file.buffer
// print data
stream.pipe(process.stdout)
}
}
})()
Global CO2 Emissions from fossil-fuels annually since 1751 till 2014.
Data comes from the Carbon Dioxide Information Analysis Center (CDIAC).
Original csv: http://cdiac.ess-dive.lbl.gov/ftp/ndp030/CSV-FILES/global.1751_2014.csv
The data was prepared in this Tabularum project: http://explorer.okfnlabs.org/#rgrp/9452691
Please cite as:
Boden, T.A., G. Marland, and R.J. Andres. 2013. Global, Regional, and National Fossil-Fuel CO2 Emissions. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. doi 10.3334/CDIAC/00001_V2013
This Data Package is licensed by its maintainers under the Public Domain Dedication and License (PDDL).
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