Global CO2 Emissions from Fossil Fuels since 1751

core

Files Size Format Created Updated License Source
2 42kB csv zip 7 months ago 3 months ago Open Data Commons Public Domain Dedication and License v1.0 CDIAC
Global CO2 Emissions from fossil-fuels annually since 1751 till 2014. Data 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 Preparation The data was prepared in this Tabularum read more
Download

Data Files

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)

global  

This is a preview version. There might be more data in the original version.

Field information

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)

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Download CLI tool and use it with the datahub almost like you use git with the github:

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)
    }
  }
})()

Read me

Global CO2 Emissions from fossil-fuels annually since 1751 till 2014.

Data

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

Preparation

The data was prepared in this Tabularum project: http://explorer.okfnlabs.org/#rgrp/9452691

Citation

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

License

This Data Package is licensed by its maintainers under the Public Domain Dedication and License (PDDL).

Datapackage.json