Estimates Emissions of CO2 at Country And Global Level Starting 1751

JohnSnowLabs

Files Size Format Created Updated License Source
2 1MB csv zip 3 months ago John Snow Labs Standard License John Snow Labs Centers for Carbon Dioxide Information Analysis Center
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Data Files

File Description Size Last changed Download
estimates-emissions-of-co2-at-country-and-global-level-starting-1751-csv 1MB csv (1MB) , json (11MB)
estimates-emissions-of-co2-at-country-and-global-level-starting-1751_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 1MB zip (1MB)

estimates-emissions-of-co2-at-country-and-global-level-starting-1751-csv  

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

Field information

Field Name Order Type (Format) Description
Year 1 date (%Y-%m-%d) The year for which estimated the data in a row corresponds
Country 2 string The names of nations as they were officially known around 1984, for which country level estimated data in a row corresponds
Country_Fossil_Fuels_And_Cement_Per_Year 3 integer Fossil fuel and cement production CO2 emissions estimated quantity in thousand of metric tons in a country and in a specific year
All_Countries_Fossil_Fuels_And_Cement_Per_Year 4 integer Fossil fuels and cement production CO2 emissions estimated quantity in thousand of metric tons estimated from countries for which data exist in a specific year
Country_Solid_Fuel_Per_Year 5 integer Solid fuel and cement CO2 emissions estimated quantity in thousand of metric tons in a country and in a specific year
All_Countries_Solid_Fuel_Per_Year 6 integer Solid fuel CO2 emissions estimated quantity in thousand of metric tons from countries for which data exist in a specific year
Country_Liquid_Fuel_Per_Year 7 integer Liquid fuel CO2 emissions estimated quantity in thousand of metric tons in a country and in a specific year
All_Countries_Liquid_Fuel_Per_Year 8 integer Liquid fuel CO2 emissions estimated quantity in thousand of metric tons from countries for which data exist in a specific year
Country_Gas_Fuel_Per_Year 9 integer Gas fuel CO2 emissions estimated quantity in thousand of metric tons in a country and in a specific year
All_Countries_Gas_Fuel_Per_Year 10 integer Gas fuel CO2 emissions estimated quantity in thousand of metric tons from countries for which data exist in a specific year
Country_Cement_Per_Year 11 number Cement production CO2 emissions estimated quantity in thousand of metric tons in a country and in a specific year
All_Countries_Cement_Per_Year 12 integer Cement production CO2 emissions estimated quantity in thousand of metric tons from countries for which data exist in a specific year
Country_Gas_Flaring_Per_Year 13 integer Gas flaring CO2 emissions estimated quantity in thousand of metric tons in a country and in a specific year
All_Countries_Gas_Flaring_Per_Year 14 integer Gas flaring CO2 emissions estimated quantity in thousand of metric tons from countries for which data exist in a specific year
Country_Per_Capita_Per_Year 15 number CO2 emissions estimated quantity per capita in thousand of metric tons related to fossil fuel and/or cement production in a country and in a specific year
All_Countries_Capita_Per_Year 16 number CO2 emissions estimated quantity per capita in thousand of metric tons related to fossil fuel and/or cement production from countries for which data exist in a specific year
Country_Bunker_Fuels_Per_Year 17 integer Bunker fuels CO2 emissions estimated quantity in thousand of metric tons in a country and in a specific year

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Use data with the datahub.io almost like you use git with the github. Here are installation instructions.

data get https://datahub.io/JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751
tree JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751
# Get a list of dataset's resources
curl -L -s https://datahub.io/JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751/r/0.csv

curl -L https://datahub.io/JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751/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/JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751/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/JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751/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/JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751/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/JohnSnowLabs/estimates-emissions-of-co2-at-country-and-global-level-starting-1751/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)
    }
  }
})()
Datapackage.json