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Files | Size | Format | Created | Updated | License | Source |
---|---|---|---|---|---|---|
2 | 871kB | csv zip | 6 years ago | 5 years ago | Open Data Commons Public Domain Dedication and License v1.0 | EU ETS data |
Download files in this dataset
File | Description | Size | Last changed | Download |
---|---|---|---|---|
eu-ets | 5MB | csv (5MB) , json (10MB) | ||
eu-emissions-trading-system_zip | Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. | 828kB | zip (828kB) |
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This is a preview version. There might be more data in the original version.
Field Name | Order | Type (Format) | Description |
---|---|---|---|
country_code | 1 | string | International Country Code (ISO 3166-1-Alpha-2 code elements) |
country | 2 | string | Country name |
main activity sector name | 3 | string | Main activity label |
ETS information | 4 | string | ETS information |
year | 5 | string | Annual data mainly in YYYY format, but also may include stings Eg: Total 1st trading period (05-07) |
value | 6 | number | measure value |
unit | 7 | string | Unit of the measure value (in tonne of CO2-equ.) |
Use our data-cli tool designed for data wranglers:
data get https://datahub.io/core/eu-emissions-trading-system
data info core/eu-emissions-trading-system
tree core/eu-emissions-trading-system
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/eu-emissions-trading-system/datapackage.json | grep path
# Get resources
curl -L https://datahub.io/core/eu-emissions-trading-system/r/0.csv
curl -L https://datahub.io/core/eu-emissions-trading-system/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/eu-emissions-trading-system/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/eu-emissions-trading-system/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/eu-emissions-trading-system/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/eu-emissions-trading-system/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)
}
}
})()
Data about the EU emission trading system (ETS). The EU emission trading system (ETS) is one of the main measures introduced by the EU to achieve cost-efficient reductions of greenhouse gas emissions and reach its targets under the Kyoto Protocol and other commitments. The data mainly comes from the EU Transaction Log (EUTL).
Aggregated data on greenhouse gas emissions and allowances.
Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom
2005-2014
Python 2 together with modules urllib and zipfile are required in order to process the data.
Run the following script from this directory to download and process the data:
make
The raw data are output to ./tmp
. The processed data are output to ./data
.
Data are sourced from European Environment Agency and no copyright restrictions are applied. More specifically:
EEA aspires to promote the sharing of environmental data. In agreeing to share, data providers need to have assurance that their data are properly handled, disseminated and acknowledged following similar principles and rules across countries and stakeholders.*
All the additional work done to build this Data Package is made available under the Public Domain Dedication and License v1.0 whose full text can be found at: http://www.opendatacommons.org/licenses/pddl/1.0/
Notifications of data updates and schema changes
Warranty / guaranteed updates
Workflow integration (e.g. Python packages, NPM packages)
Customized data (e.g. you need different or additional data)
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