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Files | Size | Format | Created | Updated | License | Source |
---|---|---|---|---|---|---|
2 | 148kB | csv zip | 6 years ago | 5 years ago | ODC-PDDL-1.0 | United Nations |
Download files in this dataset
File | Description | Size | Last changed | Download |
---|---|---|---|---|
cofog | 86kB | csv (86kB) , json (99kB) | ||
cofog_zip | Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. | 39kB | zip (39kB) |
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This is a preview version. There might be more data in the original version.
Field Name | Order | Type (Format) | Description |
---|---|---|---|
Code | 1 | string | |
Description | 2 | string | |
ExplanatoryNote | 3 | string | |
Change_date | 4 | date (%Y-%m-%d) |
Use our data-cli tool designed for data wranglers:
data get https://datahub.io/core/cofog
data info core/cofog
tree core/cofog
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/cofog/datapackage.json | grep path
# Get resources
curl -L https://datahub.io/core/cofog/r/0.csv
curl -L https://datahub.io/core/cofog/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/cofog/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/cofog/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/cofog/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/cofog/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)
}
}
})()
Classification of the Functions of Government (COFOG) is a classification defined by the United Nations Statistics Division. Its purpose is to “classify the purpose of transactions such as outlays on final consumption expenditure, intermediate consumption, gross capital formation and capital and current transfers, by general government” (from home page).
These functions are designed to be general enough to apply to the government of different countries. The accounts of each country in the United Nations are presented under these categories. The value of this is that the accounts of different countries can be compared.
Data was sourced from the UN site (raw access database from the UN) and extracted using the scripts found in the scripts directory of the source data package. In addition to the UN site, versions of COFOG can also be found on Eurostat with one advantage of the Eurostat data being the availability of additional languages (e.g. German).
No license specified but factual data and extraction and normalization of the csv file has been done by the Maintainer who places the material in the Public Domain under the PDDL.
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