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Cash Surplus/Deficit, in % of GDP, from 1990 to 2013.

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core

Files Size Format Created Updated License Source
2 149kB csv zip 1 year ago 9 months ago Open Data Commons Public Domain Dedication and License v1.0
Repository of the data package of the Cash Surplus or Deficit, in percentage of GDP, from 1990 to 2013. Data Data comes originally from World Bank. Preparation To update the current package from its source, simply run make from your terminal. It should update the package automatically, unless read more
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Data Files

Download files in this dataset

File Description Size Last changed Download
cash-surp-def 252kB csv (252kB) , json (452kB)
cash-surplus-deficit_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 125kB zip (125kB)

cash-surp-def  

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

Field information

Field Name Order Type (Format) Description
Country Name 1 string
Country Code 2 string
Year 3 year
Value 4 number

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

data get https://datahub.io/core/cash-surplus-deficit
data info core/cash-surplus-deficit
tree core/cash-surplus-deficit
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/cash-surplus-deficit/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/core/cash-surplus-deficit/r/0.csv

curl -L https://datahub.io/core/cash-surplus-deficit/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/cash-surplus-deficit/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/cash-surplus-deficit/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/cash-surplus-deficit/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/cash-surplus-deficit/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

Repository of the data package of the Cash Surplus or Deficit, in percentage of GDP, from 1990 to 2013.

Data

Data comes originally from World Bank.

Preparation

To update the current package from its source, simply run make from your terminal. It should update the package automatically, unless there were some changes in the source.

License

All data is licensed under the Open Data Commons Public Domain Dedication and License. All code is licensed under the MIT/BSD license.

Note that while no credit is formally required a link back or credit to Rufus Pollock and the Open Knowledge Foundation is much appreciated.

Datapackage.json

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