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Expenditure on Research and Development(R&D)



Files Size Format Created Updated License Source
2 259kB csv zip 6 years ago 5 years ago Open Data Commons Public Domain Dedication and Licence (PDDL) UNESCO institute for statistics
Expenditure on Research and Development(R&D) by countries with indicators such as source of funds, type of R%&D activity, fields of R&D(medical and health sciences) since 1996. Data Data comes from UNESCO institute for statistics It consists of useful information about read more
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Data Files

Download files in this dataset

File Description Size Last changed Download
expenditure 148kB csv (148kB) , json (565kB)
expenditure-on-research-and-development_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 216kB zip (216kB)


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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
LOCATION 1 string (default) Country code
Country 2 string (default) Country name
TIME 3 year (default) Date in the form of %Y
Business enterprise 4 number (default) GERD - financed by Business enterprise (in '000 current PPP$)
Government 5 number (default) GERD - financed by Government (in '000 current PPP$)
Higher Education 6 number (default) GERD - financed by Higher education (in '000 current PPP$)
Private non-profit 7 number (default) GERD - financed by Private non-profit (in '000 current PPP$)
Rest of the world 8 number (default) GERD - financed by Rest of the world (abroad) (in '000 current PPP$)
Not specified source 9 string (default) GERD - financed by Not specified source (in '000 current PPP$)
Basic research 10 string (default) GERD - Basic research (in '000 current PPP$)
Applied research 11 string (default) GERD - Applied research (in '000 current PPP$)
Experimental development 12 string (default) GERD - Experimental development (in '000 current PPP$)
Not specified activities 13 string (default) GERD - Not specified activities (in '000 current PPP$)
Medical and health sciences 14 string (default) GERD - Medical and health sciences (in '000 current PPP$)

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

data get
data info core/expenditure-on-research-and-development
tree core/expenditure-on-research-and-development
# Get a list of dataset's resources
curl -L -s | grep path

# Get resources

curl -L

curl -L

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite", repos="")

json_file <- ''
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# get list of all resources:

# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
    path_to_file = json_data$resources$path[i]
    data <- read.csv(url(path_to_file))

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 = ''

# 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('')

# print list of all resources:

# print processed tabular data (if exists any)
for resource in package.resources:
    if resource.descriptor['datahub']['type'] == 'derived/csv':

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 = ''

// 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) {
  // 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
      // entire file as a buffer (be careful with large files!)
      const buffer = await file.buffer
      // print data

Read me

Expenditure on Research and Development(R&D) by countries with indicators such as source of funds, type of R%&D activity, fields of R&D(medical and health sciences) since 1996.


Data comes from UNESCO institute for statistics

It consists of useful information about how much is spent by government/the private sectors, type of activites like Basic research, Applied research, Experimental development for specific countries. Also, we added spendings for Medical and health sciences.


The main resource is located in archive/gerd.csv There are several steps have been done to get final data.

  • Extracted separately each resource by source of funds “Business enterprise”, “Government” and “Higher Education”, “Private non-profit”, “Rest of the world”, “Not specified source”
  • Extracted separately each resource by type of activities “Basic research”, “Applied research”, “Experimental development”, “Not specified activities”
  • Extracted by field of R&D “Medical and health sciences”
  • Merged them into one resource data/medical.csv using pandas library.

Process is recorded and automated in python script:

# to get final merged data which is `data/expenditure.csv`, run the following script


Public Domain Dedication and License (PDDL)


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