Purchasing power parity (PPP)

core

Files Size Format Created Updated License Source
2 1MB csv zip 1 week ago ODC-PDDL-1.0 PPP conversion factor, GDP (LCU per international $). World Bank, International Comparison Program database.
Purchasing power parity (PPP). Data are sourced from the World Bank, International Comparison Program database. One dataset is provided: PPP conversion factor, GDP (LCU per international $). Data Description > Purchasing power parity conversion factor is the number of units of a country's read more
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Data Files

File Description Size Last changed Download Other formats
ppp-gdp [csv] 163kB ppp-gdp [csv] ppp-gdp [json] (388kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 194kB datapackage_zip [zip]

ppp-gdp  

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

Field information

Field Name Order Type (Format) Description
Country 1 string
Country ID 2 string ISO 3166-1 alpha-2 code
Year 3 year Relevant year
PPP 4 number PPP conversion factor, GDP (LCU per international $)

datapackage_zip  

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

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Purchasing power parity (PPP). Data are sourced from the World Bank, International Comparison Program database. One dataset is provided: PPP conversion factor, GDP (LCU per international $).

Data

Description

Purchasing power parity conversion factor is the number of units of a country’s currency required to buy the same amounts of goods and services in the domestic market as U.S. dollar would buy in the United States.*

Citations

  1. PPP conversion factor, GDP (LCU per international $). World Bank, International Comparison Program database.

Sources

Data Preparation

Requirements

Data preparation requires Python 2. Required external Python modules are listed in the requirements.txt file in this directory.

Processing

Run the following script from this directory to download and process the data:

make data

Resources

The raw data are output to ./tmp. The processed data are output to ./data.

License

ODC-PDDL-1.0

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/

Notes

Refer to the terms of use of the source dataset for any specific restrictions on using these data in a public or commercial product.

Import into your tool

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

install.packages("jsonlite")
library("jsonlite")

json_file <- "http://datahub.io/core/ppp/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources[[1]]$path
data <- read.csv(url(path_to_file))
print(data)

In order to work with Data Packages in Pandas you need to install the Frictionless Data data package library and the pandas extension:

pip install datapackage
pip install jsontableschema-pandas

To get the data run following code:

import datapackage

data_url = "http://datahub.io/core/ppp/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# data frames available (corresponding to data files in original dataset)
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

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('http://datahub.io/core/ppp/datapackage.json')

# get list of resources:
resources = package.descriptor['resources']
resourceList = [resources[x]['name'] for x in range(0, len(resources))]
print(resourceList)

data = package.resources[0].read()
print(data)

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 = 'http://datahub.io/core/ppp/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 the first data file in this dataset
  const file = dataset.resources[0]
  // Get a raw stream
  const stream = await file.stream()
  // entire file as a buffer (be careful with large files!)
  const buffer = await file.buffer
})()

Install the datapackage library created specially for Ruby language using gem:

gem install datapackage

Now get the dataset and read the data:

require 'datapackage'

path = 'http://datahub.io/core/ppp/datapackage.json'

package = DataPackage::Package.new(path)
# So package variable contains metadata. You can see it:
puts package

# Read data itself:
resource = package.resources[0]
data = resource.read
puts data
Datapackage.json