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Price level ratio of PPP conversion factor (GDP) to market exchange rate

world-bank

Files Size Format Created Updated License Source
2 1MB csv zip 1 year ago 1 year ago CC-BY-4.0
Purchasing power parity conversion factor is the number of units of a countrys currency required to buy the same amount of goods and services in the domestic market as a U.S. dollar would buy in the United States. The ratio of PPP conversion factor to market exchange rate is the result obtained by read more
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Data Files

Download files in this dataset

File Description Size Last changed Download
data Indicator data 183kB csv (183kB) , json (458kB)
pa_nus_pppc_rf_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 184kB zip (184kB)

Indicator data [data]  

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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 or Region name
Country Code 2 string ISO 3-digit ISO code extended to include regional codes e.g. EUR, ARB etc
Year 3 year Year
Value 4 number Purchasing power parity conversion factor is the number of units of a countrys currency required to buy the same amount of goods and services in the domestic market as a U.S. dollar would buy in the United States. The ratio of PPP conversion factor to market exchange rate is the result obtained by dividing the PPP conversion factor by the market exchange rate. The ratio, also referred to as the national price level, makes it possible to compare the cost of the bundle of goods that make up gross domestic product (GDP) across countries. It tells how many dollars are needed to buy a dollars worth of goods in the country as compared to the United States. PPP conversion factors are based on the 2011 ICP round.

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

data get https://datahub.io/world-bank/pa.nus.pppc.rf
data info world-bank/pa.nus.pppc.rf
tree world-bank/pa.nus.pppc.rf
# Get a list of dataset's resources
curl -L -s https://datahub.io/world-bank/pa.nus.pppc.rf/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/world-bank/pa.nus.pppc.rf/r/0.csv

curl -L https://datahub.io/world-bank/pa.nus.pppc.rf/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/world-bank/pa.nus.pppc.rf/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/world-bank/pa.nus.pppc.rf/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/world-bank/pa.nus.pppc.rf/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/world-bank/pa.nus.pppc.rf/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

Purchasing power parity conversion factor is the number of units of a countrys currency required to buy the same amount of goods and services in the domestic market as a U.S. dollar would buy in the United States. The ratio of PPP conversion factor to market exchange rate is the result obtained by dividing the PPP conversion factor by the market exchange rate. The ratio, also referred to as the national price level, makes it possible to compare the cost of the bundle of goods that make up gross domestic product (GDP) across countries. It tells how many dollars are needed to buy a dollars worth of goods in the country as compared to the United States. PPP conversion factors are based on the 2011 ICP round.

Datapackage.json

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