Annual inflation by GDP deflator and consumer prices

core

Files Size Format Created Updated License Source
3 5MB csv zip 7 months ago 2 months ago Open Data Commons Public Domain Dedication and License v1.0 The World Bank The World Bank
Inflation, GDP deflator (annual %) and Inflation, consumer prices (annual %) for most countries in the world when it has been measured. Data The data comes from The World Bank (CPI), The World Bank (GDP) and is collected from 1973 to 2014. There are some values missing from data so users of the read more
Download

Data Files

File Description Size Last changed Download
inflation-gdp 433kB csv (433kB) , json (1MB)
inflation-consumer 433kB csv (433kB) , json (1MB)
inflation_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 828kB zip (828kB)

inflation-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 Code 2 string
Year 3 year
Inflation 4 number

inflation-consumer  

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 Code 2 string
Year 3 year
Inflation 4 number

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Download CLI tool and use it with the datahub almost like you use git with the github:

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

# Get resources

curl -L https://datahub.io/core/inflation/r/0.csv

curl -L https://datahub.io/core/inflation/r/1.csv

curl -L https://datahub.io/core/inflation/r/2.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/inflation/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/inflation/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/inflation/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/inflation/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

Inflation, GDP deflator (annual %) and Inflation, consumer prices (annual %) for most countries in the world when it has been measured.

Data

The data comes from The World Bank (CPI), The World Bank (GDP) and is collected from 1973 to 2014. There are some values missing from data so users of the data will have to guess what should be in the empty slots.

The actual download happens via The World Bank’s API (with csv as the requested format) (CPI), The World Bank’s API (with csv as the requested format) (GDP).

Preparation

They are parsed via the script process.py located in scripts.

License

This Data Package is licensed by its maintainers under the Public Domain Dedication and License (PDDL).

Datapackage.json