Annual Consumer Price Index (CPI)

core

Files Size Format Created Updated License Source
2 285kB csv zip 7 months ago 3 months ago The World Bank
Annual Consumer Price Index (CPI) for most countries in the world when it has been measured. The reference year is 2005 (meaning the value of CPI for all countries is 100 and all other CPI values are relative to that year). Data The data comes from The World Bank and is collected from 1960 to read more
Download

Data Files

File Description Size Last changed Download
cpi 248kB csv (248kB) , json (620kB)
cpi_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 259kB zip (259kB)

cpi  

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
CPI 4 number CPI (where 2005=100)

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

# Get resources

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

curl -L https://datahub.io/core/cpi/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/cpi/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/cpi/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/cpi/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/cpi/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

Annual Consumer Price Index (CPI) for most countries in the world when it has been measured. The reference year is 2005 (meaning the value of CPI for all countries is 100 and all other CPI values are relative to that year).

Data

The data comes from The World Bank and is collected from 1960 to 2011. 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).

Preparation

It is parsed via the script cpi2datapackage.py, located in scripts.

usage: cpi2datapackage.py [-h] [-o filename] [source]

convert WorldBank CPI data to a data package resource

positional arguments:
  source                source file to generate output from

optional arguments:
  -h, --help            show this help message and exit
  -o filename, --output filename
                        define output filename

License

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/

Datapackage.json