Annual Consumer Price Index (CPI)

core

Files Size Format Created Updated License Source
2 2MB csv zip 1 month 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
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Data Files

File Description Size Last changed Download Other formats
cpi [csv] 248kB cpi [csv] cpi [json] (620kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 285kB datapackage_zip [zip]

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)

datapackage_zip  

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

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).

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

Usage of cpi2datapackage.py

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

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/cpi/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources$path[1][1]
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/cpi/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/cpi/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/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 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/cpi/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