Annual inflation by GDP deflator and consumer prices

core

Files Size Format Created Updated License Source
3 8MB csv zip 2 days ago 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 Other formats
inflation-gdp [csv] 382kB inflation-gdp [csv] inflation-gdp [json] (382kB)
inflation-consumer [csv] 307kB inflation-consumer [csv] inflation-consumer [json] (307kB)
inflation_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 729kB inflation_zip [zip]

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

inflation_zip  

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

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).

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

Import into your tool

In order to use Data Package in R follow instructions below:

install.packages("devtools")
library(devtools)
install_github("hadley/readr")
install_github("ropenscilabs/jsonvalidate")
install_github("ropenscilabs/datapkg")

#Load client
library(datapkg)

#Get Data Package
datapackage <- datapkg_read("https://pkgstore.datahub.io/core/inflation/latest")

#Package info
print(datapackage)

#Open actual data in RStudio Viewer
View(datapackage$data$"inflation-gdp")
View(datapackage$data$"inflation-consumer")
View(datapackage$data$"inflation_zip")

Tested with Python 3.5.2

To generate Pandas data frames based on JSON Table Schema descriptors we have to install jsontableschema-pandas plugin. To load resources from a data package as Pandas data frames use datapackage.push_datapackage function. Storage works as a container for Pandas data frames.

In order to work with Data Packages in Pandas you need to install our packages:

$ pip install datapackage
$ pip install jsontableschema-pandas

To get Data Package run following code:

import datapackage

data_url = "https://pkgstore.datahub.io/core/inflation/latest/datapackage.json"

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

# to see datasets in this package
storage.buckets

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

In order to work with Data Packages in Python you need to install our packages:

$ pip install datapackage

To get Data Package into your Python environment, run following code:

import datapackage

dp = datapackage.DataPackage('https://pkgstore.datahub.io/core/inflation/latest/datapackage.json')

# see metadata
print(dp.descriptor)

# get list of csv files
csvList = [dp.resources[x].descriptor['name'] for x in range(0,len(dp.resources))]
print(csvList) # ["resource name", ...]

# access csv file by the index starting 0
print(dp.resources[0].data)

To use this dataset in JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use code snippet below:

  const {Dataset} = require('data.js')

  const path = 'https://pkgstore.datahub.io/core/inflation/latest/datapackage.json'

  const dataset = Dataset.load(path)

  // get a data file in this dataset
  const file = dataset.resources[0]
  const data = file.stream()

In order to work with Data Packages in SQL you need to install our packages:

$ pip install datapackage
$ pip install jsontableschema-sql
$ pip install sqlalchemy

To import Data Package to your SQLite Database, run following code:

import datapackage
from sqlalchemy import create_engine

data_url = 'https://pkgstore.datahub.io/core/inflation/latest/datapackage.json'
engine = create_engine('sqlite:///:memory:')

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

# to see datasets in this package
storage.buckets

# to execute sql command (assuming data is in "data" folder, name of resource is data and file name is data.csv)
storage._Storage__connection.execute('select * from data__data___data limit 1;').fetchall()

# description of the table columns
storage.describe('data__data___data')
Datapackage.json