IMF World Economic Outlook Database

core

Files Size Format Created Updated License Source
3 65MB csv zip 1 week ago PDDL-1.0 IMF
IMF World Economic Outlook (WEO) database. The [IMF World Economic Outlook][weo] is a twice-yearly survey by IMF staff that presents IMF staff economists' analyses of global economic developments during the near and medium term. Associated with the report is the [World Economic read more
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Data Files

File Description Size Last changed Download Other formats
indicators [csv] 47kB indicators [csv] indicators [json] (49kB)
values [csv] 13MB values [csv] values [json] (27MB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 5MB datapackage_zip [zip]

indicators  

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

Field information

Field Name Order Type (Format) Description
id 1 string
title 2 string
description 3 string
units 4 string
scale 5 string

values  

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
Indicator 2 string
Year 3 integer
Value 4 string

datapackage_zip  

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

Read me

IMF World Economic Outlook (WEO) database. The IMF World Economic Outlook is a twice-yearly survey by IMF staff that presents IMF staff economists’ analyses of global economic developments during the near and medium term. Associated with the report is the World Economic Outlook Database, a country-level dataset of major macro-economic variables (GDP, Unemployment, Debt etc). It is the data from that database which is provided here.

Data

The source database is made of annual values for each country on 45 indicators since 1980. In addition the database includes the IMF projects approximately 6 years into the future.

We extract this data and normalize into 2 files:

  • Indicators - data/indicators.csv - the list of indicators
  • Values - data/values.csv - set of values for each indicator, country, year tuple.
  • Country - ‘data/country.csv’ - set of value for mapping each ISO country code, WEO country code, and CLDR English Name

Sources

Note the XLS files actual turn out to be tsv files!

Preparation

Code to extract the data from the source WEO Database is in the scripts directory.

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

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