weo 0.5.1

Python client to download IMF World Economic Outlook (WEO) dataset as pandas dataframes.

weo-reader

This is a Python client to download IMF World Economic Outlook Report dataset and use its data as pandas dataframes.

You can download WEO releases by year and month and explore the dataset.

Install

The program uses Python 3.7. To install weo use:

pip install weo

Download data

You need to save data as a local file before use. Download WEO country data from IMF web site as shown below:

import weo

weo.download(2019, "Oct", filename="weo.csv")

You can access WEO releases starting October 2007 with this client. WEO is normally released in April and October, one exception is September 2011. The release is referenced by number (1 or 2) or month 'Apr', 'Oct' and in 2011 - 'Sep'. C

Your can list all years and releases available for download with weo.all_releases(). Combine it to create local dataset of WEO vintages from 2007 to present:

    from weo import all_releases

    for (year, release) in all_releases():
      download(year, release, directory='weo_data') 

Note that folder 'weo_data' must exist for this script to run.

Inspect data

Use WEO class to view and extract data. WEO is a wrapper around a pandas dataframe that ensures proper data import and easier access and slicing of data.

The dataset is year-variable-country-value cube, you can fix any dimension to get a table of values.

Try code below:

from weo import WEO

w = WEO("weo.csv")

What variables and measurements are inside?

# variable listing
w.variables()

# units
w.units()
w.units("Gross domestic product, current prices")

# variable codesß
w.codes
w.from_code("LUR")

# countries
w.countries("United")      # Dataframe with United Arab Emirates, United Kingdom
                           # and United States
w.iso_code3("Netherlands") # 'NLD'

See some data:

w.get("General government gross debt", "Percent of GDP")
w.getc("NGDP_RPCH")
w.country("DEU", 2018)

Plot a chart with largest economies in 2024 (current prices):

(w.gdp_usd(2024)
  .dropna()
  .sort_values()
  .tail(12)
  .plot
  .barh(title="GDP by country, USD bln (2024)")
)

Alternative data sources

1. If you need the latest data as time series and not the vintages of WEO releases, and you know variables that you are looking for, dbnomics is a good choice:

• https://db.nomics.world/IMF/WEO
• https://db.nomics.world/IMF/WEOAGG

Small example:

from dbnomics import fetch_series_by_api_link
ts1 = fetch_series_by_api_link("https://api.db.nomics.world/v22/"
                               "series/IMF/WEO/DEU.NGDPRPC"
                               "?observations=1")

2. Similar dataset, not updated since 2018, but with earlier years: https://github.com/datasets/imf-weo

Development notes

• You can download the WEO file in command line with curl command:

       curl -o weo.csv https://www.imf.org/-/media/Files/Publications/WEO/WEO-Database/2020/02/WEOOct2020all.x

• WEOOct2019all.xls from the web site is really a CSV file, not an Excel file.
• There is an update of GDP figures in June 2020, but the file structure is incompatible with regular releases.
• Prior to 2020 URL was https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/WEOOct2019all.xls