Statistical Data and Metadata eXchange (SDMX) for the  Python data  ecosystem
********************************************************************************

:mod:`pandaSDMX` is an Apache 2.0-licensed `Python <http://www.python.org>`_ library that implements `SDMX <http://www.sdmx.org>`_ 2.1
(`ISO 17369:2013 <https://www.iso.org/standard/52500.html>`_), a format for
exchange of **statistical data and metadata** used by national statistical
agencies, central banks, and international organisations.

:mod:`pandaSDMX` can be used to:

- explore the data available from over 20 :doc:`data providers <sources>` such as the World Bank, BIS, ILO, ECB,  
  Eurostat, OECD, UNICEF and United Nations;
- parse data and metadata in SDMX-ML (XML) or SDMX-JSON formats—either:

  - from local and remote files, or
  - retrieved from pandasdmx web services, with query validation and caching;

- convert data and metadata into `pandas <http://pandas.pydata.org>`_ objects,
  for use with the analysis, plotting, and other tools in the Python data
  science ecosystem; 
  See also the **companion project 
  `intake_sdmx <https://intake_sdmx.readthedocs.io>`__**, 
  a plugin for the 
  `intake <https://intake_sdmx.readthedocs.io>`_ 
  data acquisition
  and distribution framework;
- apply the :doc:`SDMX Information Model <implementation>` to your own data;
- validate SDMX files against the official XML schemas;

…and much more.

Get started
===========

Assuming  a working copy of `Python 3.9 or higher <https://www.python.org/downloads/>`_ 
is installed on your system,
you can get :mod:`pandaSDMX` either   by typing from the  command prompt::

    $ pip install pandasdmx

or from a `conda environment <https://www.anaconda.com/>`_::

    $ conda install pandasdmx -c conda-forge     

Next, look at a
:doc:`usage example in only 10 lines of code <example>`. Then dive into the longer, narrative :doc:`walkthrough <walkthrough>` and finally peruse   the more advanced chapters as needed.

Bear in mind  that SDMX was designed to 
be flexible enough to accommodate almost *any* data.
This also means it is complex, with many abstract concepts for describing data,
metadata, and their relationships.
These are called the “SDMX Information Model” (IM).

.. _not-the-standard:

This documentation  gently explains the
functionality provided by :mod:`pandaSDMX` itself enabling you to make the 
best use of  all supported data sources. 
A decent understanding  of the IM is  conveyed in passing. 
However, if you got hooked,  follow the :doc:`list of resources and references <resources>`, 
or read the :doc:`API documentation <api>` and :doc:`implementation notes <implementation>` 
for the :mod:`pandasdmx.model` and :mod:`pandasdmx.message` modules that  implement the IM.

.. toctree::
   :maxdepth: 1

   example
   install
   walkthrough


:mod:`pandaSDMX` user guide
===========================

.. toctree::
   :maxdepth: 2

   sources
   api
   implementation
   howto
   whatsnew
   roadmap


Contributing to pandaSDMX and getting help
==========================================

- Report bugs, suggest features or view the source code on
  `GitHub <https://github.com/dr-leo/pandaSDMX>`_.
- The `sdmx-python <https://groups.google.com/forum/?hl=en#!forum/sdmx-python>`_ Google Group and mailing list may have answers for some questions.


.. toctree::

   resources
   glossary
   license

- :ref:`genindex`