**pyam**: analysis and visualization of integrated-assessment scenarios
=======================================================================

Release v\ |version|.

|license| |pypi| |conda| |latest|

|pytest-38| |pytest-37| |codecov| |rtd|

|joss| |doi|

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Overview
--------

The open-source Python package |pyam| :cite:`Gidden:2019:pyam`
provides a suite of tools and functions for analyzing and visualizing
input data (i.e., assumptions/parametrization) 
and results (model output) of integrated-assessment scenarios,
energy systems analysis, and sectoral studies.

Key features:
~~~~~~~~~~~~~

 - Simple analysis of timeseries data in the IAMC format (more about it `here`_) |br|
   with an interface similar in feel & style to the widely
   used :class:`pandas.DataFrame`
 - Advanced visualization and plotting functions (see the `gallery`_)
 - Features for scripted validation & processing of scenario data
   and results

The source code for |pyam| is available on `Github`_.

.. _`here`:
   data.html

.. _`gallery`:
   gallery/index.html

.. _`Github`:
   https://github.com/IAMconsortium/pyam

Table of Contents
-----------------

.. toctree::
   :maxdepth: 2

   install
   authors
   contributing
   data
   tutorials
   gallery/index
   api

Copyright & License
-------------------

The development of the |pyam| package was started at the IIASA Energy Program,
with contributions from a number of `individuals & institutions`_ over the years.

The package is available under the open-source `Apache License`_.
Refer to the `NOTICE`_ in the GitHub repository for more information.

.. _individuals & institutions: authors.html

.. _Apache License: http://www.apache.org/licenses/LICENSE-2.0.html

.. _NOTICE: https://github.com/IAMconsortium/pyam/blob/master/NOTICE.md

Scientific reference
--------------------

.. bibliography:: _bib/index.bib
   :style: plain
   :all: