############ Pymrio ############

Pymrio: Multi-Regional Input-Output Analysis in Python.

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What is it

Pymrio is an open source tool for analysing global environmentally extended multi-regional input-output tables (EE MRIOs). Pymrio aims to provide a high-level abstraction layer for global EE MRIO databases in order to simplify common EE MRIO data tasks. Pymrio includes automatic download functions and parsers for available EE MRIO databases like EXIOBASE_, WIOD_ and EORA26_. It automatically checks parsed EE MRIOs for missing data necessary for calculating standard EE MRIO accounts (such as footprint, territorial, impacts embodied in trade) and calculates all missing tables. Various data report and visualization methods help to explore the dataset by comparing the different accounts across countries.

Further functions include:

• analysis methods to identify where certain impacts occur
• modifying region/sector classification
• restructuring extensions
• export to various formats
• visualization routines and
• automated report generation

Where to get it

The full source code is available on Github at: https://github.com/IndEcol/pymrio

Pymrio is registered at PyPI and on the Anaconda Cloud. Install it by:

.. code:: bash

pip install pymrio --upgrade

or when using conda install it by

.. code:: bash

conda install -c conda-forge pymrio

or update to the latest version by

.. code:: bash

conda update -c conda-forge pymrio

The source-code of Pymrio available at the GitHub repo: https://github.com/IndEcol/pymrio

The master branch in that repo is supposed to be ready for use and might be ahead of the official releases. To install directly from the master branch use:

.. code:: bash

pip install git+https://github.com/IndEcol/pymrio@master

Quickstart

A small test mrio is included in the package.

To use it call

.. code:: python

import pymrio
test_mrio = pymrio.load_test()

The test mrio consists of six regions and eight sectors:

.. code:: python

print(test_mrio.get_sectors())
print(test_mrio.get_regions())

The test mrio includes tables flow tables and some satellite accounts. To show these:

.. code:: python

test_mrio.Z
test_mrio.emissions.F

However, some tables necessary for calculating footprints (like test_mrio.A or test_mrio.emissions.S) are missing. pymrio automatically identifies which tables are missing and calculates them:

.. code:: python

test_mrio.calc_all()

Now, all accounts are calculated, including footprints and emissions embodied in trade:

.. code:: python

test_mrio.A
test_mrio.emissions.D_cba
test_mrio.emissions.D_exp

To visualize the accounts:

.. code:: python

import matplotlib as plt
test_mrio.emissions.plot_account('emission_type1')
plt.show()

Everything can be saved with

.. code:: python

test_mrio.save_all('some/folder')

See the documentation_ , tutorials_ and Stadler 2021_ for further examples.

Tutorials

The documentation_ includes information about how to use pymrio for automatic downloading_ and parsing_ of the EE MRIOs EXIOBASE_, WIOD_, OECD_ and EORA26_ as well as tutorials_ for the handling, aggregating and analysis of these databases.

Citation

If you use Pymrio in your research, citing the article describing the package (Stadler 2021_) is very much appreciated.

.. _Stadler 2021: https://openresearchsoftware.metajnl.com/articles/10.5334/jors.251/

For the full bibtex key see CITATION_ file.

.. _CITATION: CITATION

Contributing

Want to contribute? Great! Please check CONTRIBUTING.rst_ if you want to help to improve Pymrio.

.. _CONTRIBUTING.rst: https://github.com/IndEcol/pymrio/blob/master/CONTRIBUTING.rst

Communication, issues, bugs and enhancements

Please use the issue tracker for documenting bugs, proposing enhancements and all other communication related to pymrio.

You can follow me on twitter_ to get the latest news about all my open-source and research projects (and occasionally some random retweets).

Research notice

Please note that this repository is participating in a study into
sustainability of open source projects. Data will be gathered about this
repository for approximately the next 12 months, starting from June
2021.

Data collected will include number of contributors, number of PRs, time
taken to close/merge these PRs, and issues closed.

For more information, please visit `the informational
page <https://sustainable-open-science-and-software.github.io/>`__ or
download the `participant information
sheet <https://sustainable-open-science-and-software.github.io/assets/PIS_sustainable_software.pdf>`__.


.. _twitter: https://twitter.com/kst_stadler

.. _downloading: http://pymrio.readthedocs.io/en/latest/notebooks/autodownload.html
.. _parsing: http://pymrio.readthedocs.io/en/latest/handling.html
.. _documentation: http://pymrio.readthedocs.io/en/latest/
.. _tutorials: http://pymrio.readthedocs.io/en/latest/handling.html

.. _EXIOBASE: http://www.exiobase.eu/
.. _WIOD: http://www.wiod.org/home
.. _OECD: https://www.oecd.org/sti/ind/inter-country-input-output-tables.htm
.. _EORA26: http://www.worldmrio.com/simplified/