Metadata-Version: 1.2
Name: pymrio
Version: 0.4.5
Summary: A python module for automating input output calculations and generating reports
Home-page: https://github.com/konstantinstadler/pymrio
Author: Konstantin Stadler
Author-email: konstantin.stadler@ntnu.no
License: UNKNOWN
Description: ############
        Pymrio
        ############
        
        Pymrio: Multi-Regional Input-Output Analysis in Python.
        
        .. image:: https://img.shields.io/pypi/v/pymrio.svg
            :target: https://pypi.python.org/pypi/pymrio/
        .. image:: https://anaconda.org/conda-forge/pymrio/badges/version.svg   
            :target: https://anaconda.org/conda-forge/pymrio
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        .. image:: https://readthedocs.org/projects/pymrio/badge/?version=latest
            :target: http://pymrio.readthedocs.io/en/latest/?badge=latest
            :alt: Documentation Status
        .. image:: https://img.shields.io/badge/License-GPL%20v3-blue.svg
            :target: https://www.gnu.org/licenses/gpl-3.0
        .. image:: https://zenodo.org/badge/21688312.svg
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        .. image:: https://img.shields.io/badge/code%20style-black-000000.svg
            :target: https://github.com/psf/black
        
        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/konstantinstadler/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/konstantinstadler/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/konstantinstadler/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_ and tutorials_ 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. 
        
        Contributing
        =============
        
        Want to contribute? Great!
        Please check `CONTRIBUTING.rst`_ if you want to help to improve Pymrio.
          
        .. _CONTRIBUTING.rst: https://github.com/konstantinstadler/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).
        
        .. _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/
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Utilities
Requires-Python: >=3.7.0
