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Releases: IndEcol/pymrio

Automated EXIBOASE download and characterization method

24 Feb 16:17
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Changelog

v0.4.3 (February 24, 2021)

New features


  • Added automatic downloader for EXIOBASE 3 files
  • Method for characterizing stressors (pymrio.Extension.characterize)

Bugfixes


  • Fixed: xlrd and numpy requirments for later pandas versions

Development


  • Switched from travis to github actions for testing and converage reports

Bugfix release

19 Nov 19:44
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Description

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, OECD ICIO 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.

Changelog - v0.4.2

Bugfixes

  • Fixed: OECD parsing bug caused by pandas update
  • Fixed: Missing inclusion of auxiliary data for exiobase 2
  • Fixed: Making python version explicit and update package requirements
  • Fixed: hard-coded OS specific path

Development

  • switched to black code style
  • updated travis.yml for testing different python versions
  • added github workflows for automated releases
  • switched to git trunk based development

Hotfix Release - EXIOBASE 3 zip parsing on windows

08 Oct 13:47
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Description

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, OECD ICIO 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.

Bugfixes

  • Fixed: Parsing EXIOBASE 3 from zip on Windows system
  • Fixed: Doc spelling

New features

  • The tutorial notebooks of the documentation are now also used for integration
    tests. See CONTIBUTING.rst for more infos.

Release 0.4.0

12 Aug 11:57
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Description

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, OECD ICIO 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.

New features

  • New parser and automatic downloader for the OECD-ICIO tables (2016 and 2018
    release)
  • Improved test coverage to over 90 %
  • Equality comparison for MRIO System and Extension

Bugfixes

  • Fixed some typos

Backward incompatible changes

  • Minimum python version changed to 3.7
  • The FY and SY matrixes has been renamed to F_Y and S_Y. Previously stored
    data, however, can still be read (FY/SY files are automatically parsed as F_Y
    and S_Y)

Hotfix Release 0.3.8

06 Nov 14:36
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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.


v0.3.8 (November 06, 2018)


Hotfix for two EXIOBASE 3 issues

  • FY in the raw files is named F_hh. F_hh now get automatically renamed to FY.
  • In the ixi tables of EXIOBASE 3 some tables had ISO3 country names. The parser now renames these names to the standard ISO2.

v0.3.7 (October 10, 2018)


New features

  • pymrio.parse_exiobase3, accepting the compressed archive files and extraced data (solves #26)
  • pymrio.archive for archiving MRIO databases into zipfiles (solves #26)
  • pymrio.load and pymrio.load_all can read data directly from a zipfile (solves #26)

Bugfixes

  • Calculate FY and SY when final demand impacts are available (fixes issue #28)
  • Ensures that mrio.x is a pandas DataFrame (fixes issue #24)
  • Some warning if a reset method would remove data beyond recovery by calc_all (see issue #23 discussion)

Removed functionality

  • Removed the Eora26 autodownloader b/c worldmrio.com needs a registration now (short time fix for #34)

Misc

  • pymrio now depends on python > 3.6
  • Stressed the issue driven development in CONTRIBUTING.rst

v0.3.6 (March 12, 2018)


Function get_index now has a switch to return dict
for direct input into pandas groupby function.

Included function to set index across dataframes.

Docs includes examples how to use pymrio with pandas groupby.

Improved test coverage.


v0.3.5 (Jan 17, 2018)


Added xlrd to requirements


v0.3.4 (Jan 12, 2018)


API breaking changes

  • Footprints and territorial accounts were renamed to "consumption based accounts" and "production based accounts": D_fp was renamed to D_cba and D_terr to D_pba

v0.3.3 (Jan 11, 2018)


Note: This includes all changes from 0.3 to 0.3.3

  • downloaders for EORA26 and WIOD

  • codebase fully pep8 compliant

  • restructured and extended the documentation

  • License changed to GNU GENERAL PUBLIC LICENSE v3

Dependencies

  • pandas minimal version changed to 0.22
  • Optional (for aggregation): country converter coco >= 0.6.3

API breaking changes

  • The format for saving MRIOs changed from csv + ini to csv + json. Use the method '_load_all_ini_based_io' to read a previously saved MRIO and than save it again to convert to the new save format.
  • method set_sectors(), set_regions() and set_Y_categories() renamed to rename_sectors() etc.
  • connected the aggregation function to the country_converter coco
  • removed previously deprecated method 'per_source'. Use 'diag_stressor' instead.

v0.2.2 (May 27, 2016)


Dependencies

  • pytest. For the unit tests.

Misc

  • Fixed filename error for the test system.
  • Various small bug fixes.
  • Preliminary EXIOBASE 3 parser.
  • Preliminary World Input-Output Database (WIOD) parser.

v0.2.1 (Nov 17, 2014)


Dependencies

  • pandas version > 0.15. This required some change in the xls reading within
    the parser.
  • pytest. For the unit tests.

Misc

  • Unit testing for all mathematical functions and a first system wide check.
  • Fixed some mistakes in the tutorials and readme

v0.2.0 (Sept 11, 2014)


API changes

  • IOSystem.reset() replaced by IOSystem.reset_all_to_flows()
  • IOSystem.reset_to_flows() and IOSystem.reset_to_coefficients() added
  • Version number attribute added
  • Parser for EXIOBASE like extensions (pymrio.parse_exio_ext) added.
  • plot_accounts now works also for for specific products (with parameter "sector")

Misc

  • Several bugfixes
  • Mainmodule split into several packages and submodules
  • Added 3rd tutorial
  • Added CHANGELOG

v0.1.0 (June 20, 2014)


Initial version

Release 0.3.7

22 Oct 13:24
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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.


v0.3.7 (October 10, 2018)


New features

  • pymrio.parse_exiobase3, accepting the compressed archive files and extraced data (solves #26)
  • pymrio.archive for archiving MRIO databases into zipfiles (solves #26)
  • pymrio.load and pymrio.load_all can read data directly from a zipfile (solves #26)

Bugfixes

  • Calculate FY and SY when final demand impacts are available (fixes issue #28)
  • Ensures that mrio.x is a pandas DataFrame (fixes issue #24)
  • Some warning if a reset method would remove data beyond recovery by calc_all (see issue #23 discussion)

Removed functionality

  • Removed the Eora26 autodownloader b/c worldmrio.com needs a registration now (short time fix for #34)

Misc

  • pymrio now depends on python > 3.6
  • Stressed the issue driven development in CONTRIBUTING.rst

v0.3.6 (March 12, 2018)


Function get_index now has a switch to return dict
for direct input into pandas groupby function.

Included function to set index across dataframes.

Docs includes examples how to use pymrio with pandas groupby.

Improved test coverage.


v0.3.5 (Jan 17, 2018)


Added xlrd to requirements


v0.3.4 (Jan 12, 2018)


API breaking changes

  • Footprints and territorial accounts were renamed to "consumption based accounts" and "production based accounts": D_fp was renamed to D_cba and D_terr to D_pba

v0.3.3 (Jan 11, 2018)


Note: This includes all changes from 0.3 to 0.3.3

  • downloaders for EORA26 and WIOD

  • codebase fully pep8 compliant

  • restructured and extended the documentation

  • License changed to GNU GENERAL PUBLIC LICENSE v3

Dependencies

  • pandas minimal version changed to 0.22
  • Optional (for aggregation): country converter coco >= 0.6.3

API breaking changes

  • The format for saving MRIOs changed from csv + ini to csv + json. Use the method '_load_all_ini_based_io' to read a previously saved MRIO and than save it again to convert to the new save format.
  • method set_sectors(), set_regions() and set_Y_categories() renamed to rename_sectors() etc.
  • connected the aggregation function to the country_converter coco
  • removed previously deprecated method 'per_source'. Use 'diag_stressor' instead.

v0.2.2 (May 27, 2016)


Dependencies

  • pytest. For the unit tests.

Misc

  • Fixed filename error for the test system.
  • Various small bug fixes.
  • Preliminary EXIOBASE 3 parser.
  • Preliminary World Input-Output Database (WIOD) parser.

v0.2.1 (Nov 17, 2014)


Dependencies

  • pandas version > 0.15. This required some change in the xls reading within
    the parser.
  • pytest. For the unit tests.

Misc

  • Unit testing for all mathematical functions and a first system wide check.
  • Fixed some mistakes in the tutorials and readme

v0.2.0 (Sept 11, 2014)


API changes

  • IOSystem.reset() replaced by IOSystem.reset_all_to_flows()
  • IOSystem.reset_to_flows() and IOSystem.reset_to_coefficients() added
  • Version number attribute added
  • Parser for EXIOBASE like extensions (pymrio.parse_exio_ext) added.
  • plot_accounts now works also for for specific products (with parameter "sector")

Misc

  • Several bugfixes
  • Mainmodule split into several packages and submodules
  • Added 3rd tutorial
  • Added CHANGELOG

v0.1.0 (June 20, 2014)


Initial version

Pymrio - regex aggregation of stressors

12 Mar 12:52
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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.


v0.3.6 (March 12, 2018)


Function get_index now has a switch to return dict
for direct input into pandas groupby function.

Included function to set index across dataframes.

Docs includes examples how to use pymrio with pandas groupby.

Improved test coverage.


v0.3.5 (Jan 17, 2018)


Added xlrd to requirements


v0.3.4 (Jan 12, 2018)


API breaking changes

  • Footprints and territorial accounts were renamed to "consumption based accounts" and "production based accounts": D_fp was renamed to D_cba and D_terr to D_pba

v0.3.3 (Jan 11, 2018)


Note: This includes all changes from 0.3 to 0.3.3

  • downloaders for EORA26 and WIOD

  • codebase fully pep8 compliant

  • restructured and extended the documentation

  • License changed to GNU GENERAL PUBLIC LICENSE v3

Dependencies

  • pandas minimal version changed to 0.22
  • Optional (for aggregation): country converter coco >= 0.6.3

API breaking changes

  • The format for saving MRIOs changed from csv + ini to csv + json. Use the method '_load_all_ini_based_io' to read a previously saved MRIO and than save it again to convert to the new save format.
  • method set_sectors(), set_regions() and set_Y_categories() renamed to rename_sectors() etc.
  • connected the aggregation function to the country_converter coco
  • removed previously deprecated method 'per_source'. Use 'diag_stressor' instead.

Updating requirements

17 Jan 09:20
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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.


v0.3.5 (Jan 17, 2018)


Added xlrd to requirements


v0.3.4 (Jan 12, 2018)


API breaking changes

  • Footprints and territorial accounts were renamed to "consumption based accounts" and "production based accounts": D_fp was renamed to D_cba and D_terr to D_pba

v0.3.3 (Jan 11, 2018)


Note: This includes all changes from 0.3 to 0.3.3

  • downloaders for EORA26 and WIOD

  • codebase fully pep8 compliant

  • restructured and extended the documentation

  • License changed to GNU GENERAL PUBLIC LICENSE v3

Dependencies

  • pandas minimal version changed to 0.22
  • Optional (for aggregation): country converter coco >= 0.6.3

API breaking changes

  • The format for saving MRIOs changed from csv + ini to csv + json. Use the method '_load_all_ini_based_io' to read a previously saved MRIO and than save it again to convert to the new save format.
  • method set_sectors(), set_regions() and set_Y_categories() renamed to rename_sectors() etc.
  • connected the aggregation function to the country_converter coco
  • removed previously deprecated method 'per_source'. Use 'diag_stressor' instead.

Renaming of D_fp and D_terr to D_cba and D_pba

12 Jan 17:13
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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.


v0.3.4 (Jan 12, 2018)


API breaking changes

  • Footprints and territorial accounts were renamed to "consumption based accounts" and "production based accounts": D_fp was renamed to D_cba and D_terr to D_pba

v0.3.3 (Jan 11, 2018)


Note: This includes all changes from 0.3 to 0.3.3

  • downloaders for EORA26 and WIOD

  • codebase fully pep8 compliant

  • restructured and extended the documentation

  • License changed to GNU GENERAL PUBLIC LICENSE v3

Dependencies

  • pandas minimal version changed to 0.22
  • Optional (for aggregation): country converter coco >= 0.6.3

API breaking changes

  • The format for saving MRIOs changed from csv + ini to csv + json. Use the method '_load_all_ini_based_io' to read a previously saved MRIO and than save it again to convert to the new save format.
  • method set_sectors(), set_regions() and set_Y_categories() renamed to rename_sectors() etc.
  • connected the aggregation function to the country_converter coco
  • removed previously deprecated method 'per_source'. Use 'diag_stressor' instead.

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

11 Jan 17:56
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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.

v0.3.3 (Jan 11, 2018)

Note: This includes all changes from 0.3 to 0.3.3

  • downloaders for EORA26 and WIOD

  • codebase fully pep8 compliant

  • restructured and extended the documentation

  • License changed to GNU GENERAL PUBLIC LICENSE v3

Dependencies

  • pandas minimal version changed to 0.22
  • Optional (for aggregation): country converter coco >= 0.6.3

API breaking changes

  • The format for saving MRIOs changed from csv + ini to csv + json. Use the method '_load_all_ini_based_io' to read a previously saved MRIO and than save it again to convert to the new save format.
  • method set_sectors(), set_regions() and set_Y_categories() renamed to rename_sectors() etc.
  • connected the aggregation function to the country_converter coco
  • removed previously deprecated method 'per_source'. Use 'diag_stressor' instead.