pyam
pyam: a Python Package for the Analysis and Visualization of Models of the Interaction of Climate, Human, and Environmental Systems - Published in JOSS (2019)
Science Score: 100.0%
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✓DOI references
Found 14 DOI reference(s) in README and JOSS metadata -
✓Academic publication links
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3 of 33 committers (9.1%) from academic institutions -
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✓JOSS paper metadata
Published in Journal of Open Source Software
Keywords
Keywords from Contributors
Repository
Analysis & visualization of energy & climate scenarios
Basic Info
- Host: GitHub
- Owner: IAMconsortium
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://pyam-iamc.readthedocs.io/
- Size: 58.3 MB
Statistics
- Stars: 263
- Watchers: 12
- Forks: 126
- Open Issues: 97
- Releases: 36
Topics
Metadata Files
README.md
pyam: analysis & visualization
of integrated-assessment and macro-energy scenarios
Overview and scope
The open-source Python package 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 models, macro-energy scenarios, energy systems analysis, and sectoral studies.
The comprehensive documentation is hosted on Read the Docs!
Key features
- Simple analysis of scenario timeseries data with an interface similar in feel & style to the widely used pandas.DataFrame
- Advanced visualization and plotting functions (see the gallery)
- Scripted validation and processing of scenario data and results
Timeseries types & data formats
Yearly data
The pyam package was initially developed to work with the IAMC template, a timeseries format for yearly data developed and used by the Integrated Assessment Modeling Consortium (IAMC).
| model | scenario | region | variable | unit | 2005 | 2010 | 2015 | |-----------|--------------|------------|----------------|----------|----------|----------|----------| | MESSAGE | CD-LINKS 400 | World | Primary Energy | EJ/y | 462.5 | 500.7 | ... | | ... | ... | ... | ... | ... | ... | ... | ... |
An illustration of the IAMC template using a scenario
from the CD-LINKS project
via the The IAMC 1.5°C Scenario Explorer
Subannual time resolution
The package also supports timeseries data with a sub-annual time resolution: - Continuous-time data using the Python datetime format - "Representative timeslices" (e.g., "winter-night", "summer-day") using the pyam extra-columns feature
Read the docs for more information about the pyam data model or look at the data-table tutorial to see how to cast from a variety of timeseries formats to a pyam.IamDataFrame.
Installation
pip
[!WARNING] The pyam package is distributed on https://pypi.org under the name pyam-iamc.
https://pypi.org/project/pyam-iamc/
Please install using
pip install pyam-iamc
conda
https://anaconda.org/conda-forge/pyam
Please install using
conda install pyam
install from source
To install from source (including all dependencies) after cloning this repository, run
pip install --editable .[tests,optional_io_formats,tutorials]
To check that the package was installed correctly, run
pytest tests
Tutorials
An introduction to the basic functions is shown in the "first-steps" notebook.
All tutorials are available in rendered format (i.e., with output) as part of the online documentation. The source code of the tutorials notebooks is available in the folder docs/tutorials of this repository.
Documentation
The comprehensive documentation is hosted on Read the Docs.
The documentation pages can be built locally, refer to the instruction in docs/README.
Authors & Contributors
This package was initiated and is currently maintained by Matthew Gidden (@gidden) and Daniel Huppmann (@danielhuppmann). See the complete list of contributors.
The core maintenance of the package is done by the Scenario Services & Scientific Software research theme at the IIASA Energy, Climate, and Enviroment program. Visit https://software.ece.iiasa.ac.at for more information.
Scientific publications
The following manuscripts describe the pyam package at specific stages of development.
The source documents are available in the manuscripts folder of the GitHub repository.
Release v1.0 (June 2021)
Published to mark the first major release of the pyam package.
Daniel Huppmann, Matthew Gidden, Zebedee Nicholls, Jonas Hörsch, Robin Lamboll, Paul Natsuo Kishimoto, Thorsten Burandt, Oliver Fricko, Edward Byers, Jarmo Kikstra, Maarten Brinkerink, Maik Budzinski, Florian Maczek, Sebastian Zwickl-Bernhard, Lara Welder, Erik Francisco Alvarez Quispe, and Christopher J. Smith. pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios. Open Research Europe, 2021. doi: 10.12688/openreseurope.13633.2
Release v0.1.2 (November 2018)
Published following the successful application of pyam in the IPCC SR15 and the Horizon 2020 CRESCENDO project.
Matthew Gidden and Daniel Huppmann. pyam: a Python package for the analysis and visualization of models of the interaction of climate, human, and environmental systems. Journal of Open Source Software (JOSS), 4(33):1095, 2019. doi: 10.21105/joss.01095.
License
Copyright 2017-2024 IIASA and the pyam developer team
The pyam package is licensed
under the Apache License, Version 2.0 (the "License");
see LICENSE and NOTICE for details.
Owner
- Name: Integrated Assessment Modeling Consortium (IAMC)
- Login: IAMconsortium
- Kind: organization
- Website: https://www.iamconsortium.org
- Twitter: IAMConsortium
- Repositories: 4
- Profile: https://github.com/IAMconsortium
JOSS Publication
pyam: a Python Package for the Analysis and Visualization of Models of the Interaction of Climate, Human, and Environmental Systems
Authors
International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria
International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria
Editor
Lindsey Heagy
Tags
Visualization Integrated Assessment Models Simple Climate Models Climate Change Greenhouse GasesCitation (CITATION.cff)
cff-version: 1.1.0
message: "If you use this package, please cite the corresponding manuscript in Open Research Europe."
title: "pyam: analysis and visualization of integrated-assessment and macro-energy scenarios"
repository: https://github.com/iamconsortium/pyam
version: 1.0
license: Apache-2.0
journal: Open Research Europe
doi: 10.12688/openreseurope.13633.2
authors:
- family-names: Huppmann
given-names: Daniel
orcid: https://orcid.org/0000-0002-7729-7389
- family-names: Gidden
given-names: Matthew J.
orcid: https://orcid.org/0000-0003-0687-414X
- family-names: Nicholls
given-names: Zebedee
orcid: https://orcid.org/0000-0002-4767-2723
- family-names: Hörsch
given-names: Jonas
orcid: https://orcid.org/0000-0001-9438-767X
- family-names: Lamboll
given-names: Robin D.
orcid: https://orcid.org/0000-0002-8410-037X
- family-names: Kishimoto
given-names: Paul Natsuo
- family-names: Burandt
given-names: Thorsten
- family-names: Fricko
given-names: Oliver
- family-names: Byers
given-names: Edward
- family-names: Kikstra
given-names: Jarmo S.
orcid: https://orcid.org/0000-0001-9405-1228
- family-names: Brinkerink
given-names: Maarten
- family-names: Budzinski
given-names: Maik
orcid: https://orcid.org/0000-0003-2879-1193
- family-names: Maczek
given-names: Florian
- family-names: Zwickl-Bernhard
given-names: Sebastian
- family-names: Welder
given-names: Lara
- family-names: Alvarez Quispe
given-names: Erik Francisco
orcid: https://orcid.org/0000-0003-3862-9747
- family-names: Smith
given-names: Christopher J.
keywords:
- integrated assessment
- energy systems
- macro-energy
- modelling
- scenario analysis
- data visualisation
- Python package
GitHub Events
Total
- Create event: 9
- Release event: 2
- Issues event: 7
- Watch event: 27
- Delete event: 4
- Issue comment event: 49
- Push event: 22
- Pull request review comment event: 34
- Pull request review event: 31
- Pull request event: 43
- Fork event: 7
Last Year
- Create event: 9
- Release event: 2
- Issues event: 9
- Watch event: 27
- Delete event: 4
- Issue comment event: 49
- Push event: 23
- Pull request review comment event: 34
- Pull request review event: 31
- Pull request event: 45
- Fork event: 7
Committers
Last synced: 5 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Daniel Huppmann | dh@d****t | 440 |
| Matthew Gidden | m****n@g****m | 113 |
| Zeb Nicholls | z****s@c****g | 21 |
| Jonas Hörsch | j****h@c****g | 17 |
| Rlamboll | r****l@h****k | 8 |
| Nikolay Kushin | z****h@g****m | 7 |
| Philip Hackstock | 2****k | 6 |
| Fridolin Glatter | 8****2 | 5 |
| OFR-IIASA | f****o@i****t | 4 |
| pjuergens | 7****s | 3 |
| dependabot[bot] | 4****] | 3 |
| Pietro Monticone | 3****e | 3 |
| Maik Budzinski | 5****z | 3 |
| Jarmo Kikstra | 4****a | 3 |
| Edward Byers | b****s@i****t | 3 |
| David Almeida | 5****a | 2 |
| Mathias Hauser | m****e | 2 |
| Paul Natsuo Kishimoto | m****l@p****e | 2 |
| dependabot-preview[bot] | 2****] | 2 |
| rossursino | 4****o | 1 |
| lumbric | l****c@g****m | 1 |
| Thorsten Burandt | 2****t | 1 |
| Suvayu Ali | s****u | 1 |
| Philipp S. Sommer | C****p | 1 |
| Michael Pimmer | b****b@f****t | 1 |
| Linh Ho | 4****o | 1 |
| Laura Wienpahl | 5****n | 1 |
| Karthikeyan Singaravelan | t****i@g****m | 1 |
| Kamil | 3****5 | 1 |
| Jan Ivar Korsbakken | j****n@g****m | 1 |
| and 3 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 280
- Total pull requests: 636
- Average time to close issues: 4 months
- Average time to close pull requests: 11 days
- Total issue authors: 55
- Total pull request authors: 37
- Average comments per issue: 2.58
- Average comments per pull request: 3.04
- Merged pull requests: 531
- Bot issues: 0
- Bot pull requests: 16
Past Year
- Issues: 7
- Pull requests: 32
- Average time to close issues: 15 days
- Average time to close pull requests: 17 days
- Issue authors: 5
- Pull request authors: 8
- Average comments per issue: 1.86
- Average comments per pull request: 1.44
- Merged pull requests: 17
- Bot issues: 0
- Bot pull requests: 3
Top Authors
Issue Authors
- danielhuppmann (95)
- gidden (52)
- znicholls (19)
- Rlamboll (16)
- phackstock (13)
- byersiiasa (11)
- pjuergens (7)
- khaeru (6)
- stefaneidelloth (4)
- l-welder (3)
- jkikstra (2)
- glatterf42 (2)
- willu47 (2)
- maxtav (2)
- sandrinecharousset (2)
Pull Request Authors
- danielhuppmann (408)
- gidden (105)
- znicholls (38)
- coroa (22)
- dependabot[bot] (17)
- glatterf42 (11)
- phackstock (8)
- Rlamboll (8)
- quant12345 (8)
- zikolach (8)
- dependabot-preview[bot] (7)
- dc-almeida (6)
- OFR-IIASA (4)
- LinhHo (4)
- pjuergens (4)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 4
-
Total downloads:
- pypi 30,238 last-month
- Total docker downloads: 8
-
Total dependent packages: 16
(may contain duplicates) -
Total dependent repositories: 27
(may contain duplicates) - Total versions: 131
- Total maintainers: 2
pypi.org: pyam-iamc
Analysis & visualization of integrated-assessment scenarios
- Homepage: https://github.com/IAMconsortium/pyam
- Documentation: https://pyam-iamc.readthedocs.io
- License: Apache-2.0
-
Latest release: 3.0.0
published about 1 year ago
Rankings
Maintainers (2)
proxy.golang.org: github.com/iamconsortium/pyam
- Documentation: https://pkg.go.dev/github.com/iamconsortium/pyam#section-documentation
- License: apache-2.0
-
Latest release: v3.0.0+incompatible
published about 1 year ago
Rankings
proxy.golang.org: github.com/IAMconsortium/pyam
- Documentation: https://pkg.go.dev/github.com/IAMconsortium/pyam#section-documentation
- License: apache-2.0
-
Latest release: v3.0.0+incompatible
published about 1 year ago
Rankings
conda-forge.org: pyam
The open-source Python package **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 models, macro-energy scenarios, energy systems analysis, and sectoral studies. **Key features** - Simple analysis of scenario timeseries data with an interface similar in feel & style to the widely used [pandas.DataFrame](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html) - Advanced visualization and plotting functions (see the [gallery](https://pyam-iamc.readthedocs.io/en/stable/gallery/index.html)) - Scripted validation and processing of scenario data and results
- Homepage: https://pyam-iamc.readthedocs.io/
- License: Apache-2.0
-
Latest release: 1.6.0
published over 3 years ago
Rankings
Dependencies
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- psf/black stable composite