Data Science for Energy System Modelling
Find practical introductions to many Python packages that are useful for dealing with energy data and building energy system modells.
https://github.com/fneum/data-science-for-esm
Category: Sustainable Development
Sub Category: Education
Keywords
data-science energy energy-data energy-system-modelling
Keywords from Contributors
energy-system-model energy-system optimal-power-flow optimisations power-systems-analysis energy-transition climate-change parallel power wind
Last synced: about 22 hours ago
JSON representation
Repository metadata
- Host: GitHub
- URL: https://github.com/fneum/data-science-for-esm
- Owner: fneum
- License: mit
- Created: 2022-08-30T13:44:48.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-02-03T17:36:15.000Z (3 months ago)
- Last Synced: 2025-04-25T11:43:33.054Z (2 days ago)
- Topics: data-science, energy, energy-data, energy-system-modelling
- Language: Jupyter Notebook
- Homepage: https://fneum.github.io/data-science-for-esm/intro.html
- Size: 163 MB
- Stars: 82
- Watchers: 6
- Forks: 48
- Open Issues: 2
- Releases: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
README.md
Data Science for Energy System Modelling
Course at TU Berlin to learn energy system modelling with data.
Usage
Building the book
If you'd like to develop and/or build the Data Science for Energy System Modelling book, you should:
- Clone this repository
- Run
pip install -r requirements.txt(it is recommended you do this within a virtual environment) - (Optional) Edit the books source files located in the
data-science-for-esm/directory - Run
jupyter-book clean data-science-for-esm/to remove any existing builds - Run
jupyter-book build data-science-for-esm/
A fully-rendered HTML version of the book will be built in data-science-for-esm/_build/html/.
Hosting the book
Please see the Jupyter Book documentation to discover options for deploying a book online using services such as GitHub, GitLab, or Netlify.
For GitHub and GitLab deployment specifically, the cookiecutter-jupyter-book includes templates for, and information about, optional continuous integration (CI) workflow files to help easily and automatically deploy books online with GitHub or GitLab. For example, if you chose github for the include_ci cookiecutter option, your book template was created with a GitHub actions workflow file that, once pushed to GitHub, automatically renders and pushes your book to the gh-pages branch of your repo and hosts it on GitHub Pages when a push or pull request is made to the main branch.
Contributors
We welcome and recognize all contributions. You can see a list of current contributors in the contributors tab.
Credits
This project is created using the excellent open source Jupyter Book project and the executablebooks/cookiecutter-jupyter-book template.
Owner metadata
- Name: Fabian Neumann
- Login: fneum
- Email:
- Kind: user
- Description: Energy System Modeller at Technische Universität Berlin
- Website: https://fneum.org/
- Location: Berlin
- Twitter: fneum_
- Company: TU Berlin
- Icon url: https://avatars.githubusercontent.com/u/29101152?u=fad9b930db1213a472aea2c24daa6812c06fdb7d&v=4
- Repositories: 32
- Last ynced at: 2025-04-21T22:39:42.147Z
- Profile URL: https://github.com/fneum
GitHub Events
Total
- Watch event: 13
- Push event: 4
- Fork event: 4
Last Year
- Watch event: 13
- Push event: 4
- Fork event: 4
Committers metadata
Last synced: 6 days ago
Total Commits: 117
Total Committers: 5
Avg Commits per committer: 23.4
Development Distribution Score (DDS): 0.231
Commits in past year: 6
Committers in past year: 2
Avg Commits per committer in past year: 3.0
Development Distribution Score (DDS) in past year: 0.167
| Name | Commits | |
|---|---|---|
| Fabian Neumann | f****n@o****e | 90 |
| pre-commit-ci[bot] | 6****] | 18 |
| wehuang | h****3@y****m | 4 |
| Max Parzen | m****n@e****k | 4 |
| Pietro Monticone | 3****e | 1 |
Committer domains:
- ed.ac.uk: 1
- outlook.de: 1
Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 7
Total pull requests: 13
Average time to close issues: 4 months
Average time to close pull requests: about 1 month
Total issue authors: 3
Total pull request authors: 5
Average comments per issue: 1.43
Average comments per pull request: 1.0
Merged pull request: 10
Bot issues: 0
Bot pull requests: 7
Past year issues: 0
Past year pull requests: 2
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 0
Past year pull request authors: 2
Past year average comments per issue: 0
Past year average comments per pull request: 0.0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 1
Top Issue Authors
- pz-max (4)
- mikeymike555 (2)
- JohannesWirth (1)
Top Pull Request Authors
- pre-commit-ci[bot] (7)
- wehuang16 (2)
- pz-max (2)
- pitmonticone (1)
- mdzzg (1)
Top Issue Labels
Top Pull Request Labels
Dependencies
- actions/checkout v2 composite
- mamba-org/provision-with-micromamba main composite
- peaceiris/actions-gh-pages v3.6.1 composite
- atlite >=0.2.11
- cartopy >=0.22
- country-converter *
- folium *
- geopandas >=0.13.2
- geoviews >=1.10
- ghp-import *
- graphviz *
- highspy >=1.5.3
- holoviews *
- hvplot *
- ipython *
- jupyter-book *
- jupyterlab *
- lxml *
- mapclassify *
- matplotlib >=3.6
- netcdf4 *
- networkx *
- numpy *
- openpyxl *
- pandas >=2
- plotly *
- powerplantmatching >=0.5.7
- pyepsg *
- pyomo >=6.5
- pypsa >=0.25.1
- pyxlsb *
- pyyaml *
- rasterio >=1.3.2
- scipy *
- shapely >2
- tables *
- tabula-py *
- xarray *
- xlrd *
- highspy *
Score: 6.040254711277414