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https://github.com/os-climate/rmi-utility-transition-hub-ingestion-pipeline

Data ingest for RMI's Utility Transition Hub data (as of March 7, 2022)
https://github.com/os-climate/rmi-utility-transition-hub-ingestion-pipeline

data emissions-co2 energy-data os-climate

Last synced: 7 days ago
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Data ingest for RMI's Utility Transition Hub data (as of March 7, 2022)

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README

        

# rmi-utility-transition-hub-ingestion-pipeline

template for the team to use

## Project Organization

├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── Pipfile <- Pipfile stating package configuration as used by Pipenv.
├── Pipfile.lock <- Pipfile.lock stating a pinned down software stack with as used by Pipenv.
├── README.md <- The top-level README for developers using this project.
├── data
│   ├── external <- Data from third party sources.
│   ├── interim <- Intermediate data that has been transformed.
│   ├── processed <- The final, canonical data sets for modeling.
│   └── raw <- The original, immutable data dump.

├── docs <- A default Sphinx project; see sphinx-doc.org for details

├── models <- Trained and serialized models, model predictions, or model summaries

├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.

├── references <- Data dictionaries, manuals, and all other explanatory materials.

├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures <- Generated graphics and figures to be used in reporting

├── requirements.txt <- The requirements file stating direct dependencies if a library
│ is developed.

├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── src <- Source code for use in this project.
│   ├── __init__.py <- Makes src a Python module
│ │
│   ├── data <- Scripts to download or generate data
│   │   └── make_dataset.py
│ │
│   ├── features <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│ │
│   ├── models <- Scripts to train models and then use trained models to make
│ │ │ predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│ │
│   └── visualization <- Scripts to create exploratory and results oriented visualizations
│   └── visualize.py

├── .thoth.yaml <- Thoth's configuration file
├── .aicoe-ci.yaml <- AICoE CI configuration file (https://github.com/AICoE/aicoe-ci)
└── tox.ini <- tox file with settings for running tox; see tox.readthedocs.io

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Project based on the [cookiecutter](https://drivendata.github.io/cookiecutter-data-science/) data science project template