/planning-entitlements

Land use permitting analysis for City Planning

Primary LanguageJupyter NotebookApache License 2.0Apache-2.0

planning-entitlements

Land use permitting analysis for Department of City Planning

Project Organization

├── LICENSE
├── Makefile                 <- Makefile with commands like `make data` or `make train`
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├── README.md                <- The top-level README for developers using this project.
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├── catalogs                 <- A directory for data sources used in repo.
│   └── catalog.yml          <- Catalog for data sources in S3 or databases.
│   └── open-data.yml        <- Catalog for data from open data portals.
├── manifest.yml             <- Save a copy of open data into S3 with `make mirror`
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├── laplan                   <- A python package for planning-related utility functions.
├── laplan_README.md         <- README for the `laplan` pacakage.
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├── data                     <- A directory for local, raw, source data.
├── gis                      <- A directory for local geospatial data.
├── models                   <- Trained and serialized models, model predictions, or model summaries.
├── outputs                  <- A directory for outputs such as tables created.
├── processed                <- A directory for processed, final data that is used for analysis.
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├── src                      <- Source code for use in this project.
├── notebooks                <- Jupyter notebooks.
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├── 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.
├── visualization            <- A directory for visualizations created.
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├── conda-requirements.txt   <- The requirements file for conda installs.
├── requirements.txt         <- The requirements file for reproducing the analysis environment, e.g.
│                               generated with `pip freeze > requirements.txt`
├── setup.py                 <- Makes project pip installable (pip install -e .) so src can be imported
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Starting with JupyterHub

  1. Sign in with credentials. More details on getting started here.
  2. Launch a new terminal and clone repository: git clone https://github.com/CityOfLosAngeles/planning-entitlements.git
  3. Change into directory: cd planning-entitlements
  4. Make a new branch and start on a new task: git checkout -b new-branch

Starting with Docker

  1. Start with Steps 1-2 above
  2. Build Docker container: docker-compose.exe build
  3. Start Docker container docker-compose.exe up
  4. Open Jupyter Lab notebook by typing localhost:8888/lab/ in the browser.

Setting up a Conda Environment

  1. conda create --name my_project_name
  2. source activate my_project_name
  3. conda install --file conda-requirements.txt -c conda-forge
  4. pip install -r requirements.txt

Project based on the cookiecutter data science project template. #cookiecutterdatascience

References

More Docs

Other reference docs are stored in the references subfolder. Useful website links are listed here: