Land use permitting analysis for Department of City Planning
├── 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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- Sign in with credentials. More details on getting started here.
- Launch a new terminal and clone repository:
git clone https://github.com/CityOfLosAngeles/planning-entitlements.git - Change into directory:
cd planning-entitlements - Make a new branch and start on a new task:
git checkout -b new-branch
- Start with Steps 1-2 above
- Build Docker container:
docker-compose.exe build - Start Docker container
docker-compose.exe up - Open Jupyter Lab notebook by typing
localhost:8888/lab/in the browser.
conda create --name my_project_namesource activate my_project_nameconda install --file conda-requirements.txt -c conda-forgepip install -r requirements.txt
Project based on the cookiecutter data science project template. #cookiecutterdatascience
Other reference docs are stored in the references subfolder. Useful website links are listed here: