First step is to load DVF in a postgresql db, for this check src/dvf_psql.py.
Project Organization
├── data
│ ├── raw <- The original, immutable data dump.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ ├── output <- Output from models
│ ├── schemas <- Raw and processed data schemas, based on Table Schema standard
|
├── documentation <- Documentation for the project
|
├── notebooks <- Notebooks Jupyter (only include jupytext --to .py version of notebooks)
|
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
|
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── src <- Source code
│ ├── __init__.py <- Makes src a Python module
|
├── tests <- Tests for our projet
|
├── LICENCE.txt
├── README.md
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
Project based on the cookiecutter data science project template. #cookiecutterdatascience