PROJECT/
├── figures/ <- plots.m saves figures in here
├── main.m <- does something fancy, calls plots.m
├── plots.m <- make presentation figures
├── raw2wind.m <- script to clean .csv data to .mat
├── readme.txt
├── windSpeed_MITGreenBuilding.mat <- cleaned data
├── weatherStation_MITGreenBuilding_2019_07_01.csv <- raw data
├── weatherStation_MITGreenBuilding_2019_07_02.csv
├── weatherStation_MITGreenBuilding_2019_07_03.csv
├── weatherStation_MITGreenBuilding_2019_07_04.csv
├── weatherStation_MITGreenBuilding_2019_07_05.csv
├── weatherStation_MITGreenBuilding_2019_07_06.csv
└── weatherStation_MITGreenBuilding_2019_07_07.csv
PROJECT/
├── bin/ <- compiled binaries.
├── data/
│ ├── raw/
│ └── clean/
│
├── figures/ <- figures used in place of a "results" folder.
├── scripts/
│ ├── process/ <- scripts to maniuplate data between raw, cleaned, final stages.
│ └── plot/ <- intermediate plotting.
│
├── src
│ ├── model1/ <- various experimental models.
│ ├── model2/
│ └── model3/
│
├── LICENSE
├── Makefile
└── readme.md
This example is borrowed from Cookiecutter Data Science.
PROJECT/
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── 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 for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.py <- Make this project pip installable with `pip install -e`
├── 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
│
└── tox.ini <- tox file with settings for running tox; see tox.testrun.org