Demo of using Jupyter for data science, especially interactive features.
(notebook)
├── LICENSE
├── README.md <- The top-level README for developers using this project.
├── Demo.md <- Outline of demo.
├── environment.yml <- The conda environment file for reproducing the analysis environment, e.g.
│ generated with `conda env export -n jupyter-demo > environment.yml`
├── tasks.py <- Invoke tasks definitions
├── postBuild <- Binder post-build install script
│
├── data <- The original, immutable data dump.
│
├── decisions <- Lightweight decision records, for both architecture and analysis. See
│ http://thinkrelevance.com/blog/2011/11/15/documenting-architecture-decisions.
│
├── 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`.
- Jake VanderPlas, Reproducible Data Analysis in Jupyter
- ipywidgets project, Lorenz Differential Equations
- BeakerX project, Python examples
- bqplot project, Wealth of Nations
All under permissive licences like MIT, BSD or Apache 2.0.
Project based on the cookiecutter data science project template. #cookiecutterdatascience