data-science-project

Repository containing scaffolding for a language agnostic (data) science project.

Creating a new project from this template

Simply follow the instructions to create a new project repository from this template.

Project organization

Project organization is based on ideas from Good Enough Practices for Scientific Computing.

1. Put each project in its own directory, which is named after the project.
2. Put external scripts or compiled programs in the bin directory.
3. Put raw data and metadata in a data directory.
4. Put text documents associated with the project in the doc directory.
5. Put all Docker related files in the docker directory.
6. Put files generated during cleanup and analysis in a results directory.
7. Put project source code in the src directory.
8. Name all files to reflect their content or function.