This repository contains data science training content for DataWhys in the form of JupyterLab notebooks (.ipynb files).
These notebooks are completely portable to all JupyterLab environments but require a Blockly extension for the full user experience (see prerequisites below).
For a complete list of topics covered, see the course outline.
Each topic has an introduction/worked example notebook and an independent problem solving notebook (-PS).
All materials are in Python. See here for the same materials in R.
Click on any notebook in the repository, and GitHub will render it in your browser as a non-interactive document.
Launch a demo session by clicking on the Binder badge below.
If you've never used Jupyter or want to try the Blockly extension, check out the tutorial video below.
- JupyterLab
- Python Blockly extension (optional but strongly recommended)
- Xeus Python Kernel (optional but strongly recommended)
The above is a minimal environment.
See the binder subfolder for the recommended conda env and JupyterLab extension installation.
Any other content-related materials, e.g. spreadsheets, should be placed in the OneDrive folder. If you create an issue that references a document in that folder, please try to link to said document.
If you want to change/correct content, either create an issue describing your change or use a git workflow to make the change.