DataWhys Content Notebooks (Python version)

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.

Check it out!

Static viewing

Click on any notebook in the repository, and GitHub will render it in your browser as a non-interactive document.

Interactive viewing

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.

Development

Prerequisites

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.

Internal development

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.

Contributing

If you want to change/correct content, either create an issue describing your change or use a git workflow to make the change.

Name		Name	Last commit message	Last commit date
Latest commit History 287 Commits
binder		binder
datasets		datasets
images		images
internship-variations		internship-variations
.gitignore		.gitignore
Clustering-PS.ipynb		Clustering-PS.ipynb
Clustering.ipynb		Clustering.ipynb
Course-outline.ipynb		Course-outline.ipynb
Crossvalidation-PS.ipynb		Crossvalidation-PS.ipynb
Crossvalidation.ipynb		Crossvalidation.ipynb
Data-cleaning-versioning-PS.ipynb		Data-cleaning-versioning-PS.ipynb
Data-cleaning-versioning.ipynb		Data-cleaning-versioning.ipynb
Data-science-and-the-nature-of-data-PS.ipynb		Data-science-and-the-nature-of-data-PS.ipynb
Data-science-and-the-nature-of-data.ipynb		Data-science-and-the-nature-of-data.ipynb
Decision-trees-PS.ipynb		Decision-trees-PS.ipynb
Decision-trees.ipynb		Decision-trees.ipynb
Descriptive-statistics-PS.ipynb		Descriptive-statistics-PS.ipynb
Descriptive-statistics.ipynb		Descriptive-statistics.ipynb
Gradient-boosting-PS.ipynb		Gradient-boosting-PS.ipynb
Gradient-boosting.ipynb		Gradient-boosting.ipynb
Jupyter-notebooks-intro-PS.ipynb		Jupyter-notebooks-intro-PS.ipynb
KNN-classification-PS.ipynb		KNN-classification-PS.ipynb
KNN-classification.ipynb		KNN-classification.ipynb
KNN-regression-PS.ipynb		KNN-regression-PS.ipynb
KNN-regression.ipynb		KNN-regression.ipynb
LICENSE		LICENSE
Lasso-PS.ipynb		Lasso-PS.ipynb
Lasso.ipynb		Lasso.ipynb
Logistic-regression-PS.ipynb		Logistic-regression-PS.ipynb
Logistic-regression.ipynb		Logistic-regression.ipynb
Measures-of-association-PS.ipynb		Measures-of-association-PS.ipynb
Measures-of-association.ipynb		Measures-of-association.ipynb
Multiple-linear-regression-PS.ipynb		Multiple-linear-regression-PS.ipynb
Multiple-linear-regression.ipynb		Multiple-linear-regression.ipynb
Naive-Bayes-PS.ipynb		Naive-Bayes-PS.ipynb
Naive-Bayes.ipynb		Naive-Bayes.ipynb
Plotting-PS.ipynb		Plotting-PS.ipynb
Plotting.ipynb		Plotting.ipynb
README.md		README.md
Random-forests-PS.ipynb		Random-forests-PS.ipynb
Random-forests.ipynb		Random-forests.ipynb
Reference.html		Reference.html
Reference.ipynb		Reference.ipynb
Regression-trees-PS.ipynb		Regression-trees-PS.ipynb
Regression-trees.ipynb		Regression-trees.ipynb
Simple-linear-regression-PS.ipynb		Simple-linear-regression-PS.ipynb
Simple-linear-regression.ipynb		Simple-linear-regression.ipynb
Support-vector-machines-PS.ipynb		Support-vector-machines-PS.ipynb
Support-vector-machines.ipynb		Support-vector-machines.ipynb
convert-notebooks-to-v2-plugin.py		convert-notebooks-to-v2-plugin.py
create-exercises-from-solutions.py		create-exercises-from-solutions.py
remove-okpy-submission-instructions.py		remove-okpy-submission-instructions.py
template.ipynb		template.ipynb

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memphis-iis/datawhys-content-notebooks-python

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DataWhys Content Notebooks (Python version)

Check it out!

Static viewing

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Development

Prerequisites

Internal development

Contributing

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