Real-time tool for exploring the relationships between PCA components and input features.

Or, "Roughly what do these principal components actually correspond to?"

• Real-time plot to give intuition about prinipal components.
• Sliders dynamically created for each input feature.
• Sliders begin at mean and are scaled to feature data ranges, giving an intuitive feel of how "sensitive" the components are to each feature.

pip install -r requirements.txt

Matplotlib has to be installed as a framework.

Run the demo on the iris dataset using:

python3 pca_vis.py

Or load any dataset as a Pandas DataFrame and pass it into the main() function as an argument.

To learn a bit more about PCA, check out my friend Gary's repo.

• Gianluca Truda — Github | LinkedIn

This project was inspired by this one and adapted the generic slider code from here.