PCA Visualisation

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

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

Features

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.

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