Principal Components Analysis in TypeScript (Part 4): Turning PCA Into Interpretable Factor Analysis

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Remember how PCA collapses data with 100 dimensions into a single dimension, wouldn't it be cool if this dimension were interpretable. Factor Analysis does that
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Now remember how PCA collapses data with 100 dimensions into a single dimension, wouldn't it be cool if this dimension was interpretable. For example, let's say the 100 columns were like stress, smoking frequency, alcohol ml etc etc.. you see where I am going with this, the final dimension would be something like cardiac arrest or premature demise. On that cheery note, let's figure out how PCA can actually be used to label this reduced dimension.