PCA Analysis in Python Explained (Scikit - Learn)

[@RyanAndMattDataScience]

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[@henry-o8i]

Thanks- another great video. But i do have 2 questions? 1) how do i retrieve the column name of the component that has the most explained variance (for EDA purposes). 2) is PCA used for feature engineering? or will you have a video that talk about feature engineering later on?

[@bommijn]

Hey, something i noticed. You copy the column names back into your X_train after scaling. Is it not easier to do "X_train = pd.DataFrame(ss.fit_transform(X_train), columns=X_train.columns)"

[@mehdismaeili3743]

Excellent .

[@RyanAndMattDataScience]

Really appreciate you checking out the vids

[@alexhernandezherrera5198]

great video, thanks for explain clearly

[@RyanAndMattDataScience]

No problem

[@Divy91311]

Hey Ryan , really nice video! I was wondering if I could help you edit your videos and also make a highly engaging Thumbnail which will help your video to reach to a wider audience .

[@RyanAndMattDataScience]

Sorry have an editor and I make my own thumbnail. I appreciate you reaching out though

[@Divy91311]

@@RyanAndMattDataScience Sure bro no problem, if anyone in your contact is searching for an editor please refer me !!