Do you know how to apply PCA or correlation analysis for featur selection in Python? (with example)

In this tutorial, learn how to select best features by applying PCA (principal component analysis) and correlation analysis using sklearn in Python. Feature selection is a fundamental step in data modeling when there are many feature to choose from. There are various ways to find best set of features: 1) feature selection:selecting the most relevant features and remove redundant ones 2) feature extraction: for creating new features that can explain most of the variability in the data (so transforming the main features into other dimensions)