I'm want to apply PCA to the kaggle's Titanic dataset
For now I'm just taking the columns that have numeric values and dropping the NaN values, So I have five variables, actually four if we ignore the depending variable ('Survived').
I have this loaded into a DataFrame df, if I took five components using PCA:
pca_model = PCA(n_components=5) pca_model.fit(df) pca_model.explained_variance_ratio_ [ 9.30197643e-01 6.93699966e-02 2.24377672e-04 1.49076254e-04 5.89069784e-05]
I got that 93 percent of the variance comes from the first component. Is it possible how can I get this same values from the original variables? E.G. Age -> 0.3 of the variance Fare -> 0.6
Can I now which percentage of the principal component is given by each of the original variables?