DataTaunew | comments | leaders | submitlogin
2 points by astrobiased 3385 days ago | link | parent

Here's the code I used to generate the PCA plot.

    import matplotlib.pyplot as plt
    import seaborn as sns
    from sklearn.decomposition import PCA as sklearnPCA
    
    sklearn_pca = sklearnPCA(n_components=2)

    tmp = np.array(df) #df is a Pandas DataFrame
    proj = sklearn_pca.fit_transform(tmp)

    sns.set_style("white")
    sns.set_context('talk')

    g = sns.JointGrid(proj[:,0], proj[:,1], space=0, size=8)
    g.plot_marginals(sns.distplot, kde=False, color=".7", bins=30)
    g.plot_joint(plt.scatter, color=".5", edgecolor="none", alpha=1)
    g.set_axis_labels(xlabel='PC1', ylabel='PC2')



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