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pythonnumpypca

PCA with missing values in Python

I'm trying to do a PCA analysis on a masked array. From what I can tell, matplotlib.mlab.PCA doesn't work if the original 2D matrix has missing values. Does anyone have recommendations for doing a PCA with missing values in Python?

Thanks.

Solution

  • I think you will probably need to do some preprocessing of the data before doing PCA. You can use:

    sklearn.impute.SimpleImputer

    https://scikit-learn.org/stable/modules/generated/sklearn.impute.SimpleImputer.html#sklearn.impute.SimpleImputer

    With this function you can automatically replace the missing values for the mean, median or most frequent value. Which of this options is the best is hard to tell, it depends on many factors such as how the data looks like.

    By the way, you can also use PCA using the same library with:

    sklearn.decomposition.PCA

    http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html

    And many others statistical functions and machine learning tecniques.