Principal components analysis using pandas dataframe
Most sklearn objects work with pandas dataframes just fine, would something like this work for you? import pandas as pd import numpy as np from sklearn.decomposition import PCA df = pd.DataFrame(data=np.random.normal(0, 1, (20, 10))) pca = PCA(n_components=5) pca.fit(df) You can access the components themselves with pca.components_