How can I calculate Principal Components Analysis from data in a 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_