Principal components analysis using pandas dataframe

Question

How can I calculate Principal Components Analysis from data in a pandas dataframe?

Answer 1

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_