plot_matrix_n_evectors_w_scilearn.py

ax = plt.gca(); ax.set_xlabel('X'); ax.set_ylabel('Y')
plt.scatter(X[:, 0], X[:, 1], alpha=0.3, color="#191970")
plt.scatter(pca.mean_[0], pca.mean_[1], c='red', s=50)
plt.axis('equal')

for length, vector in zip(pca.explained_variance_, pca.components_):
    dir_ = vector * 3  * np.sqrt(length)
    start = pca.mean_; end = start + dir_
    arrowprops = dict(arrowstyle='->',linewidth=2, 
                      shrinkA=0, shrinkB=0, color='red', alpha=0.5)
    ax.annotate('', xy=end, xytext=start, arrowprops=arrowprops)