class_docstr: A basic class for Principal Component Analysis (PCA).
  
  p is the number of dimensions, while N is the number of data points
code: def __calc(self):
      A = self.A
      M = A - np.mean(A, axis=0)
      N = M / np.std(M, axis=0)
  
      self.M = M
      self.N = N
      self._eig = None
  
file_path: statsmodels/statsmodels/sandbox/pca.py
imports: import numpy
label_desc: Use image node_id 1 for calling the Pca obj's underlying member method code with example usage: obj.__calc() without return types