code: def blobs(n_variables=11, n_centers=5, cluster_std=1.0, n_observations=640) -> AnnData:
      
      import sklearn.datasets
      X, y = sklearn.datasets.make_blobs(n_samples=n_observations,
                                         n_features=n_variables,
                                         centers=n_centers,
                                         cluster_std=cluster_std,
                                         random_state=0)
      return AnnData(X, obs={'blobs': y.astype(str)})
docs: Gaussian Blobs.
  
      Parameters
      ----------
      n_variables : `int`, optional (default: 11)
          Dimension of feature space.
      n_centers : `int`, optional (default: 5)
          Number of cluster centers.
      cluster_std : `float`, optional (default: 1.0)
          Standard deviation of clusters.
      n_observations : `int`, optional (default: 640)
          Number of observations. By default, this is the same observation number as in
          ``sc.datasets.krumsiek11()``.
  
      Returns
      -------
      Annotated data matrix containing a observation annotation 'blobs' that
      indicates cluster identity.