docstr: The column principal coordinates.
docstr_tok: ["The","column","principal","coordinates","."]
code: def column_coordinates(self, X):
      """The column principal coordinates."""
  
      _, _, _, col_names = utils.make_labels_and_names(X)
      index_name = X.columns.name
  
      if isinstance(X, pd.DataFrame):
          is_sparse = X.dtypes.apply(
              lambda dtype: isinstance(dtype, pd.SparseDtype)
          ).all()
          if is_sparse:
              X = X.sparse.to_coo()
          else:
              X = X.to_numpy()
  
      if self.copy:
          X = X.copy()
  
      # Transpose and make sure the rows sum up to 1
      if isinstance(X, np.ndarray):
          X = X.T / X.T.sum(axis=1)[:, None]
      else:
          X = X.T / X.T.sum(axis=1)
  
      return pd.DataFrame(
          data=X
          @ sparse.diags(self.row_masses_.to_numpy() ** -0.5)
          @ self.svd_.U,
          index=pd.Index(col_names, name=index_name),
      )
  
imports: from __future__ import annotations
  import functools
  import altair
  import numpy
  import pandas
  from scipy import sparse
  from sklearn.utils import check_array
  from prince import svd, utils
label_desc: Use image node_id 7 for calling the CA obj's underlying member method code with example usage: obj.column_coordinates(X) and returns: pd