code: def _column_cosine_similarities(self, X, G):
      # Active
      X_act = X[self.active_cols_]
      X_act = X_act / X_act.sum().sum()
      marge_row = X_act.sum(axis=1)
      Tc = (
          X_act.div(marge_row, axis=0).div(X_act.sum(axis=0), axis=1)
          - 1
      )
      dist2_col = (Tc**2).mul(marge_row, axis=0).sum(axis=0)
  
      # Supplementary
      X_sup = X[X.columns.difference(self.active_cols_, sort=False)]
      X_sup = X_sup.div(X_sup.sum(axis=0), axis=1)
      dist2_col_sup = (
          ((X_sup.sub(marge_row, axis=0)) ** 2)
          .div(marge_row, axis=0)
          .sum(axis=0)
      )
  
      dist2_col = pd.concat((dist2_col, dist2_col_sup))
      return (G**2).div(dist2_col, axis=0)
  
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 9 for calling the CA obj's underlying member method code with example usage: obj._column_cosine_similarities(X, G) and returns: unknown