docstr: Return the cos2 for each column against the dimensions.
  
  The cos2 value gives an indicator of the accuracy of the column projection on the dimension.
  
  Values above 0.5 usually means that the column is relatively accurately well projected onto that dimension. Its often
  used to identify which factor/dimension is important for a given element as the cos2 can be interpreted as the proportion
  of the variance of the element attributed to a particular factor.
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code: def column_cosine_similarities(self, X):
      """Return the cos2 for each column against the dimensions.
  
      The cos2 value gives an indicator of the accuracy of the column projection on the dimension.
  
      Values above 0.5 usually means that the column is relatively accurately well projected onto that dimension. Its often
      used to identify which factor/dimension is important for a given element as the cos2 can be interpreted as the proportion
      of the variance of the element attributed to a particular factor.
      """
      G = self.column_coordinates(X)
      return self._column_cosine_similarities(X, G)
  
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 8 for calling the CA obj's underlying member method code with example usage: obj.column_cosine_similarities(X) and returns: self