old_contents: """
  User-facing interface for plotting all dimensionality reduction algorithms
  """
  
  def smushplot(data, smusher='pca', n_components=2, marker='o', marker_order=None,
                text=False, text_order=None, linewidth=1, linewidth_order=None,
                edgecolor='k', edgecolor_order=None, smusher_kws=None,
                plot_kws=None):
      if isinstance(smusher, str):
          # Need to get appropriate smusher from sklearn given the string
          pass
      else:
          # Assume this is already an initialized sklearn object with the
          # ``fit_transform()`` method
          pass
  
new_contents: """
  User-facing interface for plotting all dimensionality reduction algorithms
  """
  
  def smushplot(data, smusher='PCA', x=1, y=2, n_components=2, marker='o',
                marker_order=None, text=False, text_order=None, linewidth=1,
                linewidth_order=None, edgecolor='k', edgecolor_order=None,
                smusher_kws=None, plot_kws=None):
      """Plot high dimensional data in 2d space
  
      Parameters
      ----------
      data : pandas.DataFrame or numpy.array
          A (n_samples, m_features) wide matrix of observations. The samples
          (rows) will be plotted relative to the reduced representation of the
          features (columns)
      smusher : str or object
          Either a string specifying a valid dimensionality reduction algorithm
          in ``sklearn.decomposition`` or ``sklearn.manifold``, or any object
          with ``fit_transform()`` methods.
  
  
      Notes
      -----
  
  
      """
      if isinstance(smusher, str):
          # Need to get appropriate smusher from sklearn given the string
          pass
      else:
          # Assume this is already an initialized sklearn object with the
          # ``fit_transform()`` method
          pass
  
subject: Add x, y arguments and docstring