code: def ensure_all_columns_are_used(num_vars_accounted_for,
                                  dataframe,
                                  data_title='long_data'):
      
      dataframe_vars = set(dataframe.columns.tolist())
      num_dataframe_vars = len(dataframe_vars)
  
      if num_vars_accounted_for == num_dataframe_vars:
          pass
  
      elif num_vars_accounted_for < num_dataframe_vars:
          msg = "Note, there are {:,} variables in {} but the inputs"
          msg_2 = " ind_vars, alt_specific_vars, and subset_specific_vars only"
          msg_3 = " account for {:,} variables."
  
          warnings.warn(msg.format(num_dataframe_vars, data_title) +
                        msg_2 + msg_3.format(num_vars_accounted_for))
  
      else:  # This means num_vars_accounted_for > num_dataframe_vars
          msg = "There are more variable specified in ind_vars, "
          msg_2 = "alt_specific_vars, and subset_specific_vars ({:,}) than there"
          msg_3 = " are variables in {} ({:,})"
          warnings.warn(msg +
                        msg_2.format(num_vars_accounted_for) +
                        msg_3.format(data_title, num_dataframe_vars))
  
      return None
docs: Ensure that all of the columns from dataframe are in the list of used_cols.
      Will raise a helpful UserWarning if otherwise.
  
      Parameters
      ----------
      num_vars_accounted_for : int.
          Denotes the number of variables used in one's function.
      dataframe : pandas dataframe.
          Contains all of the data to be converted from one format to another.
      data_title : str, optional.
          Denotes the title by which `dataframe` should be referred in the
          UserWarning.
  
      Returns
      -------
      None.