old_contents: #!/usr/bin/env python
  
  import agate
  
  class ZScores(agate.Computation):
      """
      Computes the z-scores (standard scores) of a given column.
      """
      def __init__(self, column_name):
          self._column_name = column_name
  
          self._mean = None
          self._sd = None
  
      def get_computed_data_type(self, table):
          return agate.Number()
  
      def validate(self, table):
          column = table.columns[self._column_name]
  
          if not isinstance(column.data_type, agate.Number):
              raise agate.DataTypeError('ZScores column must contain Number data.')
  
      def run(self, table):
          self._mean = table.aggregate(agate.Mean(self._column_name))
          self._sd = table.aggregate(agate.StDev(self._column_name))
  
      def run(self, table):
          new_column = []
  
          for row in table.rows:
              value = row[self._column_name]
  
              if value is not None:
                  new_column.append((value - self._mean) / self._sd)
              else:
                  new_column.append(None)
  
          return new_column
  
new_contents: #!/usr/bin/env python
  
  import agate
  
  class ZScores(agate.Computation):
      """
      Computes the z-scores (standard scores) of a given column.
      """
      def __init__(self, column_name):
          self._column_name = column_name
  
          self._mean = None
          self._sd = None
  
      def get_computed_data_type(self, table):
          return agate.Number()
  
      def validate(self, table):
          column = table.columns[self._column_name]
  
          if not isinstance(column.data_type, agate.Number):
              raise agate.DataTypeError('ZScores column must contain Number data.')
  
          self._mean = table.aggregate(agate.Mean(self._column_name))
          self._sd = table.aggregate(agate.StDev(self._column_name))
  
      def run(self, table):
          new_column = []
  
          for row in table.rows:
              value = row[self._column_name]
  
              if value is not None:
                  new_column.append((value - self._mean) / self._sd)
              else:
                  new_column.append(None)
  
          return new_column
  
subject: Fix mysterious line