class_docstr: Calculate the sample variance of a column.
  
  For the population variance see :class:`.PopulationVariance`.
  
  :param column_name:
      The name of a column containing :class:`.Number` data.
class_docstr_tok: ["Calculate","the","sample","variance","of","a","column",".","For","the","population","variance","see",":","class",":","`",".PopulationVariance","`",".",":","param","column_name",":","The","name","of","a","column","containing",":","class",":","`",".Number","`","data","."]
code: def __init__(self, column_name):
      self._column_name = column_name
      self._mean = Mean(column_name)
  
file_path: agate/agate/aggregations/variance.py
imports: from agate.aggregations.base import Aggregation
  from agate.aggregations.has_nulls import HasNulls
  from agate.aggregations.mean import Mean
  from agate.data_types import Number
  from agate.exceptions import DataTypeError
  from agate.warns import warn_null_calculation
label_desc: Use image node_id 1 to create a new Variance object from inherited base classes: Aggregation with example: obj = Variance(column_name)