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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
class Variance(Aggregation):
"""
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.
"""
def __init__(self, column_name):
self._column_name = column_name
self._mean = Mean(column_name)
def get_aggregate_data_type(self, table):
return Number()
def validate(self, table):
column = table.columns[self._column_name]
if not isinstance(column.data_type, Number):
raise DataTypeError('Variance can only be applied to columns containing Number data.')
has_nulls = HasNulls(self._column_name).run(table)
if has_nulls:
warn_null_calculation(self, column)
def run(self, table):
column = table.columns[self._column_name]
data = column.values_without_nulls()
if data:
mean = self._mean.run(table)
return sum((n - mean) ** 2 for n in data) / (len(data) - 1)
class PopulationVariance(Variance):
"""
Calculate the population variance of a column.
For the sample variance see :class:`.Variance`.
:param column_name:
The name of a column containing :class:`.Number` data.
"""
def __init__(self, column_name):
self._column_name = column_name
self._mean = Mean(column_name)
def get_aggregate_data_type(self, table):
return Number()
def validate(self, table):
column = table.columns[self._column_name]
if not isinstance(column.data_type, Number):
raise DataTypeError('PopulationVariance can only be applied to columns containing Number data.')
has_nulls = HasNulls(self._column_name).run(table)
if has_nulls:
warn_null_calculation(self, column)
def run(self, table):
column = table.columns[self._column_name]
data = column.values_without_nulls()
if data:
mean = self._mean.run(table)
return sum((n - mean) ** 2 for n in data) / len(data)
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