class Mean(Aggregation):
    """
    Calculate the mean of a column.

    :param column_name:
        The name of a column containing :class:`.Number` data.
    """
    def __init__(self, column_name):
        self._column_name = column_name
        self._sum = Sum(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(
                'Mean 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]

        sum_total = self._sum.run(table)

        return sum_total / len(column.values_without_nulls())
Beispiel #2
0
Datei: mean.py Projekt: 01-/agate
class Mean(Aggregation):
    """
    Calculate the mean of a column.

    :param column_name:
        The name of a column containing :class:`.Number` data.
    """
    def __init__(self, column_name):
        self._column_name = column_name
        self._sum = Sum(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('Mean 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]

        sum_total = self._sum.run(table)

        return sum_total / len(column.values_without_nulls())
    def run(self, table):
        """
        :returns:
            :class:`decimal.Decimal`
        """
        # If the user has provided a total, use that
        if self._total is not None:
            total = self._total
        # Otherwise compute the sum of all the values in that column to
        # act as our denominator
        else:
            total = table.aggregate(Sum(self._column_name))
            # Raise error if sum is less than or equal to zero
            if total <= 0:
                raise DataTypeError(
                    'The sum of column values must be a positive number')

        # Create a list new rows
        new_column = []

        # Loop through the existing rows
        for row in table.rows:
            # Pull the value
            value = row[self._column_name]
            if value is None:
                new_column.append(None)
                continue
            # Try to divide it out of the total
            percent = value / total
            # And multiply it by 100
            percent = percent * 100
            # Append the value to the new list
            new_column.append(percent)

        # Pass out the list
        return new_column
 def __init__(self, column_name):
     self._column_name = column_name
     self._sum = Sum(column_name)
Beispiel #5
0
Datei: mean.py Projekt: 01-/agate
 def __init__(self, column_name):
     self._column_name = column_name
     self._sum = Sum(column_name)