76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
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#!/usr/bin/env python
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from agate.aggregations.has_nulls import HasNulls
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from agate.aggregations.sum import Sum
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from agate.computations.base import Computation
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from agate.data_types import Number
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from agate.exceptions import DataTypeError
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from agate.warns import warn_null_calculation
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class Percent(Computation):
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"""
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Calculate each values percentage of a total.
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:param column_name:
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The name of a column containing the :class:`.Number` values.
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:param total:
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If specified, the total value for each number to be divided into. By
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default, the :class:`.Sum` of the values in the column will be used.
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"""
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def __init__(self, column_name, total=None):
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self._column_name = column_name
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self._total = total
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def get_computed_data_type(self, table):
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return Number()
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def validate(self, table):
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column = table.columns[self._column_name]
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if not isinstance(column.data_type, Number):
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raise DataTypeError('Percent column must contain Number data.')
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if self._total is not None and self._total <= 0:
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raise DataTypeError('The total must be a positive number')
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# Throw a warning if there are nulls in there
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if HasNulls(self._column_name).run(table):
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warn_null_calculation(self, column)
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def run(self, table):
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"""
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:returns:
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:class:`decimal.Decimal`
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"""
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# If the user has provided a total, use that
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if self._total is not None:
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total = self._total
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# Otherwise compute the sum of all the values in that column to
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# act as our denominator
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else:
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total = table.aggregate(Sum(self._column_name))
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# Raise error if sum is less than or equal to zero
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if total <= 0:
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raise DataTypeError('The sum of column values must be a positive number')
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# Create a list new rows
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new_column = []
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# Loop through the existing rows
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for row in table.rows:
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# Pull the value
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value = row[self._column_name]
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if value is None:
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new_column.append(None)
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continue
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# Try to divide it out of the total
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percent = value / total
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# And multiply it by 100
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percent = percent * 100
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# Append the value to the new list
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new_column.append(percent)
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# Pass out the list
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return new_column
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