82 lines
2.6 KiB
Python
82 lines
2.6 KiB
Python
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#!/usr/bin/env python
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# pylint: disable=W0212
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from agate.table import Table
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def _aggregate(self, aggregations=[]):
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"""
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Recursive aggregation allowing for TableSet's to be nested inside
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one another.
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"""
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from agate.tableset import TableSet
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output = []
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# Process nested TableSet's
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if isinstance(self._values[0], TableSet):
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for key, nested_tableset in self.items():
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column_names, column_types, nested_output, row_name_columns = _aggregate(nested_tableset, aggregations)
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for row in nested_output:
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row.insert(0, key)
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output.append(row)
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column_names.insert(0, self._key_name)
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column_types.insert(0, self._key_type)
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row_name_columns.insert(0, self._key_name)
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# Regular Tables
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else:
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column_names = [self._key_name]
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column_types = [self._key_type]
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row_name_columns = [self._key_name]
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for new_column_name, aggregation in aggregations:
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column_names.append(new_column_name)
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column_types.append(aggregation.get_aggregate_data_type(self._sample_table))
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for name, table in self.items():
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for new_column_name, aggregation in aggregations:
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aggregation.validate(table)
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for name, table in self.items():
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new_row = [name]
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for new_column_name, aggregation in aggregations:
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new_row.append(aggregation.run(table))
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output.append(new_row)
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return column_names, column_types, output, row_name_columns
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def aggregate(self, aggregations):
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"""
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Aggregate data from the tables in this set by performing some
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set of column operations on the groups and coalescing the results into
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a new :class:`.Table`.
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:code:`aggregations` must be a sequence of tuples, where each has two
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parts: a :code:`new_column_name` and a :class:`.Aggregation` instance.
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The resulting table will have the keys from this :class:`TableSet` (and
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any nested TableSets) set as its :code:`row_names`. See
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:meth:`.Table.__init__` for more details.
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:param aggregations:
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A list of tuples in the format :code:`(new_column_name, aggregation)`,
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where each :code:`aggregation` is an instance of :class:`.Aggregation`.
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:returns:
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A new :class:`.Table`.
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"""
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column_names, column_types, output, row_name_columns = _aggregate(self, aggregations)
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if len(row_name_columns) == 1:
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row_names = row_name_columns[0]
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else:
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def row_names(r):
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return tuple(r[n] for n in row_name_columns)
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return Table(output, column_names, column_types, row_names=row_names)
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