def calculate_column(self, formula, name, groups=None):
"""Calculate a new column based on `formula` store as `name`.
The new column is joined to `dframe` and stored in `self.dataset`.
The `group_str` is only applicable to aggregations and groups for
aggregations.
.. note::
This can result in race-conditions when:
- deleting ``controllers.Datasets.DELETE``
- updating ``controllers.Datasets.POST([dataset_id])``
Therefore, perform these actions asychronously.
:param formula: The formula parsed by `self.parser` and applied to
`self.dframe`.
:param name: The name of the new column or aggregate column.
:param groups: A list of columns to group on for aggregate
calculations.
"""
self._ensure_dframe()
aggregation, new_columns = self.make_columns(formula, name)
if aggregation:
agg = Aggregator(self.dataset, self.dataset.dframe(),
groups, aggregation, name)
agg.save(new_columns)
else:
self.dataset.replace_observations(self.dframe.join(new_columns[0]))
# propagate calculation to any merged child datasets
for merged_dataset in self.dataset.merged_datasets:
merged_calculator = Calculator(merged_dataset)
merged_calculator.propagate_column(self.dataset)
