def __merge_datasets(datasets, mapping):
"""Merge two or more datasets."""
dframes = []
if not mapping:
mapping = {}
for dataset in datasets:
dframe = dataset.dframe()
column_map = mapping.get(dataset.dataset_id)
if column_map:
dframe = BambooFrame(dframe.rename(columns=column_map))
dframe = dframe.add_parent_column(dataset.dataset_id)
dframes.append(dframe)
return concat(dframes, ignore_index=True)
def save(self):
"""Save this aggregation.
If an aggregated dataset for this aggregations group already exists
store in this dataset, if not create a new aggregated dataset and store
the aggregation in this new aggregated dataset.
"""
new_dframe = BambooFrame(self.aggregation.eval(self.columns))
new_dframe = new_dframe.add_parent_column(self.dataset.dataset_id)
agg_dataset = self.dataset.aggregated_dataset(self.groups)
if agg_dataset is None:
agg_dataset = self.dataset.new_agg_dataset(
new_dframe, self.groups)
else:
agg_dframe = agg_dataset.dframe()
new_dframe = self.__merge_dframes([agg_dframe, new_dframe])
agg_dataset.replace_observations(new_dframe)
self.new_dframe = new_dframe
