captest.capdata.CapData.expand_agg_map

CapData.expand_agg_map(agg_map)

Traverses, expands, and sorts the agg_map.

If a value of agg_map is a dictionary, the items in that dictionary are added to the returned expanded agg_map at the top level. Also, the following steps are completed to aggregate the subgroups: - The column_groups attribute is updated to add a new group with the aggregated columns from the subgroups. - This new group is added to the expanded returned agg_map after the subgroup aggregations. - The resulting aggregation of the subgroups is renamed.

For example, given the following agg_map: ```python agg_map = {

‘irr_ghi’: ‘mean’, ‘irr_poa’: {

‘irr_poa_met1’: ‘mean’, ‘irr_poa_met2’: ‘mean’

},

}

The returned expanded agg_map would be: ```python agg_map = {

‘irr_ghi’: ‘mean’, ‘irr_poa_met1’: ‘mean’, ‘irr_poa_met2’: ‘mean’, ‘irr_poa_aggs’: ‘mean’,

}

and the column_groups attribute would be updated to add the group: ‘irr_poa_aggs’: [‘irr_poa_met1_mean_agg’, ‘irr_poa_met2_mean_agg’]

The column resulting from aggregating the “irr_poa_aggs” group would be “irr_poa_aggs_mean_agg”, which is renamed to “irr_poa_mean_agg”.

param agg_map:

Dictionary specifying aggregations to be performed on the specified groups from the column_groups attribute.

type agg_map:

dict

returns:

agg_map

rtype:

dict