Transformer
Aggregator
Prepare hierarchical data, including aggregate levels, from bottom level.
This transformer adds aggregate levels via summation to a DataFrame with a multiindex. The aggregate levels are included with the special tag “__total” in the index. The aggregate nodes are discovered from top-to-bottom from the input data multiindex.
Quickstart
python
from sktime.transformations.hierarchical.aggregate import Aggregator
estimator = Aggregator(flatten_single_levels=True, bypass_inverse_transform=True)Tags
Capabilities
- Multivariate
- Inverse transform: Supported
- Unequal-length series
- Missing values: Not supported
- Removes missing values: Not supported
- Equalizes series length: Not supported
Properties
- Input typescitype:transform-input
- Series
- Output typescitype:transform-output
- Series
- Label typescitype:transform-labels
- None
- Fit is emptyfit_is_empty
- Yes
- Keeps the time indextransform-returns-same-time-index
- No
- Requires Xrequires_X
- Yes
- Requires yrequires_y
- No
- X and y need the same indexX-y-must-have-same-index
- No
Parameters(2)
- flatten_single_levelboolean (default=True)
- Remove aggregate nodes, i.e. (“__total”), where there is only a single child to the level
- bypass_inverse_transformboolean (default=True)
- If True, the inverse_transform method is skipped. If False, the inverse_transform method is implemented and can be used to remove aggregate levels from the data.
Examples
>>> from sktime.transformations.hierarchical.aggregate import Aggregator
>>> from sktime.utils._testing.hierarchical import _bottom_hier_datagen
>>> agg = Aggregator ()
>>> y = _bottom_hier_datagen (
... no_bottom_nodes = 3,
... no_levels = 1,
... random_seed = 123,
... )
>>> y = agg. fit_transform (y)