Grouper¶
Applies a transformer within different groups.
This transformer allows you to split your data into groups and apply a transformer within each group. This happens in a streaming manner, which means that the groups are discovered online. A separate copy of the provided transformer is made whenever a new group appears. The groups are defined according to one or more keys.
Parameters¶
-
transformer
Type → base.Transformer
-
by
Type → base.typing.FeatureName | list[base.typing.FeatureName]
The field on which to group the data. This can either by a single value, or a list of values.
Methods¶
learn_one
Update with a set of features x
.
A lot of transformers don't actually have to do anything during the learn_one
step because they are stateless. For this reason the default behavior of this function is to do nothing. Transformers that however do something during the learn_one
can override this method.
Parameters
- x — 'dict'
Returns
Transformer: self
transform_one
Transform a set of features x
.
Parameters
- x — 'dict'
Returns
dict: The transformed values.