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This will be replaced with separate calls to _handle_nullable_types in both X and y. Since we only need to transform when self._impute_target == "interpolate", we can consider implementing a special _handle_nullable_types that takes _self.impute_target into account.
The text was updated successfully, but these errors were encountered:
tamargrey
changed the title
Add nullable type handling to TimeSeriesImputer
TimeSeriesImputer: Add nullable type handling for X and y when interpolate is impute method
Feb 17, 2023
Since nans will be present at this point, there may need to be some logic to make sure we maintain the original logical types that will not be needed at the other coponents. We should be able to just initialize the interpolated data with the original schema (minus any dropped fully null cols and some cols that can't do type conversions like float64 -> Int64) after interpolation occurs
When
interpolate
is the impute method, we use pandas'series.impute
method, which cannot handle nullable types: pandas-dev/pandas#40252As part of component-specific nullable type handling, we should remove the calls to
astype(float)
we currently do:This will be replaced with separate calls to
_handle_nullable_types
in both X and y. Since we only need to transform whenself._impute_target == "interpolate"
, we can consider implementing a special_handle_nullable_types
that takes_self.impute_target
into account.The text was updated successfully, but these errors were encountered: