fix sklearn links (#91)

src/sklearndf/_sklearndf.py

@@ -40,6 +40,7 @@ class EstimatorDF(FittableMixin[pd.DataFrame], metaclass=ABCMeta):
     Provides enhanced support for data frames.
     """
 
+    #: Name for the series containing input feature names.
     COL_FEATURE_IN = "feature_in"
 
     def __new__(cls: Type["EstimatorDF"], *args, **kwargs) -> object:
@@ -213,6 +214,7 @@ class TransformerDF(EstimatorDF, TransformerMixin, metaclass=ABCMeta):
     Provides enhanced support for data frames.
     """
 
+    #: Name for the series containing feature names after transform.
     COL_FEATURE_OUT = "feature_out"
 
     def __init__(self, *args, **kwargs) -> None:

src/sklearndf/_wrapper.py

@@ -149,7 +149,8 @@ def from_fitted(
     ) -> T_EstimatorWrapperDF:
         """
         Make a new wrapped data frame estimator whose delegate is an estimator which
-        has already been fitted
+        has already been fitted.
+
         :param estimator: the fitted estimator
         :param features_in: the column names of X used for fitting the estimator
         :param n_outputs: the number of outputs in y used for fitting the estimator
@@ -454,6 +455,7 @@ class _LearnerWrapperDF(
     Base class for wrappers around a delegate learner.
     """
 
+    #: Name for the series containing model predictions.
     COL_PREDICTION = "prediction"
 
     # noinspection PyPep8Naming
@@ -973,9 +975,9 @@ def _update_class_docstring(
                     *tag_line,
                     (
                         f"""
-.. note:: This class is a wrapper around class :class:{estimator_name}.
+.. note:: This class is a wrapper around class :class:`{estimator_name}`.
    It provides enhanced support for pandas data frames, and otherwise
-   replicates all parameters and behaviours of class :class:~{estimator_name}."""
+   replicates all parameters and behaviours of class :class:`~{estimator_name}`."""
                     ),
                     *(base_doc_lines if INCLUDE_FULL_SKLEARN_DOCUMENTATION else []),
                 ]

src/sklearndf/pipeline/_pipeline.py

@@ -30,6 +30,7 @@ class _PipelineWrapperDF(
     _TransformerWrapperDF[Pipeline],
     metaclass=ABCMeta,
 ):
+    #: Name for transformes in the pipeline that are passthrough.
     PASSTHROUGH = "passthrough"
 
     def _validate_delegate_estimator(self) -> None: