feat: move ImputerStrategy to safeds.data.tabular.typing (#174)

### Summary of Changes

* Move the abstract base class `ImputerStrategy` to
`safeds.data.tabular.typing` since it is only needed for type
annotations
* Improve documentation

---------

Co-authored-by: megalinter-bot <[email protected]>

src/safeds/data/tabular/transformation/__init__.py

@@ -1,13 +1,12 @@
 """Classes for transforming tabular data."""
 
-from ._imputer import Imputer, ImputerStrategy
+from ._imputer import Imputer
 from ._label_encoder import LabelEncoder
 from ._one_hot_encoder import OneHotEncoder
 from ._table_transformer import InvertibleTableTransformer, TableTransformer
 
 __all__ = [
     "Imputer",
-    "ImputerStrategy",
     "LabelEncoder",
     "OneHotEncoder",
     "InvertibleTableTransformer",

src/safeds/data/tabular/transformation/_imputer.py

@@ -1,30 +1,38 @@
 from __future__ import annotations
 
-from abc import ABC, abstractmethod
 from typing import Any
 
 import pandas as pd
 from sklearn.impute import SimpleImputer as sk_SimpleImputer
 
 from safeds.data.tabular.containers import Table
 from safeds.data.tabular.transformation._table_transformer import TableTransformer
+from safeds.data.tabular.typing import ImputerStrategy
 from safeds.exceptions import TransformerNotFittedError, UnknownColumnNameError
 
 
-class ImputerStrategy(ABC):
-    @abstractmethod
-    def _augment_imputer(self, imputer: sk_SimpleImputer) -> None:
-        pass
-
-
 class Imputer(TableTransformer):
     """
-    Impute the data for a given Table.
+    Replace missing values with the given strategy.
 
     Parameters
     ----------
     strategy : ImputerStrategy
-        The strategy used to impute missing values.
+        The strategy used to impute missing values. Use the classes nested inside `Imputer.Strategy` to specify it.
+
+    Examples
+    --------
+    >>> from safeds.data.tabular.containers import Column, Table
+    >>> from safeds.data.tabular.transformation import Imputer
+    >>>
+    >>> table = Table.from_columns(
+    ...     [
+    ...         Column("a", [1, 3, None]),
+    ...         Column("b", [None, 2, 3]),
+    ...     ],
+    ... )
+    >>> transformer = Imputer(Imputer.Strategy.Constant(0))
+    >>> transformed_table = transformer.fit_and_transform(table)
     """
 
     class Strategy:

src/safeds/data/tabular/typing/__init__.py

@@ -1,12 +1,14 @@
 """Types used to define the schema of a tabular dataset."""
 
 from ._column_type import Anything, Boolean, ColumnType, Integer, RealNumber, String
+from ._imputer_strategy import ImputerStrategy
 from ._schema import Schema
 
 __all__ = [
     "Anything",
     "Boolean",
     "ColumnType",
+    "ImputerStrategy",
     "Integer",
     "RealNumber",
     "Schema",

src/safeds/data/tabular/typing/_imputer_strategy.py

@@ -0,0 +1,15 @@
+from abc import ABC, abstractmethod
+
+from sklearn.impute import SimpleImputer as sk_SimpleImputer
+
+
+class ImputerStrategy(ABC):
+    """
+    The abstract base class of the different imputation strategies supported by the `Imputer`.
+
+    This class is only needed for type annotations. Use the subclasses nested inside `Imputer.Strategy` instead.
+    """
+
+    @abstractmethod
+    def _augment_imputer(self, imputer: sk_SimpleImputer) -> None:
+        pass

tests/safeds/data/tabular/transformation/test_imputer.py

@@ -1,6 +1,7 @@
 import pytest
 from safeds.data.tabular.containers import Column, Table
-from safeds.data.tabular.transformation import Imputer, ImputerStrategy
+from safeds.data.tabular.transformation import Imputer
+from safeds.data.tabular.typing import ImputerStrategy
 from safeds.exceptions import TransformerNotFittedError, UnknownColumnNameError