feat: Added Table.transform_table method which returns the transformed Table

src/safeds/data/tabular/containers/_table.py

@@ -34,6 +34,8 @@
 if TYPE_CHECKING:
     from collections.abc import Callable, Iterable
 
+    from safeds.data.tabular.transformation import TableTransformer
+
     from ._tagged_table import TaggedTable
 
 
@@ -991,6 +993,27 @@ def transform_column(self, name: str, transformer: Callable[[Row], Any]) -> Tabl
             return self.replace_column(name, result)
         raise UnknownColumnNameError([name])
 
+    def transform_table(self, transformer: TableTransformer) -> Table:
+        """
+        Apply a learned transformation onto this table.
+
+        Parameters
+        ----------
+        transformer : TableTransformer
+            The transformer which transforms the given table
+
+        Returns
+        -------
+        transformed_table : Table
+            The transformed table.
+
+        Raises
+        ------
+        TransformerNotFittedError
+            If the transformer has not been fitted yet.
+        """
+        return transformer.transform(self)
+
     # ------------------------------------------------------------------------------------------------------------------
     # Plotting
     # ------------------------------------------------------------------------------------------------------------------

tests/safeds/data/tabular/containers/_table/test_transform_table.py

@@ -0,0 +1,36 @@
+import pytest
+from safeds.data.tabular.containers import Table
+from safeds.data.tabular.exceptions import TransformerNotFittedError, UnknownColumnNameError
+from safeds.data.tabular.transformation import OneHotEncoder
+
+
+class TestTransform:
+    def test_should_raise_if_column_not_found(self) -> None:
+        table_to_fit = Table.from_dict(
+            {
+                "col1": ["a", "b", "c"],
+            },
+        )
+
+        transformer = OneHotEncoder().fit(table_to_fit, None)
+
+        table_to_transform = Table.from_dict(
+            {
+                "col2": ["a", "b", "c"],
+            },
+        )
+
+        with pytest.raises(UnknownColumnNameError):
+            table_to_transform.transform_table(transformer)
+
+    def test_should_raise_if_not_fitted(self) -> None:
+        table = Table.from_dict(
+            {
+                "col1": ["a", "b", "c"],
+            },
+        )
+
+        transformer = OneHotEncoder()
+
+        with pytest.raises(TransformerNotFittedError):
+            table.transform_table(transformer)