style: fix linter errors

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

@@ -13,11 +13,6 @@
 from pandas import DataFrame, Series
 from scipy import stats
 
-if TYPE_CHECKING:
-    from ._tagged_table import TaggedTable
-
-from ._column import Column
-from ._row import Row
 from safeds.data.tabular.typing import ColumnType, TableSchema
 from safeds.exceptions import (
     ColumnLengthMismatchError,
@@ -30,6 +25,11 @@
     SchemaMismatchError,
     UnknownColumnNameError,
 )
+from ._column import Column
+from ._row import Row
+
+if TYPE_CHECKING:
+    from ._tagged_table import TaggedTable
 
 
 # noinspection PyProtectedMember
@@ -921,7 +921,7 @@ def tag_columns(self, target_name: str, feature_names: Optional[list[str]] = Non
         tagged_table : TaggedTable
             A new tagged table with the given target and feature names.
         """
-        from ._tagged_table import TaggedTable
+        from ._tagged_table import TaggedTable  # pylint: disable=import-outside-toplevel
         return TaggedTable(self._data, target_name, feature_names, self._schema)
 
     def transform_column(self, name: str, transformer: Callable[[Row], Any]) -> Table:

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

@@ -38,11 +38,7 @@ def __init__(
 
         super().__init__(data, schema)
 
-        if feature_names is None:
-            self._features: Table = self.drop_columns([target_name])
-        else:
-            self._features: Table = self.keep_only_columns(feature_names)
-
+        self._features: Table = self.drop_columns([target_name]) if feature_names is None else self.keep_only_columns(feature_names)
         self._target: Column = self.get_column(target_name)
 
     @property

tests/safeds/ml/test_util_sklearn.py

@@ -1,6 +1,6 @@
 import warnings
 
-from safeds.data.tabular.containers import Table, TaggedTable
+from safeds.data.tabular.containers import Table
 from safeds.ml.regression import LinearRegression
 
 
@@ -9,7 +9,7 @@ def test_predict_should_not_warn_about_feature_names() -> None:
     See https://github.com/Safe-DS/Stdlib/issues/51.
     """
 
-    training_set = TaggedTable(Table({"a": [1, 2, 3], "b": [2, 4, 6]}), target_name="b")
+    training_set = Table({"a": [1, 2, 3], "b": [2, 4, 6]}).tag_columns(target_name="b")
 
     model = LinearRegression()
     fitted_model = model.fit(training_set)