Merge branch 'main' into 319-better-error-for-columnstability-if-the-…

…column-contains-only-null-values

.github/workflows/megalinter.yml

@@ -11,3 +11,5 @@ jobs:
       contents: write
       issues: write
       pull-requests: write
+    secrets:
+      PAT: ${{ secrets.PAT }}

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

@@ -54,6 +54,8 @@ class Table:
     | [from_columns][safeds.data.tabular.containers._table.Table.from_columns]     | Create a table from a list of columns. |
     | [from_rows][safeds.data.tabular.containers._table.Table.from_rows]           | Create a table from a list of rows.    |
 
+    Note: When removing the last column of the table, the `number_of_columns` property will be set to 0.
+
     Parameters
     ----------
     data : Mapping[str, Sequence[Any]] | None
@@ -825,6 +827,8 @@ def keep_only_columns(self, column_names: list[str]) -> Table:
 
         This table is not modified.
 
+        Note: When removing the last column of the table, the `number_of_columns` property will be set to 0.
+
         Parameters
         ----------
         column_names : list[str]
@@ -857,6 +861,8 @@ def remove_columns(self, column_names: list[str]) -> Table:
 
         This table is not modified.
 
+        Note: When removing the last column of the table, the `number_of_columns` property will be set to 0.
+
         Parameters
         ----------
         column_names : list[str]
@@ -889,6 +895,8 @@ def remove_columns_with_missing_values(self) -> Table:
 
         This table is not modified.
 
+        Note: When removing the last column of the table, the `number_of_columns` property will be set to 0.
+
         Returns
         -------
         table : Table
@@ -902,6 +910,8 @@ def remove_columns_with_non_numerical_values(self) -> Table:
 
         This table is not modified.
 
+        Note: When removing the last column of the table, the `number_of_columns` property will be set to 0.
+
         Returns
         -------
         table : Table

src/safeds/ml/classical/classification/_classifier.py

@@ -117,7 +117,7 @@ def accuracy(self, validation_or_test_set: TaggedTable) -> float:
 
         return sk_accuracy_score(expected_values._data, predicted_values._data)
 
-    def precision(self, validation_or_test_set: TaggedTable, positive_class: Any = 1) -> float:
+    def precision(self, validation_or_test_set: TaggedTable, positive_class: Any) -> float:
         """
         Compute the classifier's precision on the given data.
 
@@ -154,7 +154,7 @@ def precision(self, validation_or_test_set: TaggedTable, positive_class: Any = 1
             return 1.0
         return n_true_positives / (n_true_positives + n_false_positives)
 
-    def recall(self, validation_or_test_set: TaggedTable, positive_class: Any = 1) -> float:
+    def recall(self, validation_or_test_set: TaggedTable, positive_class: Any) -> float:
         """
         Compute the classifier's recall on the given data.
 
@@ -191,7 +191,7 @@ def recall(self, validation_or_test_set: TaggedTable, positive_class: Any = 1) -
             return 1.0
         return n_true_positives / (n_true_positives + n_false_negatives)
 
-    def f1_score(self, validation_or_test_set: TaggedTable, positive_class: Any = 1) -> float:
+    def f1_score(self, validation_or_test_set: TaggedTable, positive_class: Any) -> float:
         """
         Compute the classifier's $F_1$-score on the given data.
 

tests/safeds/ml/classical/classification/test_classifier.py

@@ -375,7 +375,7 @@ def test_should_return_1_if_never_expected_to_be_positive(self) -> None:
     )
     def test_should_raise_if_table_is_not_tagged(self, table: Table) -> None:
         with pytest.raises(UntaggedTableError):
-            DummyClassifier().precision(table)  # type: ignore[arg-type]
+            DummyClassifier().precision(table, 1)  # type: ignore[arg-type]
 
 
 class TestRecall:
@@ -424,7 +424,7 @@ def test_should_return_1_if_never_expected_to_be_positive(self) -> None:
     )
     def test_should_raise_if_table_is_not_tagged(self, table: Table) -> None:
         with pytest.raises(UntaggedTableError):
-            DummyClassifier().recall(table)  # type: ignore[arg-type]
+            DummyClassifier().recall(table, 1)  # type: ignore[arg-type]
 
 
 class TestF1Score:
@@ -473,4 +473,4 @@ def test_should_return_1_if_never_expected_or_predicted_to_be_positive(self) ->
     )
     def test_should_raise_if_table_is_not_tagged(self, table: Table) -> None:
         with pytest.raises(UntaggedTableError):
-            DummyClassifier().f1_score(table)  # type: ignore[arg-type]
+            DummyClassifier().f1_score(table, 1)  # type: ignore[arg-type]