added error to Imputer_Mode when there are multiple most frequent val…

…ues in a Column

Runtime/safe-ds/safeds/data/tabular/transformation/_imputer.py

@@ -4,9 +4,10 @@
 from typing import Any, Optional
 
 import pandas as pd
-from safeds.data.tabular import Table
 from sklearn.impute import SimpleImputer
 
+from safeds.data.tabular import Table, ColumnStatistics
+
 
 class ImputerStrategy(ABC):
     @abstractmethod
@@ -86,6 +87,11 @@ def fit(self, table: Table, column_names: Optional[list[str]] = None) -> None:
         if column_names is None:
             column_names = table.schema.get_column_names()
 
+        if self._imp.strategy == "most_frequent":
+            for name in column_names:
+                if 1 < len(ColumnStatistics(table.get_column(name)).mode()):
+                    raise IndexError("There are multiple frequent values in a column given for the Imputer")
+
         self._column_names = column_names
         indices = [
             table.schema._get_column_index_by_name(name) for name in self._column_names

Runtime/safe-ds/tests/data/tabular/transformation/_imputer/test_imputer.py

@@ -1,5 +1,7 @@
 import numpy as np
 import pandas as pd
+import pytest
+
 from safeds.data.tabular import Table
 from safeds.data.tabular.transformation import Imputer
 
@@ -31,6 +33,13 @@ def test_imputer_mode() -> None:
     assert new_table.get_column("col1")._data[0] == column.statistics.mode()[0]
 
 
+def test_imputer_mode_invalid() -> None:
+    table = Table(pd.DataFrame(data={"col1": [np.nan, 2, 3, 4, 5]}))
+    imp = Imputer(Imputer.Strategy.Mode())
+    with pytest.raises(IndexError):
+        imp.fit_transform(table)
+
+
 def test_imputer_constant() -> None:
     table = Table(pd.DataFrame(data={"col1": [np.nan, 2, 3, 4, 5]}))
     imp = Imputer(Imputer.Strategy.Constant(0))