feat: allow calling correlation_heatmap with non-numerical columns

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

@@ -975,22 +975,16 @@ def shuffle(self) -> Table:
 
     def correlation_heatmap(self) -> None:
         """
-        Plot a correlation heatmap of an entire table. This function can only plot real numerical data.
-
-        Raises
-        -------
-        TypeError
-            If the table contains non-numerical data or complex data.
+        Plot a correlation heatmap for all numerical columns of this `Table`.
         """
-        for column in self.to_columns():
-            if not column.type.is_numeric():
-                raise NonNumericColumnError(column.name)
+        only_numerical = Table.from_columns(self.list_columns_with_numerical_values())
+
         sns.heatmap(
-            data=self._data.corr(),
+            data=only_numerical._data.corr(),
             vmin=-1,
             vmax=1,
-            xticklabels=self.get_column_names(),
-            yticklabels=self.get_column_names(),
+            xticklabels=only_numerical.get_column_names(),
+            yticklabels=only_numerical.get_column_names(),
             cmap="vlag",
         )
         plt.tight_layout()

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

@@ -1,15 +1,13 @@
 import _pytest
 import matplotlib.pyplot as plt
 import pandas as pd
-import pytest
 from safeds.data.tabular.containers import Table
-from safeds.exceptions import NonNumericColumnError
 
 
-def test_correlation_heatmap_non_numeric() -> None:
-    with pytest.raises(NonNumericColumnError):
-        table = Table(pd.DataFrame(data={"A": [1, 2, "A"], "B": [1, 2, "A"]}))
-        table.correlation_heatmap()
+def test_correlation_heatmap_non_numeric(monkeypatch: _pytest.monkeypatch) -> None:
+    monkeypatch.setattr(plt, "show", lambda: None)
+    table = Table(pd.DataFrame(data={"A": [1, 2, "A"], "B": [1, 2, 3]}))
+    table.correlation_heatmap()
 
 
 def test_correlation_heatmap(monkeypatch: _pytest.monkeypatch) -> None: