Backport PR #59545 on branch 2.2.x (CI: Fix ci for numpy 2 failures) (#59550)

Backport PR #59545: CI: Fix ci for numpy 2 failures

Co-authored-by: Patrick Hoefler <[email protected]>

Author: meeseeksmachine

pandas/plotting/_matplotlib/core.py

@@ -547,7 +547,7 @@ def _maybe_right_yaxis(self, ax: Axes, axes_num: int) -> Axes:
                 new_ax.set_yscale("log")
             elif self.logy == "sym" or self.loglog == "sym":
                 new_ax.set_yscale("symlog")
-            return new_ax  # type: ignore[return-value]
+            return new_ax
 
     @final
     @cache_readonly

pandas/tests/io/test_parquet.py

@@ -1195,6 +1195,10 @@ def test_duplicate_columns(self, fp):
         msg = "Cannot create parquet dataset with duplicate column names"
         self.check_error_on_write(df, fp, ValueError, msg)
 
+    @pytest.mark.xfail(
+        Version(np.__version__) >= Version("2.0.0"),
+        reason="fastparquet uses np.float_ in numpy2",
+    )
     def test_bool_with_none(self, fp):
         df = pd.DataFrame({"a": [True, None, False]})
         expected = pd.DataFrame({"a": [1.0, np.nan, 0.0]}, dtype="float16")

pandas/tests/plotting/frame/test_frame.py

@@ -44,6 +44,7 @@
     _check_visible,
     get_y_axis,
 )
+from pandas.util.version import Version
 
 from pandas.io.formats.printing import pprint_thing
 
@@ -2487,8 +2488,14 @@ def test_group_subplot_invalid_column_name(self):
         d = {"a": np.arange(10), "b": np.arange(10)}
         df = DataFrame(d)
 
-        with pytest.raises(ValueError, match=r"Column label\(s\) \['bad_name'\]"):
-            df.plot(subplots=[("a", "bad_name")])
+        if Version(np.__version__) < Version("2.0.0"):
+            with pytest.raises(ValueError, match=r"Column label\(s\) \['bad_name'\]"):
+                df.plot(subplots=[("a", "bad_name")])
+        else:
+            with pytest.raises(
+                ValueError, match=r"Column label\(s\) \[np\.str\_\('bad_name'\)\]"
+            ):
+                df.plot(subplots=[("a", "bad_name")])
 
     def test_group_subplot_duplicated_column(self):
         d = {"a": np.arange(10), "b": np.arange(10), "c": np.arange(10)}