Fix pre-commit.ci errors: line length and NumPy API deprecation, proper type checking with isinstance and type ignore

Author: ali-aqib

pandas/core/apply.py

@@ -848,7 +848,8 @@ def agg_or_apply_list_like(
 
                 # Only proceed if we have numeric columns
                 if not numeric_obj.empty:
-                    # Create kwargs without numeric_only to avoid passing it to Series methods
+                    # Create kwargs without numeric_only to avoid
+                    # passing it to Series methods
                     kwargs_filtered = {
                         k: v for k, v in kwargs.items() if k != "numeric_only"
                     }
@@ -864,7 +865,13 @@ def agg_or_apply_list_like(
                     from pandas import DataFrame
 
                     # Get function names for index
-                    keys = list(self.func) if is_list_like(self.func) else []
+                    if isinstance(self.func, list):
+                        keys = self.func  # type: ignore[assignment]
+                    elif isinstance(self.func, dict):
+                        keys = list(self.func.keys())
+                    else:
+                        keys = []
+
                     return DataFrame(index=keys)
 
         keys, results = self.compute_list_like(op_name, obj, kwargs)

pandas/tests/apply/test_frame_apply_numeric_only.py

@@ -206,14 +206,15 @@ def test_agg_list_numeric_only_with_datetime(self):
 
     def test_agg_list_numeric_only_large_dataframe(self):
         """Test with a larger DataFrame for performance verification."""
-        np.random.seed(42)
+        rng = np.random.default_rng(42)
         df = DataFrame(
             {
-                "A": np.random.randint(1, 100, 1000),
-                "B": np.random.randn(1000),
+                "A": rng.integers(1, 100, 1000),
+                "B": rng.standard_normal(1000),
                 "C": ["text"] * 1000,
             }
         )
+
         result = df.agg(["sum", "mean", "std"], numeric_only=True)
 
         # Just verify structure, not exact values due to randomness