MAINT: Adjust the codebase to the new np.array copy keyword meaning

Author: mtsokol

pandas/core/frame.py

@@ -1919,7 +1919,7 @@ def to_numpy(
             dtype = np.dtype(dtype)
         result = self._mgr.as_array(dtype=dtype, copy=copy, na_value=na_value)
         if result.dtype is not dtype:
-            result = np.array(result, dtype=dtype, copy=False)
+            result = np.asarray(result, dtype=dtype)
 
         return result
 

pandas/tests/arrays/test_datetimelike.py

@@ -12,6 +12,7 @@
     Timestamp,
 )
 from pandas._libs.tslibs import to_offset
+from pandas.compat.numpy import np_version_gt2
 
 from pandas.core.dtypes.dtypes import PeriodDtype
 
@@ -952,13 +953,14 @@ def test_int_properties(self, timedelta_index, propname):
 
     def test_array_interface(self, timedelta_index):
         arr = timedelta_index._data
+        copy_false = None if np_version_gt2 else False
 
         # default asarray gives the same underlying data
         result = np.asarray(arr)
         expected = arr._ndarray
         assert result is expected
         tm.assert_numpy_array_equal(result, expected)
-        result = np.array(arr, copy=False)
+        result = np.array(arr, copy=copy_false)
         assert result is expected
         tm.assert_numpy_array_equal(result, expected)
 
@@ -967,7 +969,7 @@ def test_array_interface(self, timedelta_index):
         expected = arr._ndarray
         assert result is expected
         tm.assert_numpy_array_equal(result, expected)
-        result = np.array(arr, dtype="timedelta64[ns]", copy=False)
+        result = np.array(arr, dtype="timedelta64[ns]", copy=copy_false)
         assert result is expected
         tm.assert_numpy_array_equal(result, expected)
         result = np.array(arr, dtype="timedelta64[ns]")

pandas/tests/extension/array_with_attr/array.py

@@ -9,6 +9,8 @@
 
 import numpy as np
 
+from pandas.compat.numpy import np_version_gt2
+
 from pandas.core.dtypes.base import ExtensionDtype
 
 import pandas as pd
@@ -49,6 +51,8 @@ def __init__(self, values, attr=None) -> None:
 
     @classmethod
     def _from_sequence(cls, scalars, *, dtype=None, copy=False):
+        if np_version_gt2 and not copy:
+            copy = None
         data = np.array(scalars, dtype="float64", copy=copy)
         return cls(data)