BUG: ArrayManager not respecting copy keyword (#44889)

pandas/core/internals/construction.py

@@ -35,7 +35,6 @@
 )
 from pandas.core.dtypes.common import (
     is_1d_only_ea_dtype,
-    is_datetime64tz_dtype,
     is_datetime_or_timedelta_dtype,
     is_dtype_equal,
     is_extension_array_dtype,
@@ -44,7 +43,6 @@
     is_named_tuple,
     is_object_dtype,
 )
-from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCSeries,
@@ -475,23 +473,16 @@ def dict_to_mgr(
         keys = list(data.keys())
         columns = Index(keys)
         arrays = [com.maybe_iterable_to_list(data[k]) for k in keys]
-        # GH#24096 need copy to be deep for datetime64tz case
-        # TODO: See if we can avoid these copies
         arrays = [arr if not isinstance(arr, Index) else arr._data for arr in arrays]
-        arrays = [
-            arr if not is_datetime64tz_dtype(arr) else arr.copy() for arr in arrays
-        ]
 
     if copy:
-        # arrays_to_mgr (via form_blocks) won't make copies for EAs
-        # dtype attr check to exclude EADtype-castable strs
-        arrays = [
-            x
-            if not hasattr(x, "dtype") or not isinstance(x.dtype, ExtensionDtype)
-            else x.copy()
-            for x in arrays
-        ]
-        # TODO: can we get rid of the dt64tz special case above?
+        if typ == "block":
+            # We only need to copy arrays that will not get consolidated, i.e.
+            #  only EA arrays
+            arrays = [x.copy() if isinstance(x, ExtensionArray) else x for x in arrays]
+        else:
+            # dtype check to exclude e.g. range objects, scalars
+            arrays = [x.copy() if hasattr(x, "dtype") else x for x in arrays]
 
     return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
 

pandas/tests/frame/indexing/test_setitem.py

@@ -421,10 +421,6 @@ def test_setitem_frame_duplicate_columns(self, using_array_manager, request):
             # TODO(ArrayManager) .loc still overwrites
             expected["B"] = expected["B"].astype("int64")
 
-            mark = pytest.mark.xfail(
-                reason="Both 'A' columns get set with 3 instead of 0 and 3"
-            )
-            request.node.add_marker(mark)
         else:
             # set these with unique columns to be extra-unambiguous
             expected[2] = expected[2].astype(np.int64)

pandas/tests/frame/test_constructors.py

@@ -2157,8 +2157,6 @@ def test_constructor_ndarray_copy(self, float_frame, using_array_manager):
             arr[0, 0] = 1000
             assert df.iloc[0, 0] == 1000
 
-    # TODO(ArrayManager) keep view on Series?
-    @td.skip_array_manager_not_yet_implemented
     def test_constructor_series_copy(self, float_frame):
         series = float_frame._series
 
@@ -2507,13 +2505,10 @@ def test_constructor_list_str_na(self, string_dtype):
     def test_dict_nocopy(
         self, request, copy, any_numeric_ea_dtype, any_numpy_dtype, using_array_manager
     ):
-        if using_array_manager and not (
-            (any_numpy_dtype in (tm.STRING_DTYPES + tm.BYTES_DTYPES))
-            or (
-                any_numpy_dtype
-                in (tm.DATETIME64_DTYPES + tm.TIMEDELTA64_DTYPES + tm.BOOL_DTYPES)
-                and copy
-            )
+        if (
+            using_array_manager
+            and not copy
+            and not (any_numpy_dtype in (tm.STRING_DTYPES + tm.BYTES_DTYPES))
         ):
             # TODO(ArrayManager) properly honor copy keyword for dict input
             td.mark_array_manager_not_yet_implemented(request)

pandas/tests/frame/test_reductions.py

@@ -773,11 +773,7 @@ def test_operators_timedelta64(self):
     def test_std_timedelta64_skipna_false(self):
         # GH#37392
         tdi = pd.timedelta_range("1 Day", periods=10)
-        df = DataFrame({"A": tdi, "B": tdi})
-        # Copy is needed for ArrayManager case, otherwise setting df.iloc
-        #  below edits tdi, alterting both df['A'] and df['B']
-        #  FIXME: passing copy=True to constructor does not fix this
-        df = df.copy()
+        df = DataFrame({"A": tdi, "B": tdi}, copy=True)
         df.iloc[-2, -1] = pd.NaT
 
         result = df.std(skipna=False)
@@ -1064,11 +1060,7 @@ def test_idxmax_idxmin_convert_dtypes(self, op, expected_value):
 
     def test_idxmax_dt64_multicolumn_axis1(self):
         dti = date_range("2016-01-01", periods=3)
-        df = DataFrame({3: dti, 4: dti[::-1]})
-        # FIXME: copy needed for ArrayManager, otherwise setting with iloc
-        #  below also sets df.iloc[-1, 1]; passing copy=True to DataFrame
-        #  does not solve this.
-        df = df.copy()
+        df = DataFrame({3: dti, 4: dti[::-1]}, copy=True)
         df.iloc[0, 0] = pd.NaT
 
         df._consolidate_inplace()

pandas/tests/indexing/multiindex/test_setitem.py

@@ -214,11 +214,9 @@ def test_multiindex_assignment_single_dtype(self, using_array_manager):
         exp = Series(arr, index=[8, 10], name="c", dtype="int64")
         result = df.loc[4, "c"]
         tm.assert_series_equal(result, exp)
-        if not using_array_manager:
-            # FIXME(ArrayManager): this correctly preserves dtype,
-            #  but incorrectly is not inplace.
-            # extra check for inplace-ness
-            tm.assert_numpy_array_equal(view, exp.values)
+
+        # extra check for inplace-ness
+        tm.assert_numpy_array_equal(view, exp.values)
 
         # arr + 0.5 cannot be cast losslessly to int, so we upcast
         df.loc[4, "c"] = arr + 0.5