[ArrayManager] TST: run (+fix/skip) pandas/tests/frame/indexing tests (…

…#40323)

.github/workflows/ci.yml

@@ -155,10 +155,7 @@ jobs:
       run: |
         source activate pandas-dev
 
-        pytest pandas/tests/frame/methods
-        pytest pandas/tests/frame/test_constructors.py
-        pytest pandas/tests/frame/test_*
-        pytest pandas/tests/frame/test_reductions.py
+        pytest pandas/tests/frame/
         pytest pandas/tests/reductions/
         pytest pandas/tests/generic/test_generic.py
         pytest pandas/tests/arithmetic/
@@ -170,10 +167,6 @@ jobs:
         pytest pandas/tests/series/test_*
 
         # indexing subset (temporary since other tests don't pass yet)
-        pytest pandas/tests/frame/indexing/test_indexing.py::TestDataFrameIndexing::test_setitem_boolean
-        pytest pandas/tests/frame/indexing/test_where.py
-        pytest pandas/tests/frame/indexing/test_setitem.py::TestDataFrameSetItem::test_setitem_multi_index
-        pytest pandas/tests/frame/indexing/test_setitem.py::TestDataFrameSetItem::test_setitem_listlike_indexer_duplicate_columns
         pytest pandas/tests/indexing/multiindex/test_setitem.py::TestMultiIndexSetItem::test_astype_assignment_with_dups
         pytest pandas/tests/indexing/multiindex/test_setitem.py::TestMultiIndexSetItem::test_frame_setitem_multi_column
 

pandas/core/internals/array_manager.py

@@ -861,7 +861,7 @@ def iset(self, loc: Union[int, slice, np.ndarray], value):
             # DataFrame into 1D array when loc is an integer
             if isinstance(value, np.ndarray) and value.ndim == 2:
                 assert value.shape[1] == 1
-                value = value[0, :]
+                value = value[:, 0]
 
             # TODO we receive a datetime/timedelta64 ndarray from DataFrame._iset_item
             # but we should avoid that and pass directly the proper array
@@ -1163,10 +1163,6 @@ def axes(self):
     def index(self) -> Index:
         return self._axes[0]
 
-    @property
-    def array(self):
-        return self.arrays[0]
-
     @property
     def dtype(self):
         return self.array.dtype

pandas/core/internals/base.py

@@ -126,6 +126,13 @@ def isna(self: T, func) -> T:
 class SingleDataManager(DataManager):
     ndim = 1
 
+    @property
+    def array(self):
+        """
+        Quick access to the backing array of the Block or SingleArrayManager.
+        """
+        return self.arrays[0]  # type: ignore[attr-defined]
+
 
 def interleaved_dtype(dtypes: List[DtypeObj]) -> Optional[DtypeObj]:
     """

pandas/tests/frame/indexing/test_indexing.py

@@ -8,6 +8,7 @@
 import pytest
 
 from pandas._libs import iNaT
+import pandas.util._test_decorators as td
 
 from pandas.core.dtypes.common import is_integer
 
@@ -534,6 +535,7 @@ def test_getitem_setitem_integer_slice_keyerrors(self):
         with pytest.raises(KeyError, match=r"^3$"):
             df2.loc[3:11] = 0
 
+    @td.skip_array_manager_invalid_test  # already covered in test_iloc_col_slice_view
     def test_fancy_getitem_slice_mixed(self, float_frame, float_string_frame):
         sliced = float_string_frame.iloc[:, -3:]
         assert sliced["D"].dtype == np.float64
@@ -592,6 +594,7 @@ def test_getitem_fancy_scalar(self, float_frame):
             for idx in f.index[::5]:
                 assert ix[idx, col] == ts[idx]
 
+    @td.skip_array_manager_invalid_test  # TODO(ArrayManager) rewrite not using .values
     def test_setitem_fancy_scalar(self, float_frame):
         f = float_frame
         expected = float_frame.copy()
@@ -631,6 +634,7 @@ def test_getitem_fancy_boolean(self, float_frame):
         expected = f.reindex(index=f.index[boolvec], columns=["C", "D"])
         tm.assert_frame_equal(result, expected)
 
+    @td.skip_array_manager_invalid_test  # TODO(ArrayManager) rewrite not using .values
     def test_setitem_fancy_boolean(self, float_frame):
         # from 2d, set with booleans
         frame = float_frame.copy()
@@ -990,21 +994,29 @@ def test_iloc_row(self):
         expected = df.loc[8:14]
         tm.assert_frame_equal(result, expected)
 
+        # list of integers
+        result = df.iloc[[1, 2, 4, 6]]
+        expected = df.reindex(df.index[[1, 2, 4, 6]])
+        tm.assert_frame_equal(result, expected)
+
+    def test_iloc_row_slice_view(self, using_array_manager):
+        df = DataFrame(np.random.randn(10, 4), index=range(0, 20, 2))
+        original = df.copy()
+
         # verify slice is view
         # setting it makes it raise/warn
+        subset = df.iloc[slice(4, 8)]
+
         msg = r"\nA value is trying to be set on a copy of a slice from a DataFrame"
         with pytest.raises(com.SettingWithCopyError, match=msg):
-            result[2] = 0.0
+            subset[2] = 0.0
 
-        exp_col = df[2].copy()
-        exp_col[4:8] = 0.0
+        exp_col = original[2].copy()
+        # TODO(ArrayManager) verify it is expected that the original didn't change
+        if not using_array_manager:
+            exp_col[4:8] = 0.0
         tm.assert_series_equal(df[2], exp_col)
 
-        # list of integers
-        result = df.iloc[[1, 2, 4, 6]]
-        expected = df.reindex(df.index[[1, 2, 4, 6]])
-        tm.assert_frame_equal(result, expected)
-
     def test_iloc_col(self):
 
         df = DataFrame(np.random.randn(4, 10), columns=range(0, 20, 2))
@@ -1022,19 +1034,32 @@ def test_iloc_col(self):
         expected = df.loc[:, 8:14]
         tm.assert_frame_equal(result, expected)
 
-        # verify slice is view
-        # and that we are setting a copy
-        msg = r"\nA value is trying to be set on a copy of a slice from a DataFrame"
-        with pytest.raises(com.SettingWithCopyError, match=msg):
-            result[8] = 0.0
-
-        assert (df[8] == 0).all()
-
         # list of integers
         result = df.iloc[:, [1, 2, 4, 6]]
         expected = df.reindex(columns=df.columns[[1, 2, 4, 6]])
         tm.assert_frame_equal(result, expected)
 
+    def test_iloc_col_slice_view(self, using_array_manager):
+        df = DataFrame(np.random.randn(4, 10), columns=range(0, 20, 2))
+        original = df.copy()
+        subset = df.iloc[:, slice(4, 8)]
+
+        if not using_array_manager:
+            # verify slice is view
+            # and that we are setting a copy
+            msg = r"\nA value is trying to be set on a copy of a slice from a DataFrame"
+            with pytest.raises(com.SettingWithCopyError, match=msg):
+                subset[8] = 0.0
+
+            assert (df[8] == 0).all()
+        else:
+            # TODO(ArrayManager) verify this is the desired behaviour
+            subset[8] = 0.0
+            # subset changed
+            assert (subset[8] == 0).all()
+            # but df itself did not change (setitem replaces full column)
+            tm.assert_frame_equal(df, original)
+
     def test_loc_duplicates(self):
         # gh-17105
 
@@ -1218,7 +1243,7 @@ def test_setitem(self, uint64_frame):
         )
 
 
-def test_object_casting_indexing_wraps_datetimelike():
+def test_object_casting_indexing_wraps_datetimelike(using_array_manager):
     # GH#31649, check the indexing methods all the way down the stack
     df = DataFrame(
         {
@@ -1240,6 +1265,10 @@ def test_object_casting_indexing_wraps_datetimelike():
     assert isinstance(ser.values[1], Timestamp)
     assert isinstance(ser.values[2], pd.Timedelta)
 
+    if using_array_manager:
+        # remainder of the test checking BlockManager internals
+        return
+
     mgr = df._mgr
     mgr._rebuild_blknos_and_blklocs()
     arr = mgr.fast_xs(0)

pandas/tests/frame/indexing/test_insert.py

@@ -72,11 +72,17 @@ def test_insert_with_columns_dups(self):
         )
         tm.assert_frame_equal(df, exp)
 
-    def test_insert_item_cache(self):
+    def test_insert_item_cache(self, using_array_manager):
         df = DataFrame(np.random.randn(4, 3))
         ser = df[0]
 
-        with tm.assert_produces_warning(PerformanceWarning):
+        if using_array_manager:
+            expected_warning = None
+        else:
+            # with BlockManager warn about high fragmentation of single dtype
+            expected_warning = PerformanceWarning
+
+        with tm.assert_produces_warning(expected_warning):
             for n in range(100):
                 df[n + 3] = df[1] * n
 

pandas/tests/frame/indexing/test_setitem.py

@@ -3,6 +3,8 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
+
 from pandas.core.dtypes.base import registry as ea_registry
 from pandas.core.dtypes.common import (
     is_categorical_dtype,
@@ -298,12 +300,12 @@ def test_setitem_dt64tz(self, timezone_frame):
 
         # assert that A & C are not sharing the same base (e.g. they
         # are copies)
-        b1 = df._mgr.blocks[1]
-        b2 = df._mgr.blocks[2]
-        tm.assert_extension_array_equal(b1.values, b2.values)
-        b1base = b1.values._data.base
-        b2base = b2.values._data.base
-        assert b1base is None or (id(b1base) != id(b2base))
+        v1 = df._mgr.arrays[1]
+        v2 = df._mgr.arrays[2]
+        tm.assert_extension_array_equal(v1, v2)
+        v1base = v1._data.base
+        v2base = v2._data.base
+        assert v1base is None or (id(v1base) != id(v2base))
 
         # with nan
         df2 = df.copy()
@@ -366,7 +368,7 @@ def test_setitem_frame_length_0_str_key(self, indexer):
         expected["A"] = expected["A"].astype("object")
         tm.assert_frame_equal(df, expected)
 
-    def test_setitem_frame_duplicate_columns(self):
+    def test_setitem_frame_duplicate_columns(self, using_array_manager):
         # GH#15695
         cols = ["A", "B", "C"] * 2
         df = DataFrame(index=range(3), columns=cols)
@@ -382,6 +384,11 @@ def test_setitem_frame_duplicate_columns(self):
             columns=cols,
             dtype="object",
         )
+        if using_array_manager:
+            # setitem replaces column so changes dtype
+            expected["C"] = expected["C"].astype("int64")
+            # TODO(ArrayManager) .loc still overwrites
+            expected["B"] = expected["B"].astype("int64")
         tm.assert_frame_equal(df, expected)
 
     @pytest.mark.parametrize("cols", [["a", "b", "c"], ["a", "a", "a"]])
@@ -628,6 +635,8 @@ def test_setitem_object_array_of_tzaware_datetimes(self, idx, expected):
 
 
 class TestDataFrameSetItemWithExpansion:
+    # TODO(ArrayManager) update parent (_maybe_update_cacher)
+    @td.skip_array_manager_not_yet_implemented
     def test_setitem_listlike_views(self):
         # GH#38148
         df = DataFrame({"a": [1, 2, 3], "b": [4, 4, 6]})
@@ -699,7 +708,7 @@ def test_setitem_with_expansion_categorical_dtype(self):
 
         result1 = df["D"]
         result2 = df["E"]
-        tm.assert_categorical_equal(result1._mgr._block.values, cat)
+        tm.assert_categorical_equal(result1._mgr.array, cat)
 
         # sorting
         ser.name = "E"
@@ -767,6 +776,7 @@ def inc(x):
 
 
 class TestDataFrameSetItemBooleanMask:
+    @td.skip_array_manager_invalid_test  # TODO(ArrayManager) rewrite not using .values
     @pytest.mark.parametrize(
         "mask_type",
         [lambda df: df > np.abs(df) / 2, lambda df: (df > np.abs(df) / 2).values],

pandas/tests/frame/indexing/test_xs.py

@@ -109,14 +109,22 @@ def test_xs_keep_level(self):
         result = df.xs([2008, "sat"], level=["year", "day"], drop_level=False)
         tm.assert_frame_equal(result, expected)
 
-    def test_xs_view(self):
+    def test_xs_view(self, using_array_manager):
         # in 0.14 this will return a view if possible a copy otherwise, but
         # this is numpy dependent
 
         dm = DataFrame(np.arange(20.0).reshape(4, 5), index=range(4), columns=range(5))
 
-        dm.xs(2)[:] = 10
-        assert (dm.xs(2) == 10).all()
+        if using_array_manager:
+            # INFO(ArrayManager) with ArrayManager getting a row as a view is
+            # not possible
+            msg = r"\nA value is trying to be set on a copy of a slice from a DataFrame"
+            with pytest.raises(com.SettingWithCopyError, match=msg):
+                dm.xs(2)[:] = 20
+            assert not (dm.xs(2) == 20).any()
+        else:
+            dm.xs(2)[:] = 20
+            assert (dm.xs(2) == 20).all()
 
 
 class TestXSWithMultiIndex:
@@ -327,10 +335,26 @@ def test_xs_droplevel_false(self):
         expected = DataFrame({"a": [1]})
         tm.assert_frame_equal(result, expected)
 
-    def test_xs_droplevel_false_view(self):
+    def test_xs_droplevel_false_view(self, using_array_manager):
         # GH#37832
         df = DataFrame([[1, 2, 3]], columns=Index(["a", "b", "c"]))
         result = df.xs("a", axis=1, drop_level=False)
-        df.values[0, 0] = 2
-        expected = DataFrame({"a": [2]})
+        # check that result still views the same data as df
+        assert np.shares_memory(result.iloc[:, 0]._values, df.iloc[:, 0]._values)
+        # modifying original df also modifies result when having a single block
+        df.iloc[0, 0] = 2
+        if not using_array_manager:
+            expected = DataFrame({"a": [2]})
+        else:
+            # TODO(ArrayManager) iloc does not update the array inplace using
+            # "split" path
+            expected = DataFrame({"a": [1]})
+        tm.assert_frame_equal(result, expected)
+
+        # with mixed dataframe, modifying the parent doesn't modify result
+        # TODO the "split" path behaves differently here as with single block
+        df = DataFrame([[1, 2.5, "a"]], columns=Index(["a", "b", "c"]))
+        result = df.xs("a", axis=1, drop_level=False)
+        df.iloc[0, 0] = 2
+        expected = DataFrame({"a": [1]})
         tm.assert_frame_equal(result, expected)