[ArrayManager] TST: get tests running for /tests/frame

.github/workflows/ci.yml

@@ -153,7 +153,7 @@ jobs:
       run: |
         source activate pandas-dev
         pytest pandas/tests/frame/methods --array-manager
-        pytest pandas/tests/frame/test_reductions.py --array-manager
+        pytest pandas/tests/frame/test_* --array-manager
         pytest pandas/tests/reductions/ --array-manager
         pytest pandas/tests/generic/test_generic.py --array-manager
         pytest pandas/tests/arithmetic/ --array-manager

pandas/core/internals/array_manager.py

@@ -816,7 +816,13 @@ def insert(self, loc: int, item: Hashable, value, allow_duplicates: bool = False
 
         value = extract_array(value, extract_numpy=True)
         if value.ndim == 2:
-            value = value[0, :]
+            if value.shape[0] == 1:
+                value = value[0, :]
+            else:
+                raise ValueError(
+                    f"expected 1D array, got array with shape {value.shape}"
+                )
+
         # TODO self.arrays can be empty
         # assert len(value) == len(self.arrays[0])
 

pandas/tests/frame/test_arithmetic.py

@@ -7,6 +7,8 @@
 import pytest
 import pytz
 
+import pandas.util._test_decorators as td
+
 import pandas as pd
 from pandas import (
     DataFrame,
@@ -686,6 +688,7 @@ def test_df_add_2d_array_collike_broadcasts(self):
         result = collike + df
         tm.assert_frame_equal(result, expected)
 
+    @td.skip_array_manager_not_yet_implemented  # TODO(ArrayManager) decide on dtypes
     def test_df_arith_2d_array_rowlike_broadcasts(self, all_arithmetic_operators):
         # GH#23000
         opname = all_arithmetic_operators
@@ -707,6 +710,7 @@ def test_df_arith_2d_array_rowlike_broadcasts(self, all_arithmetic_operators):
         result = getattr(df, opname)(rowlike)
         tm.assert_frame_equal(result, expected)
 
+    @td.skip_array_manager_not_yet_implemented  # TODO(ArrayManager) decide on dtypes
     def test_df_arith_2d_array_collike_broadcasts(self, all_arithmetic_operators):
         # GH#23000
         opname = all_arithmetic_operators
@@ -1351,7 +1355,7 @@ def test_strings_to_numbers_comparisons_raises(self, compare_operators_no_eq_ne)
 
     def test_comparison_protected_from_errstate(self):
         missing_df = tm.makeDataFrame()
-        missing_df.iloc[0]["A"] = np.nan
+        missing_df.loc[missing_df.index[0], "A"] = np.nan
         with np.errstate(invalid="ignore"):
             expected = missing_df.values < 0
         with np.errstate(invalid="raise"):

pandas/tests/frame/test_block_internals.py

@@ -9,6 +9,7 @@
 import pytest
 
 from pandas.errors import PerformanceWarning
+import pandas.util._test_decorators as td
 
 import pandas as pd
 from pandas import (
@@ -30,6 +31,11 @@
 # structure
 
 
+# TODO(ArrayManager) check which of those tests need to be rewritten to test the
+# equivalent for ArrayManager
+pytestmark = td.skip_array_manager_invalid_test
+
+
 class TestDataFrameBlockInternals:
     def test_setitem_invalidates_datetime_index_freq(self):
         # GH#24096 altering a datetime64tz column inplace invalidates the

pandas/tests/frame/test_constructors.py

@@ -18,6 +18,7 @@
 import pytz
 
 from pandas.compat import np_version_under1p19
+import pandas.util._test_decorators as td
 
 from pandas.core.dtypes.common import is_integer_dtype
 from pandas.core.dtypes.dtypes import (
@@ -165,7 +166,10 @@ def test_constructor_cast_failure(self):
         df["foo"] = np.ones((4, 2)).tolist()
 
         # this is not ok
-        msg = "Wrong number of items passed 2, placement implies 1"
+        msg = (
+            "Wrong number of items passed 2, placement implies 1"
+            "|expected 1D array, got array"
+        )
         with pytest.raises(ValueError, match=msg):
             df["test"] = np.ones((4, 2))
 
@@ -180,12 +184,15 @@ def test_constructor_dtype_copy(self):
         new_df["col1"] = 200.0
         assert orig_df["col1"][0] == 1.0
 
-    def test_constructor_dtype_nocast_view(self):
+    def test_constructor_dtype_nocast_view_dataframe(self):
         df = DataFrame([[1, 2]])
         should_be_view = DataFrame(df, dtype=df[0].dtype)
         should_be_view[0][0] = 99
         assert df.values[0, 0] == 99
 
+    @td.skip_array_manager_invalid_test  # TODO(ArrayManager) keep view on 2D array?
+    def test_constructor_dtype_nocast_view_2d_array(self):
+        df = DataFrame([[1, 2]])
         should_be_view = DataFrame(df.values, dtype=df[0].dtype)
         should_be_view[0][0] = 97
         assert df.values[0, 0] == 97
@@ -1937,6 +1944,7 @@ def test_constructor_frame_copy(self, float_frame):
         assert (cop["A"] == 5).all()
         assert not (float_frame["A"] == 5).all()
 
+    @td.skip_array_manager_invalid_test  # TODO(ArrayManager) keep view on 2D array?
     def test_constructor_ndarray_copy(self, float_frame):
         df = DataFrame(float_frame.values)
 

pandas/tests/frame/test_nonunique_indexes.py

@@ -291,7 +291,7 @@ def test_multi_dtype2(self):
         expected = DataFrame([[1, 2, "foo", "bar"]], columns=["a", "a.1", "a.2", "a.3"])
         tm.assert_frame_equal(df, expected)
 
-    def test_dups_across_blocks(self):
+    def test_dups_across_blocks(self, using_array_manager):
         # dups across blocks
         df_float = DataFrame(np.random.randn(10, 3), dtype="float64")
         df_int = DataFrame(np.random.randn(10, 3), dtype="int64")
@@ -302,8 +302,9 @@ def test_dups_across_blocks(self):
         )
         df = pd.concat([df_float, df_int, df_bool, df_object, df_dt], axis=1)
 
-        assert len(df._mgr.blknos) == len(df.columns)
-        assert len(df._mgr.blklocs) == len(df.columns)
+        if not using_array_manager:
+            assert len(df._mgr.blknos) == len(df.columns)
+            assert len(df._mgr.blklocs) == len(df.columns)
 
         # testing iloc
         for i in range(len(df.columns)):

pandas/tests/frame/test_repr_info.py

@@ -26,14 +26,16 @@
 
 
 class TestDataFrameReprInfoEtc:
-    def test_repr_bytes_61_lines(self):
+    def test_repr_bytes_61_lines(self, using_array_manager):
         # GH#12857
         lets = list("ACDEFGHIJKLMNOP")
         slen = 50
         nseqs = 1000
         words = [[np.random.choice(lets) for x in range(slen)] for _ in range(nseqs)]
         df = DataFrame(words).astype("U1")
-        assert (df.dtypes == object).all()
+        # TODO(Arraymanager) astype("U1") actually gives this dtype instead of object
+        if not using_array_manager:
+            assert (df.dtypes == object).all()
 
         # smoke tests; at one point this raised with 61 but not 60
         repr(df)

pandas/tests/frame/test_stack_unstack.py

@@ -5,6 +5,8 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
+
 import pandas as pd
 from pandas import (
     DataFrame,
@@ -60,12 +62,13 @@ def test_stack_mixed_level(self):
         expected = expected[["a", "b"]]
         tm.assert_frame_equal(result, expected)
 
-    def test_unstack_not_consolidated(self):
+    def test_unstack_not_consolidated(self, using_array_manager):
         # Gh#34708
         df = DataFrame({"x": [1, 2, np.NaN], "y": [3.0, 4, np.NaN]})
         df2 = df[["x"]]
         df2["y"] = df["y"]
-        assert len(df2._mgr.blocks) == 2
+        if not using_array_manager:
+            assert len(df2._mgr.blocks) == 2
 
         res = df2.unstack()
         expected = df.unstack()
@@ -747,7 +750,8 @@ def test_unstack_multi_level_rows_and_cols(self):
         expected = df.unstack(["i3"]).unstack(["i2"])
         tm.assert_frame_equal(result, expected)
 
-    def test_unstack_nan_index(self):  # GH7466
+    def test_unstack_nan_index1(self):
+        # GH7466
         def cast(val):
             val_str = "" if val != val else val
             return f"{val_str:1}"
@@ -833,6 +837,7 @@ def verify(df):
                 for col in ["4th", "5th"]:
                     verify(udf[col])
 
+    def test_unstack_nan_index2(self):
         # GH7403
         df = DataFrame({"A": list("aaaabbbb"), "B": range(8), "C": range(8)})
         df.iloc[3, 1] = np.NaN
@@ -875,6 +880,7 @@ def verify(df):
         right = DataFrame(vals, columns=cols, index=idx)
         tm.assert_frame_equal(left, right)
 
+    def test_unstack_nan_index3(self, using_array_manager):
         # GH7401
         df = DataFrame(
             {
@@ -896,8 +902,13 @@ def verify(df):
         )
 
         right = DataFrame(vals, columns=cols, index=idx)
+        if using_array_manager:
+            # INFO(ArrayManager) with ArrayManager preserve dtype where possible
+            cols = right.columns[[1, 2, 3, 5]]
+            right[cols] = right[cols].astype("int64")
         tm.assert_frame_equal(left, right)
 
+    def test_unstack_nan_index4(self):
         # GH4862
         vals = [
             ["Hg", np.nan, np.nan, 680585148],
@@ -938,6 +949,8 @@ def verify(df):
         left = df.loc[17264:].copy().set_index(["s_id", "dosage", "agent"])
         tm.assert_frame_equal(left.unstack(), right)
 
+    @td.skip_array_manager_not_yet_implemented  # TODO(ArrayManager) MultiIndex bug
+    def test_unstack_nan_index5(self):
         # GH9497 - multiple unstack with nulls
         df = DataFrame(
             {
@@ -1453,6 +1466,7 @@ def test_stack_mixed_dtype(self, multiindex_dataframe_random_data):
         assert result.name is None
         assert stacked["bar"].dtype == np.float_
 
+    @td.skip_array_manager_not_yet_implemented  # TODO(ArrayManager) groupby
     def test_unstack_bug(self):
         df = DataFrame(
             {
@@ -1887,7 +1901,7 @@ def test_unstack_group_index_overflow(self):
         result = s.unstack(4)
         assert result.shape == (500, 2)
 
-    def test_unstack_with_missing_int_cast_to_float(self):
+    def test_unstack_with_missing_int_cast_to_float(self, using_array_manager):
         # https://github.com/pandas-dev/pandas/issues/37115
         df = DataFrame(
             {
@@ -1899,7 +1913,8 @@ def test_unstack_with_missing_int_cast_to_float(self):
 
         # add another int column to get 2 blocks
         df["is_"] = 1
-        assert len(df._mgr.blocks) == 2
+        if not using_array_manager:
+            assert len(df._mgr.blocks) == 2
 
         result = df.unstack("b")
         result[("is_", "ca")] = result[("is_", "ca")].fillna(0)
@@ -1912,6 +1927,10 @@ def test_unstack_with_missing_int_cast_to_float(self):
                 names=[None, "b"],
             ),
         )
+        if using_array_manager:
+            # INFO(ArrayManager) with ArrayManager preserve dtype where possible
+            expected[("v", "cb")] = expected[("v", "cb")].astype("int64")
+            expected[("is_", "cb")] = expected[("is_", "cb")].astype("int64")
         tm.assert_frame_equal(result, expected)
 
     def test_unstack_with_level_has_nan(self):