Fix DataFrame.drop(columns=cudf.Series/Index, axis=1) (rapidsai#16712)

Before when `columns=` was a `cudf.Series/Index` we would call `return array.unique.to_pandas()`, but `.unique` is a method not a property so this would have raised an error.

Also took the time to refactor the helper methods here and push down the `errors=` keyword to `Frame._drop_column`

Authors:
  - Matthew Roeschke (https://github.com/mroeschke)

Approvers:
  - Bradley Dice (https://github.com/bdice)

URL: rapidsai#16712

python/cudf/cudf/core/frame.py

@@ -767,11 +767,15 @@ def fillna(
         )
 
     @_performance_tracking
-    def _drop_column(self, name):
-        """Drop a column by *name*"""
-        if name not in self._data:
-            raise KeyError(f"column '{name}' does not exist")
-        del self._data[name]
+    def _drop_column(
+        self, name: abc.Hashable, errors: Literal["ignore", "raise"] = "raise"
+    ) -> None:
+        """Drop a column by *name* inplace."""
+        try:
+            del self._data[name]
+        except KeyError as err:
+            if errors != "ignore":
+                raise KeyError(f"column '{name}' does not exist") from err
 
     @_performance_tracking
     def _quantile_table(

python/cudf/cudf/core/indexed_frame.py

@@ -3,7 +3,6 @@
 
 from __future__ import annotations
 
-import numbers
 import operator
 import textwrap
 import warnings
@@ -150,24 +149,14 @@
 )
 
 
-def _get_host_unique(array):
+def _get_unique_drop_labels(array):
+    """Return labels to be dropped for IndexFrame.drop."""
     if isinstance(array, (cudf.Series, cudf.Index, ColumnBase)):
-        return array.unique.to_pandas()
-    elif isinstance(array, (str, numbers.Number)):
-        return [array]
+        yield from np.unique(as_column(array).values_host)
+    elif is_scalar(array):
+        yield array
     else:
-        return set(array)
-
-
-def _drop_columns(f: Frame, columns: abc.Iterable, errors: str):
-    for c in columns:
-        try:
-            f._drop_column(c)
-        except KeyError as e:
-            if errors == "ignore":
-                pass
-            else:
-                raise e
+        yield from set(array)
 
 
 def _indices_from_labels(obj, labels):
@@ -5262,15 +5251,14 @@ def drop(
             out = self.copy()
 
         if axis in (1, "columns"):
-            target = _get_host_unique(target)
-
-            _drop_columns(out, target, errors)
+            for label in _get_unique_drop_labels(target):
+                out._drop_column(label, errors=errors)
         elif axis in (0, "index"):
             dropped = _drop_rows_by_labels(out, target, level, errors)
 
             if columns is not None:
-                columns = _get_host_unique(columns)
-                _drop_columns(dropped, columns, errors)
+                for label in _get_unique_drop_labels(columns):
+                    dropped._drop_column(label, errors=errors)
 
             out._mimic_inplace(dropped, inplace=True)
 

python/cudf/cudf/tests/test_dataframe.py

@@ -515,6 +515,17 @@ def test_dataframe_drop_columns(pdf, columns, inplace):
     assert_eq(expected, actual)
 
 
+@pytest.mark.parametrize("obj", ["Index", "Series"])
+def test_drop_cudf_obj_columns(obj):
+    pdf = pd.DataFrame({"A": [1], "B": [1]})
+    gdf = cudf.from_pandas(pdf)
+
+    columns = ["B"]
+    expected = pdf.drop(labels=getattr(pd, obj)(columns), axis=1)
+    actual = gdf.drop(columns=getattr(cudf, obj)(columns), axis=1)
+    assert_eq(expected, actual)
+
+
 @pytest.mark.parametrize(
     "pdf",
     [