Introduce nan_as_null parameter for cudf.Index (#9893)

Fixes: #9822 

This PR introduces `nan_as_null` parameter to `cudf.Index` constructor which is similar to the one present in `cudf.Series` constructor.

Authors:
  - GALI PREM SAGAR (https://github.com/galipremsagar)

Approvers:
  - Ashwin Srinath (https://github.com/shwina)

URL: #9893

python/cudf/cudf/core/_base_index.py

@@ -829,7 +829,7 @@ def is_floating(self):
         >>> idx = cudf.Index([1.0, 2.0, np.nan, 4.0])
         >>> idx.is_floating()
         True
-        >>> idx = cudf.Index([1, 2, 3, 4, np.nan])
+        >>> idx = cudf.Index([1, 2, 3, 4, np.nan], nan_as_null=False)
         >>> idx.is_floating()
         True
         >>> idx = cudf.Index([1, 2, 3, 4])

python/cudf/cudf/core/column/categorical.py

@@ -809,7 +809,9 @@ def __setitem__(self, key, value):
             to_add_categories = 0
         else:
             to_add_categories = len(
-                cudf.Index(value).difference(self.categories)
+                cudf.Index(value, nan_as_null=False).difference(
+                    self.categories
+                )
             )
 
         if to_add_categories > 0:

python/cudf/cudf/core/index.py

@@ -2527,7 +2527,7 @@ def is_object(self):
         return True
 
 
-def as_index(arbitrary, **kwargs) -> BaseIndex:
+def as_index(arbitrary, nan_as_null=None, **kwargs) -> BaseIndex:
     """Create an Index from an arbitrary object
 
     Currently supported inputs are:
@@ -2560,7 +2560,7 @@ def as_index(arbitrary, **kwargs) -> BaseIndex:
     elif isinstance(arbitrary, ColumnBase):
         return _index_from_data({kwargs.get("name", None): arbitrary})
     elif isinstance(arbitrary, cudf.Series):
-        return as_index(arbitrary._column, **kwargs)
+        return as_index(arbitrary._column, nan_as_null=nan_as_null, **kwargs)
     elif isinstance(arbitrary, (pd.RangeIndex, range)):
         return RangeIndex(
             start=arbitrary.start,
@@ -2569,11 +2569,14 @@ def as_index(arbitrary, **kwargs) -> BaseIndex:
             **kwargs,
         )
     elif isinstance(arbitrary, pd.MultiIndex):
-        return cudf.MultiIndex.from_pandas(arbitrary)
+        return cudf.MultiIndex.from_pandas(arbitrary, nan_as_null=nan_as_null)
     elif isinstance(arbitrary, cudf.DataFrame):
         return cudf.MultiIndex.from_frame(arbitrary)
     return as_index(
-        column.as_column(arbitrary, dtype=kwargs.get("dtype", None)), **kwargs
+        column.as_column(
+            arbitrary, dtype=kwargs.get("dtype", None), nan_as_null=nan_as_null
+        ),
+        **kwargs,
     )
 
 
@@ -2623,6 +2626,10 @@ class Index(BaseIndex, metaclass=IndexMeta):
     tupleize_cols : bool (default: True)
         When True, attempt to create a MultiIndex if possible.
         tupleize_cols == False is not yet supported.
+    nan_as_null : bool, Default True
+        If ``None``/``True``, converts ``np.nan`` values to
+        ``null`` values.
+        If ``False``, leaves ``np.nan`` values as is.
 
     Returns
     -------
@@ -2655,6 +2662,7 @@ def __new__(
         copy=False,
         name=None,
         tupleize_cols=True,
+        nan_as_null=True,
         **kwargs,
     ):
         assert (
@@ -2665,7 +2673,14 @@ def __new__(
                 "tupleize_cols != True is not yet supported"
             )
 
-        return as_index(data, copy=copy, dtype=dtype, name=name, **kwargs)
+        return as_index(
+            data,
+            copy=copy,
+            dtype=dtype,
+            name=name,
+            nan_as_null=nan_as_null,
+            **kwargs,
+        )
 
     @classmethod
     def from_arrow(cls, obj):

python/cudf/cudf/tests/test_index.py

@@ -2509,3 +2509,22 @@ def test_index_datetime_round(resolution):
     cuidx_floor = cuidx.round(resolution)
 
     assert_eq(pidx_floor, cuidx_floor)
+
+
+@pytest.mark.parametrize(
+    "data,nan_idx,NA_idx",
+    [([1, 2, 3, None], None, 3), ([2, 3, np.nan, None], 2, 3)],
+)
+@pytest.mark.parametrize("nan_as_null", [True, False])
+def test_index_nan_as_null(data, nan_idx, NA_idx, nan_as_null):
+    idx = cudf.Index(data, nan_as_null=nan_as_null)
+
+    if nan_as_null:
+        if nan_idx is not None:
+            assert idx[nan_idx] is cudf.NA
+    else:
+        if nan_idx is not None:
+            assert np.isnan(idx[nan_idx])
+
+    if NA_idx is not None:
+        assert idx[NA_idx] is cudf.NA