DEPR: store SparseArray directly in Index

doc/source/whatsnew/v2.0.0.rst

@@ -229,6 +229,7 @@ Removal of prior version deprecations/changes
 - Removed the ``display.column_space`` option in favor of ``df.to_string(col_space=...)`` (:issue:`47280`)
 - Removed the deprecated method ``mad`` from pandas classes (:issue:`11787`)
 - Removed the deprecated method ``tshift`` from pandas classes (:issue:`11631`)
+- Changed behavior of :class:`Index` constructor when passed a ``SparseArray`` or ``SparseDtype`` to retain that dtype instead of casting to ``numpy.ndarray`` (:issue:`43930`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_200.performance:

pandas/core/indexes/base.py

@@ -156,7 +156,6 @@
     tz_to_dtype,
     validate_tz_from_dtype,
 )
-from pandas.core.arrays.sparse import SparseDtype
 from pandas.core.arrays.string_ import StringArray
 from pandas.core.base import (
     IndexOpsMixin,
@@ -618,17 +617,6 @@ def _dtype_to_subclass(cls, dtype: DtypeObj):
 
                 return PeriodIndex
 
-            elif isinstance(dtype, SparseDtype):
-                warnings.warn(
-                    "In a future version, passing a SparseArray to pd.Index "
-                    "will store that array directly instead of converting to a "
-                    "dense numpy ndarray. To retain the old behavior, use "
-                    "pd.Index(arr.to_numpy()) instead",
-                    FutureWarning,
-                    stacklevel=find_stack_level(),
-                )
-                return cls._dtype_to_subclass(dtype.subtype)
-
             return Index
 
         if dtype.kind == "M":

pandas/tests/base/test_conversion.py

@@ -334,10 +334,7 @@ def test_array_multiindex_raises():
 def test_to_numpy(arr, expected, index_or_series_or_array, request):
     box = index_or_series_or_array
 
-    warn = None
-    if index_or_series_or_array is pd.Index and isinstance(arr, SparseArray):
-        warn = FutureWarning
-    with tm.assert_produces_warning(warn):
+    with tm.assert_produces_warning(None):
         thing = box(arr)
 
     if arr.dtype.name == "int64" and box is pd.array:

pandas/tests/extension/test_sparse.py

@@ -211,17 +211,6 @@ def test_reindex(self, data, na_value):
 
 
 class TestIndex(base.BaseIndexTests):
-    def test_index_from_array(self, data):
-        msg = "will store that array directly"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            idx = pd.Index(data)
-
-        if data.dtype.subtype == "f":
-            assert idx.dtype == np.float64
-        elif data.dtype.subtype == "i":
-            assert idx.dtype == np.int64
-        else:
-            assert idx.dtype == data.dtype.subtype
 
     # TODO(2.0): should pass once SparseArray is stored directly in Index.
     @pytest.mark.xfail(reason="Index cannot yet store sparse dtype")

pandas/tests/indexes/datetimes/test_constructors.py

@@ -142,11 +142,9 @@ def test_constructor_from_sparse_array(self):
             Timestamp("2016-05-01T01:00:00.000000"),
         ]
         arr = pd.arrays.SparseArray(values)
-        msg = "will store that array directly"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = Index(arr)
-        expected = DatetimeIndex(values)
-        tm.assert_index_equal(result, expected)
+        result = Index(arr)
+        assert type(result) is Index
+        assert result.dtype == arr.dtype
 
     def test_construction_caching(self):
 

pandas/tests/series/test_ufunc.py

@@ -5,8 +5,6 @@
 import numpy as np
 import pytest
 
-from pandas.core.dtypes.common import is_dtype_equal
-
 import pandas as pd
 import pandas._testing as tm
 from pandas.arrays import SparseArray
@@ -277,14 +275,10 @@ def test_multiply(self, values_for_np_reduce, box_with_array, request):
         box = box_with_array
         values = values_for_np_reduce
 
-        warn = None
-        if is_dtype_equal(values.dtype, "Sparse[int]") and box is pd.Index:
-            warn = FutureWarning
-        msg = "passing a SparseArray to pd.Index"
-        with tm.assert_produces_warning(warn, match=msg):
+        with tm.assert_produces_warning(None):
             obj = box(values)
 
-        if isinstance(values, pd.core.arrays.SparseArray) and box is not pd.Index:
+        if isinstance(values, pd.core.arrays.SparseArray):
             mark = pytest.mark.xfail(reason="SparseArray has no 'prod'")
             request.node.add_marker(mark)
 
@@ -316,11 +310,7 @@ def test_add(self, values_for_np_reduce, box_with_array):
         box = box_with_array
         values = values_for_np_reduce
 
-        warn = None
-        if is_dtype_equal(values.dtype, "Sparse[int]") and box is pd.Index:
-            warn = FutureWarning
-        msg = "passing a SparseArray to pd.Index"
-        with tm.assert_produces_warning(warn, match=msg):
+        with tm.assert_produces_warning(None):
             obj = box(values)
 
         if values.dtype.kind in "miuf":
@@ -355,11 +345,7 @@ def test_max(self, values_for_np_reduce, box_with_array):
             # ATM Index casts to object, so we get python ints/floats
             same_type = False
 
-        warn = None
-        if is_dtype_equal(values.dtype, "Sparse[int]") and box is pd.Index:
-            warn = FutureWarning
-        msg = "passing a SparseArray to pd.Index"
-        with tm.assert_produces_warning(warn, match=msg):
+        with tm.assert_produces_warning(None):
             obj = box(values)
 
         result = np.maximum.reduce(obj)
@@ -383,11 +369,7 @@ def test_min(self, values_for_np_reduce, box_with_array):
             # ATM Index casts to object, so we get python ints/floats
             same_type = False
 
-        warn = None
-        if is_dtype_equal(values.dtype, "Sparse[int]") and box is pd.Index:
-            warn = FutureWarning
-        msg = "passing a SparseArray to pd.Index"
-        with tm.assert_produces_warning(warn, match=msg):
+        with tm.assert_produces_warning(None):
             obj = box(values)
 
         result = np.minimum.reduce(obj)