DEPR: don't make Index instantiate Int64/Uint64/Flaot64Index

Author: Terji Petersen

pandas/conftest.py

@@ -593,10 +593,7 @@ def _create_mi_with_dt64tz_level():
     "datetime-tz": tm.makeDateIndex(100, tz="US/Pacific"),
     "period": tm.makePeriodIndex(100),
     "timedelta": tm.makeTimedeltaIndex(100),
-    "int": tm.makeIntIndex(100),
-    "uint": tm.makeUIntIndex(100),
     "range": tm.makeRangeIndex(100),
-    "float": tm.makeFloatIndex(100),
     "complex64": tm.makeFloatIndex(100).astype("complex64"),
     "complex128": tm.makeFloatIndex(100).astype("complex128"),
     "num_int64": tm.makeNumericIndex(100, dtype="int64"),

pandas/tests/arrays/interval/test_interval.py

@@ -287,7 +287,7 @@ def test_arrow_array():
     with pytest.raises(TypeError, match="Not supported to convert IntervalArray"):
         pa.array(intervals, type="float64")
 
-    with pytest.raises(TypeError, match="different 'subtype'"):
+    with pytest.raises(TypeError, match="Not supported to convert IntervalArray"):
         pa.array(intervals, type=ArrowIntervalType(pa.float64(), "left"))
 
 

pandas/tests/arrays/sparse/test_accessor.py

@@ -41,7 +41,12 @@ def test_from_coo(self):
         sp_array = scipy.sparse.coo_matrix((data, (row, col)), dtype="int")
         result = pd.Series.sparse.from_coo(sp_array)
 
-        index = pd.MultiIndex.from_arrays([[0, 0, 1, 3], [0, 2, 1, 3]])
+        index = pd.MultiIndex.from_arrays(
+            [
+                np.array([0, 0, 1, 3], dtype=np.int32),
+                np.array([0, 2, 1, 3], dtype=np.int32),
+            ],
+        )
         expected = pd.Series([4, 9, 7, 5], index=index, dtype="Sparse[int]")
         tm.assert_series_equal(result, expected)
 
@@ -212,7 +217,15 @@ def test_series_from_coo(self, dtype, dense_index):
 
         A = scipy.sparse.eye(3, format="coo", dtype=dtype)
         result = pd.Series.sparse.from_coo(A, dense_index=dense_index)
-        index = pd.MultiIndex.from_tuples([(0, 0), (1, 1), (2, 2)])
+
+        index_dtype = np.int64 if dense_index else np.int32
+        index = pd.MultiIndex.from_tuples(
+            [
+                np.array([0, 0], dtype=index_dtype),
+                np.array([1, 1], dtype=index_dtype),
+                np.array([2, 2], dtype=index_dtype),
+            ],
+        )
         expected = pd.Series(SparseArray(np.array([1, 1, 1], dtype=dtype)), index=index)
         if dense_index:
             expected = expected.reindex(pd.MultiIndex.from_product(index.levels))