DEPR: remove some more Int/UInt/Float64Index from tests (#50075)

* DEPR: remove some more Int/UInt/Float64Index from tests

* fix failed tests

* fix failed code check

* fix tests

* fix tests 2

* fix tests 3

* fix tests

Co-authored-by: Terji Petersen <[email protected]>
Co-authored-by: Terji Petersen <[email protected]>

Author: 3 people

pandas/tests/arithmetic/test_timedelta64.py

@@ -26,11 +26,7 @@
     timedelta_range,
 )
 import pandas._testing as tm
-from pandas.core.api import (
-    Float64Index,
-    Int64Index,
-    UInt64Index,
-)
+from pandas.core.api import NumericIndex
 from pandas.tests.arithmetic.common import (
     assert_invalid_addsub_type,
     assert_invalid_comparison,
@@ -492,10 +488,10 @@ def test_addition_ops(self):
         # random indexes
         msg = "Addition/subtraction of integers and integer-arrays"
         with pytest.raises(TypeError, match=msg):
-            tdi + Int64Index([1, 2, 3])
+            tdi + NumericIndex([1, 2, 3], dtype=np.int64)
 
         # this is a union!
-        # pytest.raises(TypeError, lambda : Int64Index([1,2,3]) + tdi)
+        # pytest.raises(TypeError, lambda : Index([1,2,3]) + tdi)
 
         result = tdi + dti  # name will be reset
         expected = DatetimeIndex(["20130102", NaT, "20130105"])
@@ -1508,9 +1504,9 @@ def test_tdi_mul_float_series(self, box_with_array):
         "other",
         [
             np.arange(1, 11),
-            Int64Index(range(1, 11)),
-            UInt64Index(range(1, 11)),
-            Float64Index(range(1, 11)),
+            NumericIndex(np.arange(1, 11), np.int64),
+            NumericIndex(range(1, 11), np.uint64),
+            NumericIndex(range(1, 11), np.float64),
             pd.RangeIndex(1, 11),
         ],
         ids=lambda x: type(x).__name__,
@@ -1594,7 +1590,7 @@ def test_td64arr_div_tdlike_scalar(self, two_hours, box_with_array):
         xbox = np.ndarray if box is pd.array else box
 
         rng = timedelta_range("1 days", "10 days", name="foo")
-        expected = Float64Index((np.arange(10) + 1) * 12, name="foo")
+        expected = NumericIndex((np.arange(10) + 1) * 12, dtype=np.float64, name="foo")
 
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, xbox)
@@ -1634,7 +1630,7 @@ def test_td64arr_div_tdlike_scalar_with_nat(self, two_hours, box_with_array):
         xbox = np.ndarray if box is pd.array else box
 
         rng = TimedeltaIndex(["1 days", NaT, "2 days"], name="foo")
-        expected = Float64Index([12, np.nan, 24], name="foo")
+        expected = NumericIndex([12, np.nan, 24], dtype=np.float64, name="foo")
 
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, xbox)
@@ -1652,7 +1648,7 @@ def test_td64arr_div_td64_ndarray(self, box_with_array):
         xbox = np.ndarray if box is pd.array else box
 
         rng = TimedeltaIndex(["1 days", NaT, "2 days"])
-        expected = Float64Index([12, np.nan, 24])
+        expected = NumericIndex([12, np.nan, 24], dtype=np.float64)
 
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, xbox)

pandas/tests/dtypes/test_inference.py

@@ -1829,7 +1829,6 @@ def test_is_timedelta(self):
         assert is_timedelta64_ns_dtype(tdi)
         assert is_timedelta64_ns_dtype(tdi.astype("timedelta64[ns]"))
 
-        # Conversion to Int64Index:
         assert not is_timedelta64_ns_dtype(Index([], dtype=np.float64))
         assert not is_timedelta64_ns_dtype(Index([], dtype=np.int64))
 

pandas/tests/dtypes/test_missing.py

@@ -33,13 +33,14 @@
 import pandas as pd
 from pandas import (
     DatetimeIndex,
+    Index,
     NaT,
     Series,
     TimedeltaIndex,
     date_range,
 )
 import pandas._testing as tm
-from pandas.core.api import Float64Index
+from pandas.core.api import NumericIndex
 
 fix_now = pd.Timestamp("2021-01-01")
 fix_utcnow = pd.Timestamp("2021-01-01", tz="UTC")
@@ -355,7 +356,7 @@ def test_decimal(self):
         tm.assert_series_equal(result, ~expected)
 
         # index
-        idx = pd.Index(arr)
+        idx = Index(arr)
         expected = np.array([False, True])
         result = isna(idx)
         tm.assert_numpy_array_equal(result, expected)
@@ -404,10 +405,10 @@ def test_array_equivalent(dtype_equal):
         np.array(["a", "b", "c", "d"]), np.array(["e", "e"]), dtype_equal=dtype_equal
     )
     assert array_equivalent(
-        Float64Index([0, np.nan]), Float64Index([0, np.nan]), dtype_equal=dtype_equal
+        NumericIndex([0, np.nan]), NumericIndex([0, np.nan]), dtype_equal=dtype_equal
     )
     assert not array_equivalent(
-        Float64Index([0, np.nan]), Float64Index([1, np.nan]), dtype_equal=dtype_equal
+        NumericIndex([0, np.nan]), NumericIndex([1, np.nan]), dtype_equal=dtype_equal
     )
     assert array_equivalent(
         DatetimeIndex([0, np.nan]), DatetimeIndex([0, np.nan]), dtype_equal=dtype_equal
@@ -559,15 +560,15 @@ def test_array_equivalent_nested():
 
 def test_array_equivalent_index_with_tuples():
     # GH#48446
-    idx1 = pd.Index(np.array([(pd.NA, 4), (1, 1)], dtype="object"))
-    idx2 = pd.Index(np.array([(1, 1), (pd.NA, 4)], dtype="object"))
+    idx1 = Index(np.array([(pd.NA, 4), (1, 1)], dtype="object"))
+    idx2 = Index(np.array([(1, 1), (pd.NA, 4)], dtype="object"))
     assert not array_equivalent(idx1, idx2)
     assert not idx1.equals(idx2)
     assert not array_equivalent(idx2, idx1)
     assert not idx2.equals(idx1)
 
-    idx1 = pd.Index(np.array([(4, pd.NA), (1, 1)], dtype="object"))
-    idx2 = pd.Index(np.array([(1, 1), (4, pd.NA)], dtype="object"))
+    idx1 = Index(np.array([(4, pd.NA), (1, 1)], dtype="object"))
+    idx2 = Index(np.array([(1, 1), (4, pd.NA)], dtype="object"))
     assert not array_equivalent(idx1, idx2)
     assert not idx1.equals(idx2)
     assert not array_equivalent(idx2, idx1)

pandas/tests/frame/test_constructors.py

@@ -55,7 +55,6 @@
     SparseArray,
     TimedeltaArray,
 )
-from pandas.core.api import Int64Index
 
 MIXED_FLOAT_DTYPES = ["float16", "float32", "float64"]
 MIXED_INT_DTYPES = [
@@ -626,7 +625,7 @@ def test_constructor_2d_index(self):
         df = DataFrame([[1]], columns=[[1]], index=[1, 2])
         expected = DataFrame(
             [1, 1],
-            index=Int64Index([1, 2], dtype="int64"),
+            index=Index([1, 2], dtype="int64"),
             columns=MultiIndex(levels=[[1]], codes=[[0]]),
         )
         tm.assert_frame_equal(df, expected)

pandas/tests/groupby/test_apply.py

@@ -16,7 +16,6 @@
     bdate_range,
 )
 import pandas._testing as tm
-from pandas.core.api import Int64Index
 from pandas.tests.groupby import get_groupby_method_args
 
 
@@ -799,11 +798,9 @@ def test_apply_with_mixed_types():
 
 def test_func_returns_object():
     # GH 28652
-    df = DataFrame({"a": [1, 2]}, index=Int64Index([1, 2]))
+    df = DataFrame({"a": [1, 2]}, index=Index([1, 2]))
     result = df.groupby("a").apply(lambda g: g.index)
-    expected = Series(
-        [Int64Index([1]), Int64Index([2])], index=Int64Index([1, 2], name="a")
-    )
+    expected = Series([Index([1]), Index([2])], index=Index([1, 2], name="a"))
 
     tm.assert_series_equal(result, expected)
 

pandas/tests/groupby/test_grouping.py

@@ -14,10 +14,6 @@
     date_range,
 )
 import pandas._testing as tm
-from pandas.core.api import (
-    Float64Index,
-    Int64Index,
-)
 from pandas.core.groupby.grouper import Grouping
 
 # selection
@@ -691,11 +687,15 @@ def test_list_grouper_with_nat(self):
             ),
             (
                 "agg",
-                Series(name=2, dtype=np.float64, index=Float64Index([], name=1)),
+                Series(
+                    name=2, dtype=np.float64, index=Index([], dtype=np.float64, name=1)
+                ),
             ),
             (
                 "apply",
-                Series(name=2, dtype=np.float64, index=Float64Index([], name=1)),
+                Series(
+                    name=2, dtype=np.float64, index=Index([], dtype=np.float64, name=1)
+                ),
             ),
         ],
     )
@@ -759,7 +759,9 @@ def test_groupby_multiindex_level_empty(self):
         empty = df[df.value < 0]
         result = empty.groupby("id").sum()
         expected = DataFrame(
-            dtype="float64", columns=["value"], index=Int64Index([], name="id")
+            dtype="float64",
+            columns=["value"],
+            index=Index([], dtype=np.int64, name="id"),
         )
         tm.assert_frame_equal(result, expected)
 

pandas/tests/groupby/test_min_max.py

@@ -10,7 +10,6 @@
     Series,
 )
 import pandas._testing as tm
-from pandas.core.api import Int64Index
 
 
 def test_max_min_non_numeric():
@@ -123,7 +122,7 @@ def test_groupby_aggregate_period_column(func):
     df = DataFrame({"a": groups, "b": periods})
 
     result = getattr(df.groupby("a")["b"], func)()
-    idx = Int64Index([1, 2], name="a")
+    idx = Index([1, 2], name="a")
     expected = Series(periods, index=idx, name="b")
 
     tm.assert_series_equal(result, expected)
@@ -137,7 +136,7 @@ def test_groupby_aggregate_period_frame(func):
     df = DataFrame({"a": groups, "b": periods})
 
     result = getattr(df.groupby("a"), func)()
-    idx = Int64Index([1, 2], name="a")
+    idx = Index([1, 2], name="a")
     expected = DataFrame({"b": periods}, index=idx)
 
     tm.assert_frame_equal(result, expected)

pandas/tests/groupby/test_pipe.py

@@ -6,7 +6,7 @@
     Index,
 )
 import pandas._testing as tm
-from pandas.core.api import Int64Index
+from pandas.core.api import NumericIndex
 
 
 def test_pipe():
@@ -76,6 +76,6 @@ def h(df, arg3):
     ser = pd.Series([1, 1, 2, 2, 3, 3])
     result = ser.groupby(ser).pipe(lambda grp: grp.sum() * grp.count())
 
-    expected = pd.Series([4, 8, 12], index=Int64Index([1, 2, 3]))
+    expected = pd.Series([4, 8, 12], index=NumericIndex([1, 2, 3], dtype=np.int64))
 
     tm.assert_series_equal(result, expected)