fix more errors

pandas/tests/arithmetic/test_numeric.py

@@ -14,18 +14,20 @@
 
 import pandas as pd
 from pandas import (
-    Float64Index,
     Index,
-    Int64Index,
     RangeIndex,
     Series,
     Timedelta,
     TimedeltaIndex,
-    UInt64Index,
     array,
 )
 import pandas._testing as tm
 from pandas.core import ops
+from pandas.core.api import (
+    Float64Index,
+    Int64Index,
+    UInt64Index,
+)
 from pandas.core.computation import expressions as expr
 
 

pandas/tests/arithmetic/test_timedelta64.py

@@ -26,6 +26,11 @@
     timedelta_range,
 )
 import pandas._testing as tm
+from pandas.core.api import (
+    Float64Index,
+    Int64Index,
+    UInt64Index,
+)
 from pandas.tests.arithmetic.common import (
     assert_invalid_addsub_type,
     assert_invalid_comparison,
@@ -489,10 +494,10 @@ def test_addition_ops(self):
         # random indexes
         msg = "Addition/subtraction of integers and integer-arrays"
         with pytest.raises(TypeError, match=msg):
-            tdi + pd.Int64Index([1, 2, 3])
+            tdi + Int64Index([1, 2, 3])
 
         # this is a union!
-        # pytest.raises(TypeError, lambda : pd.Int64Index([1,2,3]) + tdi)
+        # pytest.raises(TypeError, lambda : Int64Index([1,2,3]) + tdi)
 
         result = tdi + dti  # name will be reset
         expected = DatetimeIndex(["20130102", NaT, "20130105"])
@@ -1570,9 +1575,9 @@ def test_tdi_mul_float_series(self, box_with_array):
         "other",
         [
             np.arange(1, 11),
-            pd.Int64Index(range(1, 11)),
-            pd.UInt64Index(range(1, 11)),
-            pd.Float64Index(range(1, 11)),
+            Int64Index(range(1, 11)),
+            UInt64Index(range(1, 11)),
+            Float64Index(range(1, 11)),
             pd.RangeIndex(1, 11),
         ],
         ids=lambda x: type(x).__name__,
@@ -1642,7 +1647,7 @@ 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 = pd.Float64Index((np.arange(10) + 1) * 12, name="foo")
+        expected = Float64Index((np.arange(10) + 1) * 12, name="foo")
 
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, xbox)
@@ -1685,7 +1690,7 @@ 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 = pd.Float64Index([12, np.nan, 24], name="foo")
+        expected = Float64Index([12, np.nan, 24], name="foo")
 
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, xbox)
@@ -1703,7 +1708,7 @@ 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 = pd.Float64Index([12, np.nan, 24])
+        expected = Float64Index([12, np.nan, 24])
 
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, xbox)
@@ -1846,7 +1851,7 @@ def test_td64arr_floordiv_tdlike_scalar(self, two_hours, box_with_array):
         xbox = np.ndarray if box is pd.array else box
 
         tdi = timedelta_range("1 days", "10 days", name="foo")
-        expected = pd.Int64Index((np.arange(10) + 1) * 12, name="foo")
+        expected = Int64Index((np.arange(10) + 1) * 12, name="foo")
 
         tdi = tm.box_expected(tdi, box)
         expected = tm.box_expected(expected, xbox)

pandas/tests/arrays/categorical/test_constructors.py

@@ -34,6 +34,7 @@
     timedelta_range,
 )
 import pandas._testing as tm
+from pandas.core.api import Int64Index
 
 
 class TestCategoricalConstructors:
@@ -71,7 +72,7 @@ def test_constructor_empty(self):
         tm.assert_index_equal(c.categories, expected)
 
         c = Categorical([], categories=[1, 2, 3])
-        expected = pd.Int64Index([1, 2, 3])
+        expected = Int64Index([1, 2, 3])
         tm.assert_index_equal(c.categories, expected)
 
     def test_constructor_empty_boolean(self):

pandas/tests/arrays/sparse/test_array.py

@@ -11,6 +11,7 @@
 import pandas as pd
 from pandas import isna
 import pandas._testing as tm
+from pandas.core.api import Int64Index
 from pandas.core.arrays.sparse import (
     SparseArray,
     SparseDtype,
@@ -1309,7 +1310,7 @@ def test_dropna(fill_value):
     tm.assert_sp_array_equal(arr.dropna(), exp)
 
     df = pd.DataFrame({"a": [0, 1], "b": arr})
-    expected_df = pd.DataFrame({"a": [1], "b": exp}, index=pd.Int64Index([1]))
+    expected_df = pd.DataFrame({"a": [1], "b": exp}, index=Int64Index([1]))
     tm.assert_equal(df.dropna(), expected_df)
 
 

pandas/tests/dtypes/test_generic.py

@@ -7,6 +7,11 @@
 
 import pandas as pd
 import pandas._testing as tm
+from pandas.core.api import (
+    Float64Index,
+    Int64Index,
+    UInt64Index,
+)
 
 
 class TestABCClasses:
@@ -23,9 +28,9 @@ class TestABCClasses:
     timedelta_array = pd.core.arrays.TimedeltaArray(timedelta_index)
 
     abc_pairs = [
-        ("ABCInt64Index", pd.Int64Index([1, 2, 3])),
-        ("ABCUInt64Index", pd.UInt64Index([1, 2, 3])),
-        ("ABCFloat64Index", pd.Float64Index([1, 2, 3])),
+        ("ABCInt64Index", Int64Index([1, 2, 3])),
+        ("ABCUInt64Index", UInt64Index([1, 2, 3])),
+        ("ABCFloat64Index", Float64Index([1, 2, 3])),
         ("ABCMultiIndex", multi_index),
         ("ABCDatetimeIndex", datetime_index),
         ("ABCRangeIndex", pd.RangeIndex(3)),

pandas/tests/dtypes/test_missing.py

@@ -35,13 +35,13 @@
 import pandas as pd
 from pandas import (
     DatetimeIndex,
-    Float64Index,
     NaT,
     Series,
     TimedeltaIndex,
     date_range,
 )
 import pandas._testing as tm
+from pandas.core.api import Float64Index
 
 now = pd.Timestamp.now()
 utcnow = pd.Timestamp.now("UTC")

pandas/tests/series/indexing/test_get.py

@@ -4,6 +4,7 @@
 import pandas as pd
 from pandas import Series
 import pandas._testing as tm
+from pandas.core.api import Float64Index
 
 
 def test_get():
@@ -64,7 +65,7 @@ def test_get():
                 54,
             ]
         ),
-        index=pd.Float64Index(
+        index=Float64Index(
             [
                 25.0,
                 36.0,
@@ -111,7 +112,7 @@ def test_get():
 
 def test_get_nan():
     # GH 8569
-    s = pd.Float64Index(range(10)).to_series()
+    s = Float64Index(range(10)).to_series()
     assert s.get(np.nan) is None
     assert s.get(np.nan, default="Missing") == "Missing"
 
@@ -120,7 +121,7 @@ def test_get_nan_multiple():
     # GH 8569
     # ensure that fixing "test_get_nan" above hasn't broken get
     # with multiple elements
-    s = pd.Float64Index(range(10)).to_series()
+    s = Float64Index(range(10)).to_series()
 
     idx = [2, 30]
     assert s.get(idx) is None

pandas/tseries/frequencies.py

@@ -153,7 +153,12 @@ def infer_freq(index, warn: bool = True) -> str | None:
     >>> pd.infer_freq(idx)
     'D'
     """
-    import pandas as pd
+    from pandas.core.api import (
+        DatetimeIndex,
+        Float64Index,
+        Index,
+        Int64Index,
+    )
 
     if isinstance(index, ABCSeries):
         values = index._values
@@ -182,15 +187,15 @@ def infer_freq(index, warn: bool = True) -> str | None:
         inferer = _TimedeltaFrequencyInferer(index, warn=warn)
         return inferer.get_freq()
 
-    if isinstance(index, pd.Index) and not isinstance(index, pd.DatetimeIndex):
-        if isinstance(index, (pd.Int64Index, pd.Float64Index)):
+    if isinstance(index, Index) and not isinstance(index, DatetimeIndex):
+        if isinstance(index, (Int64Index, Float64Index)):
             raise TypeError(
                 f"cannot infer freq from a non-convertible index type {type(index)}"
             )
         index = index._values
 
-    if not isinstance(index, pd.DatetimeIndex):
-        index = pd.DatetimeIndex(index)
+    if not isinstance(index, DatetimeIndex):
+        index = DatetimeIndex(index)
 
     inferer = _FrequencyInferer(index, warn=warn)
     return inferer.get_freq()