fix errors

Author: topper-123

pandas/tests/arithmetic/conftest.py

@@ -2,13 +2,13 @@
 import pytest
 
 import pandas as pd
-from pandas import (
+from pandas import RangeIndex
+import pandas._testing as tm
+from pandas.core.api import (
     Float64Index,
     Int64Index,
-    RangeIndex,
     UInt64Index,
 )
-import pandas._testing as tm
 from pandas.core.computation import expressions as expr
 
 

pandas/tests/frame/methods/test_astype.py

@@ -17,12 +17,12 @@
     Series,
     Timedelta,
     Timestamp,
-    UInt64Index,
     concat,
     date_range,
     option_context,
 )
 import pandas._testing as tm
+from pandas.core.api import UInt64Index
 from pandas.core.arrays.integer import coerce_to_array
 
 

pandas/tests/indexes/datetimes/methods/test_astype.py

@@ -15,7 +15,10 @@
     date_range,
 )
 import pandas._testing as tm
-from pandas.core.api import Int64Index
+from pandas.core.api import (
+    Int64Index,
+    UInt64Index,
+)
 
 
 class TestDatetimeIndex:
@@ -46,7 +49,7 @@ def test_astype(self):
 
     def test_astype_uint(self):
         arr = date_range("2000", periods=2, name="idx")
-        expected = pd.UInt64Index(
+        expected = UInt64Index(
             np.array([946684800000000000, 946771200000000000], dtype="uint64"),
             name="idx",
         )

pandas/tests/indexes/datetimes/test_scalar_compat.py

@@ -19,6 +19,7 @@
     date_range,
 )
 import pandas._testing as tm
+from pandas.core.api import Float64Index
 
 
 class TestDatetimeIndexOps:
@@ -332,33 +333,33 @@ def test_1700(self):
         dr = date_range(start=Timestamp("1710-10-01"), periods=5, freq="D")
         r1 = pd.Index([x.to_julian_date() for x in dr])
         r2 = dr.to_julian_date()
-        assert isinstance(r2, pd.Float64Index)
+        assert isinstance(r2, Float64Index)
         tm.assert_index_equal(r1, r2)
 
     def test_2000(self):
         dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="D")
         r1 = pd.Index([x.to_julian_date() for x in dr])
         r2 = dr.to_julian_date()
-        assert isinstance(r2, pd.Float64Index)
+        assert isinstance(r2, Float64Index)
         tm.assert_index_equal(r1, r2)
 
     def test_hour(self):
         dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="H")
         r1 = pd.Index([x.to_julian_date() for x in dr])
         r2 = dr.to_julian_date()
-        assert isinstance(r2, pd.Float64Index)
+        assert isinstance(r2, Float64Index)
         tm.assert_index_equal(r1, r2)
 
     def test_minute(self):
         dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="T")
         r1 = pd.Index([x.to_julian_date() for x in dr])
         r2 = dr.to_julian_date()
-        assert isinstance(r2, pd.Float64Index)
+        assert isinstance(r2, Float64Index)
         tm.assert_index_equal(r1, r2)
 
     def test_second(self):
         dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="S")
         r1 = pd.Index([x.to_julian_date() for x in dr])
         r2 = dr.to_julian_date()
-        assert isinstance(r2, pd.Float64Index)
+        assert isinstance(r2, Float64Index)
         tm.assert_index_equal(r1, r2)

pandas/tests/indexes/interval/test_formats.py

@@ -3,14 +3,14 @@
 
 from pandas import (
     DataFrame,
-    Float64Index,
     Interval,
     IntervalIndex,
     Series,
     Timedelta,
     Timestamp,
 )
 import pandas._testing as tm
+from pandas.core.api import Float64Index
 
 
 class TestIntervalIndexRendering:

pandas/tests/indexes/interval/test_interval.py

@@ -20,6 +20,7 @@
     timedelta_range,
 )
 import pandas._testing as tm
+from pandas.core.api import Float64Index
 import pandas.core.common as com
 
 
@@ -406,7 +407,7 @@ def test_maybe_convert_i8_nat(self, breaks):
         index = IntervalIndex.from_breaks(breaks)
 
         to_convert = breaks._constructor([pd.NaT] * 3)
-        expected = pd.Float64Index([np.nan] * 3)
+        expected = Float64Index([np.nan] * 3)
         result = index._maybe_convert_i8(to_convert)
         tm.assert_index_equal(result, expected)
 

pandas/tests/indexes/multi/test_analytics.py

@@ -9,6 +9,7 @@
     period_range,
 )
 import pandas._testing as tm
+from pandas.core.api import UInt64Index
 
 
 def test_shift(idx):
@@ -174,7 +175,7 @@ def test_map(idx):
     index = idx
 
     # we don't infer UInt64
-    if isinstance(index, pd.UInt64Index):
+    if isinstance(index, UInt64Index):
         expected = index.astype("int64")
     else:
         expected = index
@@ -198,7 +199,7 @@ def test_map_dictlike(idx, mapper):
     identity = mapper(idx.values, idx)
 
     # we don't infer to UInt64 for a dict
-    if isinstance(idx, pd.UInt64Index) and isinstance(identity, dict):
+    if isinstance(idx, UInt64Index) and isinstance(identity, dict):
         expected = idx.astype("int64")
     else:
         expected = idx

pandas/tests/indexes/period/test_indexing.py

@@ -23,7 +23,10 @@
     period_range,
 )
 import pandas._testing as tm
-from pandas.core.api import Int64Index
+from pandas.core.api import (
+    Float64Index,
+    Int64Index,
+)
 
 dti4 = date_range("2016-01-01", periods=4)
 dti = dti4[:-1]
@@ -933,7 +936,7 @@ def test_asof_locs_mismatched_type(self):
             pi.asof_locs(Int64Index(pi.asi8), mask)
 
         with pytest.raises(TypeError, match=msg):
-            pi.asof_locs(pd.Float64Index(pi.asi8), mask)
+            pi.asof_locs(Float64Index(pi.asi8), mask)
 
         with pytest.raises(TypeError, match=msg):
             # TimedeltaIndex

pandas/tests/indexes/test_numpy_compat.py

@@ -3,13 +3,13 @@
 
 from pandas import (
     DatetimeIndex,
-    Float64Index,
     Index,
     NumericIndex,
     PeriodIndex,
     TimedeltaIndex,
 )
 import pandas._testing as tm
+from pandas.core.api import Float64Index
 from pandas.core.indexes.datetimelike import DatetimeIndexOpsMixin
 
 

pandas/tests/indexes/timedeltas/methods/test_astype.py

@@ -5,15 +5,18 @@
 
 import pandas as pd
 from pandas import (
-    Float64Index,
     Index,
-    Int64Index,
     NaT,
     Timedelta,
     TimedeltaIndex,
     timedelta_range,
 )
 import pandas._testing as tm
+from pandas.core.api import (
+    Float64Index,
+    Int64Index,
+    UInt64Index,
+)
 
 
 class TestTimedeltaIndex:
@@ -74,7 +77,7 @@ def test_astype(self):
 
     def test_astype_uint(self):
         arr = timedelta_range("1H", periods=2)
-        expected = pd.UInt64Index(
+        expected = UInt64Index(
             np.array([3600000000000, 90000000000000], dtype="uint64")
         )
         with tm.assert_produces_warning(FutureWarning):

pandas/tests/indexing/common.py

@@ -5,13 +5,15 @@
 
 from pandas import (
     DataFrame,
-    Float64Index,
     MultiIndex,
     Series,
-    UInt64Index,
     date_range,
 )
 import pandas._testing as tm
+from pandas.core.api import (
+    Float64Index,
+    UInt64Index,
+)
 
 
 def _mklbl(prefix, n):

pandas/tests/indexing/test_indexing.py

@@ -25,6 +25,7 @@
     timedelta_range,
 )
 import pandas._testing as tm
+from pandas.core.api import Float64Index
 from pandas.tests.indexing.common import _mklbl
 from pandas.tests.indexing.test_floats import gen_obj
 
@@ -143,7 +144,7 @@ def test_inf_upcast(self):
         assert df.loc[np.inf, 0] == 3
 
         result = df.index
-        expected = pd.Float64Index([1, 2, np.inf])
+        expected = Float64Index([1, 2, np.inf])
         tm.assert_index_equal(result, expected)
 
     def test_setitem_dtype_upcast(self):

pandas/tests/indexing/test_loc.py

@@ -36,6 +36,7 @@
 )
 import pandas._testing as tm
 from pandas.api.types import is_scalar
+from pandas.core.api import Float64Index
 from pandas.tests.indexing.common import Base
 
 
@@ -1838,7 +1839,7 @@ def test_loc_setitem_with_expansion_inf_upcast_empty(self):
         df.loc[0, np.inf] = 3
 
         result = df.columns
-        expected = pd.Float64Index([0, 1, np.inf])
+        expected = Float64Index([0, 1, np.inf])
         tm.assert_index_equal(result, expected)
 
     @pytest.mark.filterwarnings("ignore:indexing past lexsort depth")

pandas/tests/io/test_stata.py

@@ -1955,7 +1955,7 @@ def test_chunked_categorical_partial(dirpath):
                 if i < 2:
                     idx = pd.Index(["a", "b"])
                 else:
-                    idx = pd.Float64Index([3.0])
+                    idx = pd.Index([3.0], dtype="float64")
                 tm.assert_index_equal(block.cats.cat.categories, idx)
     with tm.assert_produces_warning(CategoricalConversionWarning):
         with StataReader(dta_file, chunksize=5) as reader: