STYLE: Inconsistent namespace - Indexes (#39992)

Author: alexprincel

pandas/tests/indexes/common.py

@@ -360,7 +360,7 @@ def test_numpy_repeat(self):
     @pytest.mark.parametrize("klass", [list, tuple, np.array, Series])
     def test_where(self, klass):
         i = self.create_index()
-        if isinstance(i, (pd.DatetimeIndex, pd.TimedeltaIndex)):
+        if isinstance(i, (DatetimeIndex, TimedeltaIndex)):
             # where does not preserve freq
             i = i._with_freq(None)
 
@@ -611,7 +611,7 @@ def test_map(self):
         index = self.create_index()
 
         # we don't infer UInt64
-        if isinstance(index, pd.UInt64Index):
+        if isinstance(index, UInt64Index):
             expected = index.astype("int64")
         else:
             expected = index
@@ -630,13 +630,13 @@ def test_map(self):
     def test_map_dictlike(self, mapper):
 
         index = self.create_index()
-        if isinstance(index, pd.CategoricalIndex):
+        if isinstance(index, CategoricalIndex):
             pytest.skip(f"skipping tests for {type(index)}")
 
         identity = mapper(index.values, index)
 
         # we don't infer to UInt64 for a dict
-        if isinstance(index, pd.UInt64Index) and isinstance(identity, dict):
+        if isinstance(index, UInt64Index) and isinstance(identity, dict):
             expected = index.astype("int64")
         else:
             expected = index

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

@@ -202,13 +202,13 @@ def test_astype_object_tz(self, tz):
 
     def test_astype_object_with_nat(self):
         idx = DatetimeIndex(
-            [datetime(2013, 1, 1), datetime(2013, 1, 2), pd.NaT, datetime(2013, 1, 4)],
+            [datetime(2013, 1, 1), datetime(2013, 1, 2), NaT, datetime(2013, 1, 4)],
             name="idx",
         )
         expected_list = [
             Timestamp("2013-01-01"),
             Timestamp("2013-01-02"),
-            pd.NaT,
+            NaT,
             Timestamp("2013-01-04"),
         ]
         expected = Index(expected_list, dtype=object, name="idx")

pandas/tests/indexes/datetimes/test_constructors.py

@@ -506,8 +506,8 @@ def test_construction_outofbounds(self):
     def test_construction_with_ndarray(self):
         # GH 5152
         dates = [datetime(2013, 10, 7), datetime(2013, 10, 8), datetime(2013, 10, 9)]
-        data = DatetimeIndex(dates, freq=pd.offsets.BDay()).values
-        result = DatetimeIndex(data, freq=pd.offsets.BDay())
+        data = DatetimeIndex(dates, freq=offsets.BDay()).values
+        result = DatetimeIndex(data, freq=offsets.BDay())
         expected = DatetimeIndex(["2013-10-07", "2013-10-08", "2013-10-09"], freq="B")
         tm.assert_index_equal(result, expected)
 

pandas/tests/indexes/datetimes/test_date_range.py

@@ -1009,7 +1009,7 @@ def test_range_with_millisecond_resolution(self, start_end):
 
 def test_date_range_with_custom_holidays():
     # GH 30593
-    freq = pd.offsets.CustomBusinessHour(start="15:00", holidays=["2020-11-26"])
+    freq = offsets.CustomBusinessHour(start="15:00", holidays=["2020-11-26"])
     result = date_range(start="2020-11-25 15:00", periods=4, freq=freq)
     expected = DatetimeIndex(
         [

pandas/tests/indexes/datetimes/test_datetime.py

@@ -210,7 +210,7 @@ def test_asarray_tz_naive(self):
         # optionally, object
         result = np.asarray(idx, dtype=object)
 
-        expected = np.array([pd.Timestamp("2000-01-01"), pd.Timestamp("2000-01-02")])
+        expected = np.array([Timestamp("2000-01-01"), Timestamp("2000-01-02")])
         tm.assert_numpy_array_equal(result, expected)
 
     def test_asarray_tz_aware(self):
@@ -228,7 +228,7 @@ def test_asarray_tz_aware(self):
 
         # Future behavior with no warning
         expected = np.array(
-            [pd.Timestamp("2000-01-01", tz=tz), pd.Timestamp("2000-01-02", tz=tz)]
+            [Timestamp("2000-01-01", tz=tz), Timestamp("2000-01-02", tz=tz)]
         )
         result = np.asarray(idx, dtype=object)
 

pandas/tests/indexes/multi/test_conversion.py

@@ -87,7 +87,7 @@ def test_to_frame():
 
 def test_to_frame_dtype_fidelity():
     # GH 22420
-    mi = pd.MultiIndex.from_arrays(
+    mi = MultiIndex.from_arrays(
         [
             pd.date_range("19910905", periods=6, tz="US/Eastern"),
             [1, 1, 1, 2, 2, 2],
@@ -116,7 +116,7 @@ def test_to_frame_dtype_fidelity():
 def test_to_frame_resulting_column_order():
     # GH 22420
     expected = ["z", 0, "a"]
-    mi = pd.MultiIndex.from_arrays(
+    mi = MultiIndex.from_arrays(
         [["a", "b", "c"], ["x", "y", "z"], ["q", "w", "e"]], names=expected
     )
     result = mi.to_frame().columns.tolist()

pandas/tests/indexes/multi/test_drop.py

@@ -184,7 +184,7 @@ def test_single_level_drop_partially_missing_elements():
 
 def test_droplevel_multiindex_one_level():
     # GH#37208
-    index = pd.MultiIndex.from_tuples([(2,)], names=("b",))
+    index = MultiIndex.from_tuples([(2,)], names=("b",))
     result = index.droplevel([])
     expected = pd.Int64Index([2], name="b")
     tm.assert_index_equal(result, expected)

pandas/tests/indexes/multi/test_equivalence.py

@@ -219,11 +219,11 @@ def test_equals_missing_values():
 
 def test_equals_missing_values_differently_sorted():
     # GH#38439
-    mi1 = pd.MultiIndex.from_tuples([(81.0, np.nan), (np.nan, np.nan)])
-    mi2 = pd.MultiIndex.from_tuples([(np.nan, np.nan), (81.0, np.nan)])
+    mi1 = MultiIndex.from_tuples([(81.0, np.nan), (np.nan, np.nan)])
+    mi2 = MultiIndex.from_tuples([(np.nan, np.nan), (81.0, np.nan)])
     assert not mi1.equals(mi2)
 
-    mi2 = pd.MultiIndex.from_tuples([(81.0, np.nan), (np.nan, np.nan)])
+    mi2 = MultiIndex.from_tuples([(81.0, np.nan), (np.nan, np.nan)])
     assert mi1.equals(mi2)
 
 

pandas/tests/indexes/multi/test_join.py

@@ -1,7 +1,6 @@
 import numpy as np
 import pytest
 
-import pandas as pd
 from pandas import Index, MultiIndex
 import pandas._testing as tm
 
@@ -51,12 +50,12 @@ def test_join_self(idx, join_type):
 
 def test_join_multi():
     # GH 10665
-    midx = pd.MultiIndex.from_product([np.arange(4), np.arange(4)], names=["a", "b"])
+    midx = MultiIndex.from_product([np.arange(4), np.arange(4)], names=["a", "b"])
     idx = Index([1, 2, 5], name="b")
 
     # inner
     jidx, lidx, ridx = midx.join(idx, how="inner", return_indexers=True)
-    exp_idx = pd.MultiIndex.from_product([np.arange(4), [1, 2]], names=["a", "b"])
+    exp_idx = MultiIndex.from_product([np.arange(4), [1, 2]], names=["a", "b"])
     exp_lidx = np.array([1, 2, 5, 6, 9, 10, 13, 14], dtype=np.intp)
     exp_ridx = np.array([0, 1, 0, 1, 0, 1, 0, 1], dtype=np.intp)
     tm.assert_index_equal(jidx, exp_idx)
@@ -93,8 +92,8 @@ def test_join_multi_wrong_order():
     # GH 25760
     # GH 28956
 
-    midx1 = pd.MultiIndex.from_product([[1, 2], [3, 4]], names=["a", "b"])
-    midx2 = pd.MultiIndex.from_product([[1, 2], [3, 4]], names=["b", "a"])
+    midx1 = MultiIndex.from_product([[1, 2], [3, 4]], names=["a", "b"])
+    midx2 = MultiIndex.from_product([[1, 2], [3, 4]], names=["b", "a"])
 
     join_idx, lidx, ridx = midx1.join(midx2, return_indexers=True)
 
@@ -108,8 +107,8 @@ def test_join_multi_wrong_order():
 def test_join_multi_return_indexers():
     # GH 34074
 
-    midx1 = pd.MultiIndex.from_product([[1, 2], [3, 4], [5, 6]], names=["a", "b", "c"])
-    midx2 = pd.MultiIndex.from_product([[1, 2], [3, 4]], names=["a", "b"])
+    midx1 = MultiIndex.from_product([[1, 2], [3, 4], [5, 6]], names=["a", "b", "c"])
+    midx2 = MultiIndex.from_product([[1, 2], [3, 4]], names=["a", "b"])
 
     result = midx1.join(midx2, return_indexers=False)
     tm.assert_index_equal(result, midx1)

pandas/tests/indexes/multi/test_reindex.py

@@ -49,7 +49,7 @@ def test_reindex_preserves_names_when_target_is_list_or_ndarray(idx):
     target = idx.copy()
     idx.names = target.names = [None, None]
 
-    other_dtype = pd.MultiIndex.from_product([[1, 2], [3, 4]])
+    other_dtype = MultiIndex.from_product([[1, 2], [3, 4]])
 
     # list & ndarray cases
     assert idx.reindex([])[0].names == [None, None]
@@ -70,14 +70,14 @@ def test_reindex_preserves_names_when_target_is_list_or_ndarray(idx):
 
 def test_reindex_lvl_preserves_names_when_target_is_list_or_array():
     # GH7774
-    idx = pd.MultiIndex.from_product([[0, 1], ["a", "b"]], names=["foo", "bar"])
+    idx = MultiIndex.from_product([[0, 1], ["a", "b"]], names=["foo", "bar"])
     assert idx.reindex([], level=0)[0].names == ["foo", "bar"]
     assert idx.reindex([], level=1)[0].names == ["foo", "bar"]
 
 
 def test_reindex_lvl_preserves_type_if_target_is_empty_list_or_array():
     # GH7774
-    idx = pd.MultiIndex.from_product([[0, 1], ["a", "b"]])
+    idx = MultiIndex.from_product([[0, 1], ["a", "b"]])
     assert idx.reindex([], level=0)[0].levels[0].dtype.type == np.int64
     assert idx.reindex([], level=1)[0].levels[1].dtype.type == np.object_
 
@@ -94,9 +94,9 @@ def test_reindex_base(idx):
 
 
 def test_reindex_non_unique():
-    idx = pd.MultiIndex.from_tuples([(0, 0), (1, 1), (1, 1), (2, 2)])
+    idx = MultiIndex.from_tuples([(0, 0), (1, 1), (1, 1), (2, 2)])
     a = pd.Series(np.arange(4), index=idx)
-    new_idx = pd.MultiIndex.from_tuples([(0, 0), (1, 1), (2, 2)])
+    new_idx = MultiIndex.from_tuples([(0, 0), (1, 1), (2, 2)])
 
     msg = "cannot handle a non-unique multi-index!"
     with pytest.raises(ValueError, match=msg):