adjust for comments

Author: topper-123

pandas/tests/indexes/common.py

@@ -173,7 +173,7 @@ def test_get_indexer_consistency(self):
             if index.is_unique or isinstance(index, CategoricalIndex):
                 indexer = index.get_indexer(index[0:2])
                 assert isinstance(indexer, np.ndarray)
-                assert indexer.dtype == np.intp
+                assert indexer.tedtype == np.intp
             else:
                 e = "Reindexing only valid with uniquely valued Index objects"
                 with pytest.raises(InvalidIndexError, match=e):

pandas/tests/indexes/multi/test_monotonic.py

@@ -5,7 +5,7 @@
 
 import pandas as pd
 from pandas import Index, IntervalIndex, MultiIndex
-import pandas.util.testing as tm
+from pandas.api.types import is_scalar
 
 
 def test_is_monotonic_increasing():
@@ -183,28 +183,28 @@ def test_searchsorted_monotonic(indices):
     # test searchsorted only for increasing
     if indices.is_monotonic_increasing:
         ssm_left = indices._searchsorted_monotonic(value, side='left')
-        assert tm.is_scalar(ssm_left)
+        assert is_scalar(ssm_left)
         assert expected_left == ssm_left
 
         ssm_right = indices._searchsorted_monotonic(value, side='right')
-        assert tm.is_scalar(ssm_right)
+        assert is_scalar(ssm_right)
         assert expected_right == ssm_right
 
         ss_left = indices.searchsorted(value, side='left')
-        assert tm.is_scalar(ss_left)
+        assert is_scalar(ss_left)
         assert expected_left == ss_left
 
         ss_right = indices.searchsorted(value, side='right')
-        assert tm.is_scalar(ss_right)
+        assert is_scalar(ss_right)
         assert expected_right == ss_right
 
     elif indices.is_monotonic_decreasing:
         ssm_left = indices._searchsorted_monotonic(value, side='left')
-        assert tm.is_scalar(ssm_left)
+        assert is_scalar(ssm_left)
         assert expected_left == ssm_left
 
         ssm_right = indices._searchsorted_monotonic(value, side='right')
-        assert tm.is_scalar(ssm_right)
+        assert is_scalar(ssm_right)
         assert expected_right == ssm_right
 
     else:

pandas/tests/series/test_analytics.py

@@ -16,6 +16,7 @@
 from pandas import (
     Categorical, CategoricalIndex, DataFrame, Series, bdate_range, compat,
     date_range, isna, notna)
+from pandas.api.types import is_scalar
 from pandas.core.index import MultiIndex
 from pandas.core.indexes.datetimes import Timestamp
 from pandas.core.indexes.timedeltas import Timedelta
@@ -1357,17 +1358,17 @@ def test_searchsorted(self):
         s = Series([1, 2, 3])
 
         result = s.searchsorted(1, side='left')
-        assert tm.is_scalar(result)
+        assert is_scalar(result)
         assert result == 0
 
         result = s.searchsorted(1, side='right')
-        assert tm.is_scalar(result)
+        assert is_scalar(result)
         assert result == 1
 
     def test_searchsorted_numeric_dtypes_scalar(self):
         s = Series([1, 2, 90, 1000, 3e9])
         r = s.searchsorted(30)
-        assert tm.is_scalar(r)
+        assert is_scalar(r)
         assert r == 2
 
         r = s.searchsorted([30])
@@ -1384,7 +1385,7 @@ def test_search_sorted_datetime64_scalar(self):
         s = Series(pd.date_range('20120101', periods=10, freq='2D'))
         v = pd.Timestamp('20120102')
         r = s.searchsorted(v)
-        assert tm.is_scalar(r)
+        assert is_scalar(r)
         assert r == 1
 
     def test_search_sorted_datetime64_list(self):

pandas/util/testing.py

@@ -28,7 +28,6 @@
     is_datetimelike_v_numeric, is_datetimelike_v_object,
     is_extension_array_dtype, is_interval_dtype, is_list_like, is_number,
     is_period_dtype, is_sequence, is_timedelta64_dtype, needs_i8_conversion)
-from pandas.core.dtypes.common import is_scalar  # noqa: F401
 from pandas.core.dtypes.missing import array_equivalent
 
 import pandas as pd