adjust for comments

Author: topper-123

pandas/core/base.py

@@ -1339,7 +1339,7 @@ def factorize(self, sort=False, na_sentinel=-1):
         Parameters
         ----------
         value : scalar or array_like
-            Value(s) to insert into `self`.
+            Value(s) to insert into `self`.t
         side : {'left', 'right'}, optional
             If 'left', the index of the first suitable location found is given.
             If 'right', return the last such index.  If there is no suitable

pandas/tests/arrays/categorical/test_analytics.py

@@ -8,6 +8,7 @@
 from pandas.compat import PYPY
 
 from pandas import Categorical, Index, Series
+from pandas.api.types import is_scalar
 import pandas.util.testing as tm
 
 
@@ -86,11 +87,11 @@ def test_searchsorted(self):
         # Searching for single item argument, side='left' (default)
         res_cat = c1.searchsorted('apple')
         assert res_cat == 2
-        assert tm.is_scalar(res_cat)
+        assert is_scalar(res_cat)
 
         res_ser = s1.searchsorted('apple')
         assert res_ser == 2
-        assert tm.is_scalar(res_ser)
+        assert is_scalar(res_ser)
 
         # Searching for single item array, side='left' (default)
         res_cat = c1.searchsorted(['bread'])

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
@@ -1365,17 +1366,17 @@ 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])
@@ -1392,7 +1393,7 @@ 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