CLN: Standardize searchsorted signatures

The parameter is "value" across the board.

xref pandas-devgh-14645.

Author: gfyoung

doc/source/whatsnew/v0.24.0.txt

@@ -570,6 +570,8 @@ Removal of prior version deprecations/changes
 - Strings passed into :meth:`DataFrame.groupby` that refer to both column and index levels will raise a ``ValueError`` (:issue:`14432`)
 - :meth:`Index.repeat` and :meth:`MultiIndex.repeat` have renamed the ``n`` argument to ``repeats`` (:issue:`14645`)
 - Removal of the previously deprecated ``as_indexer`` keyword completely from ``str.match()`` (:issue:`22356`, :issue:`6581`)
+- :meth:`Categorical.searchsorted()` and :meth:`Series.searchsorted()` have renamed the ``v`` argument to ``value`` (:issue:`14645`)
+- :meth:`TimedeltaIndex.searchsorted(), :meth:`DatetimeIndex.searchsorted()`, and :meth:`PeriodIndex.searchsorted()` have renamed the ``key`` argument to ``value`` (:issue:`14645`)
 
 .. _whatsnew_0240.performance:
 

pandas/core/arrays/categorical.py

@@ -1335,7 +1335,6 @@ def memory_usage(self, deep=False):
 
     @Substitution(klass='Categorical')
     @Appender(_shared_docs['searchsorted'])
-    @deprecate_kwarg(old_arg_name='v', new_arg_name='value')
     def searchsorted(self, value, side='left', sorter=None):
         if not self.ordered:
             raise ValueError("Categorical not ordered\nyou can use "

pandas/core/base.py

@@ -1228,7 +1228,6 @@ def factorize(self, sort=False, na_sentinel=-1):
 
     @Substitution(klass='IndexOpsMixin')
     @Appender(_shared_docs['searchsorted'])
-    @deprecate_kwarg(old_arg_name='key', new_arg_name='value')
     def searchsorted(self, value, side='left', sorter=None):
         # needs coercion on the key (DatetimeIndex does already)
         return self.values.searchsorted(value, side=side, sorter=sorter)

pandas/core/indexes/period.py

@@ -426,7 +426,6 @@ def astype(self, dtype, copy=True, how='start'):
 
     @Substitution(klass='PeriodIndex')
     @Appender(_shared_docs['searchsorted'])
-    @deprecate_kwarg(old_arg_name='key', new_arg_name='value')
     def searchsorted(self, value, side='left', sorter=None):
         if isinstance(value, Period):
             if value.freq != self.freq:

pandas/core/indexes/timedeltas.py

@@ -609,7 +609,6 @@ def _partial_td_slice(self, key, freq, use_lhs=True, use_rhs=True):
 
     @Substitution(klass='TimedeltaIndex')
     @Appender(_shared_docs['searchsorted'])
-    @deprecate_kwarg(old_arg_name='key', new_arg_name='value')
     def searchsorted(self, value, side='left', sorter=None):
         if isinstance(value, (np.ndarray, Index)):
             value = np.array(value, dtype=_TD_DTYPE, copy=False)

pandas/core/series.py

@@ -2089,7 +2089,6 @@ def __rmatmul__(self, other):
 
     @Substitution(klass='Series')
     @Appender(base._shared_docs['searchsorted'])
-    @deprecate_kwarg(old_arg_name='v', new_arg_name='value')
     def searchsorted(self, value, side='left', sorter=None):
         if sorter is not None:
             sorter = ensure_platform_int(sorter)

pandas/tests/arrays/categorical/test_analytics.py

@@ -118,11 +118,6 @@ def test_searchsorted(self):
         pytest.raises(ValueError, lambda: c2.searchsorted('apple'))
         pytest.raises(ValueError, lambda: s2.searchsorted('apple'))
 
-        with tm.assert_produces_warning(FutureWarning):
-            res = c1.searchsorted(v=['bread'])
-            exp = np.array([3], dtype=np.intp)
-            tm.assert_numpy_array_equal(res, exp)
-
     def test_unique(self):
         # categories are reordered based on value when ordered=False
         cat = Categorical(["a", "b"])

pandas/tests/indexes/period/test_tools.py

@@ -220,9 +220,6 @@ def test_searchsorted(self, freq):
         with tm.assert_raises_regex(period.IncompatibleFrequency, msg):
             pidx.searchsorted(pd.Period('2014-01-01', freq='5D'))
 
-        with tm.assert_produces_warning(FutureWarning):
-            pidx.searchsorted(key=p2)
-
 
 class TestPeriodIndexConversion(object):
     def test_tolist(self):

pandas/tests/series/test_analytics.py

@@ -1368,10 +1368,6 @@ def test_searchsorted(self):
         idx = s.searchsorted(1, side='right')
         tm.assert_numpy_array_equal(idx, np.array([1], dtype=np.intp))
 
-        with tm.assert_produces_warning(FutureWarning):
-            idx = s.searchsorted(v=1, side='left')
-            tm.assert_numpy_array_equal(idx, np.array([0], dtype=np.intp))
-
     def test_searchsorted_numeric_dtypes_scalar(self):
         s = Series([1, 2, 90, 1000, 3e9])
         r = s.searchsorted(30)