CLN/API: clean-up of level argument of isin for indexes

pandas/core/indexes/base.py

@@ -4649,7 +4649,7 @@ def map(self, mapper, na_action=None):
 
         return Index(new_values, **attributes)
 
-    def isin(self, values, level=None):
+    def isin(self, values):
         """
         Return a boolean array where the index values are in `values`.
 
@@ -4675,6 +4675,11 @@ def isin(self, values, level=None):
         is_contained : ndarray
             NumPy array of boolean values.
 
+        Raises
+        ------
+        TypeError
+            If `level` is passed and the index is not a `MultiIndex`.
+
         See Also
         --------
         Series.isin : Same for Series.
@@ -4733,8 +4738,6 @@ def isin(self, values, level=None):
         >>> dti.isin(['2000-03-11'])
         array([ True, False, False])
         """
-        if level is not None:
-            self._validate_index_level(level)
         return algos.isin(self, values)
 
     def _get_string_slice(self, key, use_lhs=True, use_rhs=True):

pandas/core/indexes/datetimelike.py

@@ -509,19 +509,8 @@ def __rsub__(self, other):
 
         cls.__rsub__ = __rsub__
 
-    def isin(self, values, level=None):
-        """
-        Compute boolean array of whether each index value is found in the
-        passed set of values.
-
-        Parameters
-        ----------
-        values : set or sequence of values
-
-        Returns
-        -------
-        is_contained : ndarray (boolean dtype)
-        """
+    @Appender(Index.isin.__doc__)
+    def isin(self, values):
         if not isinstance(values, type(self)):
             try:
                 values = type(self)(values)

pandas/core/indexes/numeric.py

@@ -442,9 +442,7 @@ def is_unique(self):
         return super().is_unique and self._nan_idxs.size < 2
 
     @Appender(Index.isin.__doc__)
-    def isin(self, values, level=None):
-        if level is not None:
-            self._validate_index_level(level)
+    def isin(self, values):
         return algorithms.isin(np.array(self), values)
 
 

pandas/tests/indexes/test_base.py

@@ -1776,36 +1776,25 @@ def test_isin_nan_common_float64(self, nulls_fixture):
         tm.assert_numpy_array_equal(Float64Index([1.0, nulls_fixture]).isin(
             [pd.NaT]), np.array([False, False]))
 
-    @pytest.mark.parametrize("level", [0, -1])
     @pytest.mark.parametrize("index", [
         Index(['qux', 'baz', 'foo', 'bar']),
         # Float64Index overrides isin, so must be checked separately
         Float64Index([1.0, 2.0, 3.0, 4.0])])
-    def test_isin_level_kwarg(self, level, index):
+    def test_isin_nonexisting(self, index):
         values = index.tolist()[-2:] + ['nonexisting']
 
         expected = np.array([False, False, True, True])
-        tm.assert_numpy_array_equal(expected, index.isin(values, level=level))
+        tm.assert_numpy_array_equal(expected, index.isin(values))
 
-        index.name = 'foobar'
-        tm.assert_numpy_array_equal(expected,
-                                    index.isin(values, level='foobar'))
-
-    @pytest.mark.parametrize("level", [1, 10, -2])
+    @pytest.mark.parametrize("level", [
+        1, 10, -2, 1.0, 'foobar', 'xyzzy', np.nan])
     @pytest.mark.parametrize("index", [
         Index(['qux', 'baz', 'foo', 'bar']),
         # Float64Index overrides isin, so must be checked separately
         Float64Index([1.0, 2.0, 3.0, 4.0])])
-    def test_isin_level_kwarg_raises_bad_index(self, level, index):
-        with pytest.raises(IndexError, match='Too many levels'):
-            index.isin([], level=level)
-
-    @pytest.mark.parametrize("level", [1.0, 'foobar', 'xyzzy', np.nan])
-    @pytest.mark.parametrize("index", [
-        Index(['qux', 'baz', 'foo', 'bar']),
-        Float64Index([1.0, 2.0, 3.0, 4.0])])
-    def test_isin_level_kwarg_raises_key(self, level, index):
-        with pytest.raises(KeyError, match='must be same as name'):
+    def test_isin_level_kwarg_raises(self, level, index):
+        msg = r"isin\(\) got an unexpected keyword argument 'level'"
+        with pytest.raises(TypeError, match=msg):
             index.isin([], level=level)
 
     @pytest.mark.parametrize("empty", [[], Series(), np.array([])])