Fix - BUG: AssertionError when slicing MultiIndex and setting value o…

pandas/core/indexes/base.py

@@ -1,24 +1,29 @@
+import operator
+import warnings
 from copy import copy as copy_func
 from datetime import datetime
-import operator
 from textwrap import dedent
 from typing import TYPE_CHECKING, Any, Callable, FrozenSet, Hashable, Optional, Union
-import warnings
 
 import numpy as np
-
-from pandas._libs import algos as libalgos, index as libindex, lib
 import pandas._libs.join as libjoin
 from pandas._libs.lib import is_datetime_array, no_default
-from pandas._libs.tslibs import OutOfBoundsDatetime, Timestamp
 from pandas._libs.tslibs.period import IncompatibleFrequency
 from pandas._libs.tslibs.timezones import tz_compare
+
+import pandas.core.algorithms as algos
+import pandas.core.common as com
+import pandas.core.missing as missing
+from pandas._libs import algos as libalgos, index as libindex, lib
+from pandas._libs.tslibs import OutOfBoundsDatetime, Timestamp
 from pandas._typing import DtypeObj, Label
 from pandas.compat import set_function_name
 from pandas.compat.numpy import function as nv
-from pandas.errors import InvalidIndexError
-from pandas.util._decorators import Appender, Substitution, cache_readonly, doc
-
+from pandas.core import ops
+from pandas.core.accessor import CachedAccessor
+from pandas.core.arrays import Categorical, ExtensionArray
+from pandas.core.arrays.datetimes import tz_to_dtype, validate_tz_from_dtype
+from pandas.core.base import IndexOpsMixin, PandasObject
 from pandas.core.dtypes import concat as _concat
 from pandas.core.dtypes.cast import (
     maybe_cast_to_integer_array,
@@ -63,29 +68,21 @@
     ABCTimedeltaIndex,
 )
 from pandas.core.dtypes.missing import array_equivalent, isna
-
-from pandas.core import ops
-from pandas.core.accessor import CachedAccessor
-import pandas.core.algorithms as algos
-from pandas.core.arrays import Categorical, ExtensionArray
-from pandas.core.arrays.datetimes import tz_to_dtype, validate_tz_from_dtype
-from pandas.core.base import IndexOpsMixin, PandasObject
-import pandas.core.common as com
 from pandas.core.indexers import deprecate_ndim_indexing
 from pandas.core.indexes.frozen import FrozenList
-import pandas.core.missing as missing
 from pandas.core.ops import get_op_result_name
 from pandas.core.ops.invalid import make_invalid_op
 from pandas.core.sorting import ensure_key_mapped
 from pandas.core.strings import StringMethods
-
+from pandas.errors import InvalidIndexError
 from pandas.io.formats.printing import (
     PrettyDict,
     default_pprint,
     format_object_attrs,
     format_object_summary,
     pprint_thing,
 )
+from pandas.util._decorators import Appender, Substitution, cache_readonly, doc
 
 if TYPE_CHECKING:
     from pandas import Series
@@ -4946,12 +4943,6 @@ def slice_indexer(self, start=None, end=None, step=None, kind=None):
         """
         start_slice, end_slice = self.slice_locs(start, end, step=step, kind=kind)
 
-        # return a slice
-        if not is_scalar(start_slice):
-            raise AssertionError("Start slice bound is non-scalar")
-        if not is_scalar(end_slice):
-            raise AssertionError("End slice bound is non-scalar")
-
         return slice(start_slice, end_slice, step)
 
     def _maybe_cast_indexer(self, key):

pandas/core/indexes/multi.py

@@ -2890,7 +2890,11 @@ def convert_indexer(start, stop, step, indexer=indexer, codes=level_codes):
             # if we have a provided indexer, then this need not consider
             # the entire labels set
 
-            r = np.arange(start, stop, step)
+            if is_scalar(start) and is_scalar(stop):
+                r = np.arange(start, stop, step)
+            else:
+                r = np.all(start, stop, step)
+
             if indexer is not None and len(indexer) != len(codes):
 
                 # we have an indexer which maps the locations in the labels

pandas/tests/indexing/test_loc.py

@@ -969,6 +969,22 @@ def test_loc_reverse_assignment(self):
 
         tm.assert_series_equal(result, expected)
 
+    def test_loc_setting_value_at_multiindex(self):
+        # GH 34870
+        arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
+                  ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
+        array = [1, 1, 1, 1, 1, 1, 1, 1]
+        answer = [1, 1, 100, 100, 100, 100, 1, 1]
+
+        tuples = list(zip(*arrays))
+        index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
+
+        dt1 = pd.Series(array, index=index)
+        dt2 = pd.Series(answer, index=index)
+
+        dt1.loc[('baz', 'one'):('foo', 'two')] = 100
+        tm.assert_series_equal(dt1, dt2)
+
 
 def test_series_loc_getitem_label_list_missing_values():
     # gh-11428