Added rest of Jeff's changes

Author: Brian Tu

doc/source/whatsnew/v0.21.0.txt

@@ -234,7 +234,7 @@ Other Enhancements
 - :meth:`DataFrame.assign` will preserve the original order of ``**kwargs`` for Python 3.6+ users instead of sorting the column names. (:issue:`14207`)
 - Improved the import time of pandas by about 2.25x.  (:issue:`16764`)
 - :func:`read_json` and :func:`to_json` now accept a ``compression`` argument which allows them to transparently handle compressed files. (:issue:`17798`)
-- :func:`Series.reindex`, :func:`DataFrame.reindex`, :func:`Index.get_indexer` now support list-like argument for ``tolerance``
+- :func:`Series.reindex`, :func:`DataFrame.reindex`, :func:`Index.get_indexer` now support list-like argument for ``tolerance``. (PR #17367)
 
 .. _whatsnew_0210.api_breaking:
 

pandas/core/indexes/base.py

@@ -2661,10 +2661,7 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
         method = missing.clean_reindex_fill_method(method)
         target = _ensure_index(target)
         if tolerance is not None:
-            tolerance = self._convert_tolerance(tolerance)
-            if target.size != tolerance.size and tolerance.size > 1:
-                raise ValueError('list-like tolerance size must match '
-                                 'target index size')
+            tolerance = self._convert_tolerance(tolerance, target)
 
         # Treat boolean labels passed to a numeric index as not found. Without
         # this fix False and True would be treated as 0 and 1 respectively.
@@ -2702,9 +2699,13 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
             indexer = self._engine.get_indexer(target._values)
         return _ensure_platform_int(indexer)
 
-    def _convert_tolerance(self, tolerance):
+    def _convert_tolerance(self, tolerance, target):
         # override this method on subclasses
-        return np.asarray(tolerance)
+        tolerance = np.asarray(tolerance)
+        if target.size != tolerance.size and tolerance.size > 1:
+            raise ValueError('list-like tolerance size must match '
+                                'target index size')
+        return tolerance
 
     def _get_fill_indexer(self, target, method, limit=None, tolerance=None):
         if self.is_monotonic_increasing and target.is_monotonic_increasing:

pandas/core/indexes/datetimelike.py

@@ -432,8 +432,12 @@ def asobject(self):
         from pandas.core.index import Index
         return Index(self._box_values(self.asi8), name=self.name, dtype=object)
 
-    def _convert_tolerance(self, tolerance):
-        return np.asarray(to_timedelta(tolerance, box=False))
+    def _convert_tolerance(self, tolerance, target):
+        tolerance = np.asarray(to_timedelta(tolerance, box=False))
+        if target.size != tolerance.size and tolerance.size > 1:
+            raise ValueError('list-like tolerance size must match '
+                                'target index size')
+        return tolerance
 
     def _maybe_mask_results(self, result, fill_value=None, convert=None):
         """

pandas/core/indexes/datetimes.py

@@ -1423,7 +1423,7 @@ def get_loc(self, key, method=None, tolerance=None):
         if tolerance is not None:
             # try converting tolerance now, so errors don't get swallowed by
             # the try/except clauses below
-            tolerance = self._convert_tolerance(tolerance)
+            tolerance = self._convert_tolerance(tolerance, np.asarray(key))
 
         if isinstance(key, datetime):
             # needed to localize naive datetimes

pandas/core/indexes/numeric.py

@@ -71,8 +71,11 @@ def _convert_for_op(self, value):
 
         return value
 
-    def _convert_tolerance(self, tolerance):
+    def _convert_tolerance(self, tolerance, target):
         tolerance = np.asarray(tolerance)
+        if target.size != tolerance.size and tolerance.size > 1:
+            raise ValueError('list-like tolerance size must match '
+                                'target index size')
         if not np.issubdtype(tolerance.dtype, np.number):
             if tolerance.ndim > 0:
                 raise ValueError(('tolerance argument for %s must contain '

pandas/core/indexes/period.py

@@ -787,10 +787,7 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
             target = target.asi8
 
         if tolerance is not None:
-            tolerance = self._convert_tolerance(tolerance)
-            if target.size != tolerance.size and tolerance.size > 1:
-                raise ValueError('list-like tolerance size must match '
-                                 'target index size')
+            tolerance = self._convert_tolerance(tolerance, target)
         return Index.get_indexer(self._int64index, target, method,
                                  limit, tolerance)
 
@@ -833,7 +830,8 @@ def get_loc(self, key, method=None, tolerance=None):
             try:
                 ordinal = tslib.iNaT if key is tslib.NaT else key.ordinal
                 if tolerance is not None:
-                    tolerance = self._convert_tolerance(tolerance)
+                    tolerance = self._convert_tolerance(tolerance,
+                                                        np.asarray(key))
                 return self._int64index.get_loc(ordinal, method, tolerance)
 
             except KeyError:
@@ -916,8 +914,12 @@ def _get_string_slice(self, key):
         return slice(self.searchsorted(t1.ordinal, side='left'),
                      self.searchsorted(t2.ordinal, side='right'))
 
-    def _convert_tolerance(self, tolerance):
-        tolerance = DatetimeIndexOpsMixin._convert_tolerance(self, tolerance)
+    def _convert_tolerance(self, tolerance, target):
+        tolerance = DatetimeIndexOpsMixin._convert_tolerance(self, tolerance,
+                                                                   target)
+        if target.size != tolerance.size and tolerance.size > 1:
+            raise ValueError('list-like tolerance size must match '
+                                'target index size')
         return self._maybe_convert_timedelta(tolerance)
 
     def insert(self, loc, item):

pandas/core/indexes/timedeltas.py

@@ -699,7 +699,7 @@ def get_loc(self, key, method=None, tolerance=None):
         if tolerance is not None:
             # try converting tolerance now, so errors don't get swallowed by
             # the try/except clauses below
-            tolerance = self._convert_tolerance(tolerance)
+            tolerance = self._convert_tolerance(tolerance, np.asarray(key))
 
         if _is_convertible_to_td(key):
             key = Timedelta(key)

pandas/core/tools/timedeltas.py

@@ -86,7 +86,7 @@ def to_timedelta(arg, unit='ns', box=True, errors='raise'):
     elif is_list_like(arg) and getattr(arg, 'ndim', 1) <= 1:
         if getattr(arg, 'ndim', 1) == 0:
             # extract array scalar and process below
-            arg = arg[()]
+            arg = arg.item()
         else:
             return _convert_listlike(arg, unit=unit, box=box, errors=errors)
     elif getattr(arg, 'ndim', 1) > 1: