BUG: Large object array isin

closes #16012

Author: Morgan Stuart <morgansstuart243@gmail.com>

Closes #16969 from Morgan243/large_array_isin and squashes the following commits:

31cb4b3 [Morgan Stuart] Removed unneeded details from whatsnew description
4b59745 [Morgan Stuart] Linting errors; additional test clarification
186607b [Morgan Stuart] BUG #16012 - fix isin for large object arrays

Author: Morgan243

doc/source/whatsnew/v0.21.0.txt

@@ -178,8 +178,6 @@ Performance Improvements
 Bug Fixes
 ~~~~~~~~~
 
-- Fixes regression in 0.20, :func:`Series.aggregate` and :func:`DataFrame.aggregate` allow dictionaries as return values again (:issue:`16741`)
-- Fixes bug where indexing with ``np.inf`` caused an ``OverflowError`` to be raised (:issue:`16957`)
 
 Conversion
 ^^^^^^^^^^
@@ -193,6 +191,7 @@ Indexing
 - Fixes regression in 0.20.3 when indexing with a string on a ``TimedeltaIndex`` (:issue:`16896`).
 - Fixed :func:`TimedeltaIndex.get_loc` handling of ``np.timedelta64`` inputs (:issue:`16909`).
 - Fix :func:`MultiIndex.sort_index` ordering when ``ascending`` argument is a list, but not all levels are specified, or are in a different order (:issue:`16934`).
+- Fixes bug where indexing with ``np.inf`` caused an ``OverflowError`` to be raised (:issue:`16957`)
 
 I/O
 ^^^
@@ -222,6 +221,8 @@ Sparse
 Reshaping
 ^^^^^^^^^
 - Joining/Merging with a non unique ``PeriodIndex`` raised a TypeError (:issue:`16871`)
+- Bug when using :func:`isin` on a large object series and large comparison array (:issue:`16012`)
+- Fixes regression from 0.20, :func:`Series.aggregate` and :func:`DataFrame.aggregate` allow dictionaries as return values again (:issue:`16741`)
 
 
 Numeric

pandas/core/algorithms.py

@@ -402,7 +402,10 @@ def isin(comps, values):
     # work-around for numpy < 1.8 and comparisions on py3
     # faster for larger cases to use np.in1d
     f = lambda x, y: htable.ismember_object(x, values)
-    if (_np_version_under1p8 and compat.PY3) or len(comps) > 1000000:
+    # GH16012
+    # Ensure np.in1d doesn't get object types or it *may* throw an exception
+    if ((_np_version_under1p8 and compat.PY3) or len(comps) > 1000000 and
+       not is_object_dtype(comps)):
         f = lambda x, y: np.in1d(x, y)
     elif is_integer_dtype(comps):
         try:

pandas/tests/series/test_analytics.py

@@ -1092,6 +1092,18 @@ def test_isin(self):
         expected = Series([True, False, True, False, False, False, True, True])
         assert_series_equal(result, expected)
 
+        # GH: 16012
+        # This specific issue has to have a series over 1e6 in len, but the
+        # comparison array (in_list) must be large enough so that numpy doesn't
+        # do a manual masking trick that will avoid this issue altogether
+        s = Series(list('abcdefghijk' * 10 ** 5))
+        # If numpy doesn't do the manual comparison/mask, these
+        # unorderable mixed types are what cause the exception in numpy
+        in_list = [-1, 'a', 'b', 'G', 'Y', 'Z', 'E',
+                   'K', 'E', 'S', 'I', 'R', 'R'] * 6
+
+        assert s.isin(in_list).sum() == 200000
+
     def test_isin_with_string_scalar(self):
         # GH4763
         s = Series(['A', 'B', 'C', 'a', 'B', 'B', 'A', 'C'])