COMPAT: when "nan is nan" is not consistent across implementations

Author: mattip

pandas/tests/indexes/test_base.py

@@ -9,7 +9,7 @@
 from pandas.tests.indexes.common import Base
 
 from pandas.compat import (range, lrange, lzip, u,
-                           text_type, zip, PY3, PY36)
+                           text_type, zip, PY3, PY36, PYPY)
 import operator
 import numpy as np
 
@@ -1360,26 +1360,34 @@ def test_isin(self):
         assert len(result) == 0
         assert result.dtype == np.bool_
 
-    def test_isin_nan(self):
+    @pytest.mark.skipif(PYPY, reason="np.nan is float('nan') on PyPy")
+    def test_isin_nan_not_pypy(self):
+        tm.assert_numpy_array_equal(Index(['a', np.nan]).isin([float('nan')]),
+                                    np.array([False, False]))
+
+    @pytest.mark.skipif(not PYPY, reason="np.nan is float('nan') on PyPy")
+    def test_isin_nan_pypy(self):
+        tm.assert_numpy_array_equal(Index(['a', np.nan]).isin([float('nan')]),
+                                    np.array([False, True]))
+
+    def test_isin_nan_common(self):
         tm.assert_numpy_array_equal(Index(['a', np.nan]).isin([np.nan]),
                                     np.array([False, True]))
         tm.assert_numpy_array_equal(Index(['a', pd.NaT]).isin([pd.NaT]),
                                     np.array([False, True]))
-        tm.assert_numpy_array_equal(Index(['a', np.nan]).isin([float('nan')]),
-                                    np.array([False, False]))
         tm.assert_numpy_array_equal(Index(['a', np.nan]).isin([pd.NaT]),
                                     np.array([False, False]))
 
         # Float64Index overrides isin, so must be checked separately
         tm.assert_numpy_array_equal(Float64Index([1.0, np.nan]).isin([np.nan]),
                                     np.array([False, True]))
+        # we cannot compare NaT with NaN
+        tm.assert_numpy_array_equal(Float64Index([1.0, np.nan]).isin([pd.NaT]),
+                                    np.array([False, False]))
         tm.assert_numpy_array_equal(
             Float64Index([1.0, np.nan]).isin([float('nan')]),
             np.array([False, True]))
 
-        # we cannot compare NaT with NaN
-        tm.assert_numpy_array_equal(Float64Index([1.0, np.nan]).isin([pd.NaT]),
-                                    np.array([False, False]))
 
     def test_isin_level_kwarg(self):
         def check_idx(idx):

pandas/tests/indexes/test_multi.py

@@ -14,7 +14,7 @@
 
 from pandas import (CategoricalIndex, DataFrame, Index, MultiIndex,
                     compat, date_range, period_range)
-from pandas.compat import PY3, long, lrange, lzip, range, u
+from pandas.compat import PY3, long, lrange, lzip, range, u, PYPY
 from pandas.errors import PerformanceWarning, UnsortedIndexError
 from pandas.core.indexes.base import InvalidIndexError
 from pandas._libs import lib
@@ -2574,13 +2574,22 @@ def test_isin(self):
         assert len(result) == 0
         assert result.dtype == np.bool_
 
-    def test_isin_nan(self):
+    @pytest.mark.skipif(PYPY, reason="tuples cmp recursively on PyPy")
+    def test_isin_nan_not_pypy(self):
         idx = MultiIndex.from_arrays([['foo', 'bar'], [1.0, np.nan]])
         tm.assert_numpy_array_equal(idx.isin([('bar', np.nan)]),
                                     np.array([False, False]))
         tm.assert_numpy_array_equal(idx.isin([('bar', float('nan'))]),
                                     np.array([False, False]))
 
+    @pytest.mark.skipif(not PYPY, reason="tuples cmp recursively on PyPy")
+    def test_isin_nan_pypy(self):
+        idx = MultiIndex.from_arrays([['foo', 'bar'], [1.0, np.nan]])
+        tm.assert_numpy_array_equal(idx.isin([('bar', np.nan)]),
+                                    np.array([False, True]))
+        tm.assert_numpy_array_equal(idx.isin([('bar', float('nan'))]),
+                                    np.array([False, True]))
+
     def test_isin_level_kwarg(self):
         idx = MultiIndex.from_arrays([['qux', 'baz', 'foo', 'bar'], np.arange(
             4)])