BUG: Series.combine() fails with ExtensionArray inside of Series

doc/source/whatsnew/v0.24.0.txt

@@ -181,7 +181,8 @@ Reshaping
 Other
 ^^^^^
 
--
+- :meth:`Series.combine()` works correctly with :class:`~pandas.api.extensions.ExtensionArray` inside of :class:`Series` (:issue:`20825`)
+- :meth:`Series.combine()` with scalar argument now works for any function type (:issue:`21248`)
 -
 -
 

pandas/core/series.py

@@ -2196,7 +2196,7 @@ def _binop(self, other, func, level=None, fill_value=None):
             result.name = None
         return result
 
-    def combine(self, other, func, fill_value=np.nan):
+    def combine(self, other, func, fill_value=None):
         """
         Perform elementwise binary operation on two Series using given function
         with optional fill value when an index is missing from one Series or
@@ -2208,6 +2208,8 @@ def combine(self, other, func, fill_value=np.nan):
         func : function
             Function that takes two scalars as inputs and return a scalar
         fill_value : scalar value
+            The default specifies to use the appropriate NaN value for
+            the underlying dtype of the Series
 
         Returns
         -------
@@ -2227,20 +2229,31 @@ def combine(self, other, func, fill_value=np.nan):
         Series.combine_first : Combine Series values, choosing the calling
             Series's values first
         """
+        self_is_ext = is_extension_array_dtype(self.values)
+        if fill_value is None:
+            fill_value = na_value_for_dtype(self.dtype, False)
+
         if isinstance(other, Series):
             new_index = self.index.union(other.index)
             new_name = ops.get_op_result_name(self, other)
-            new_values = np.empty(len(new_index), dtype=self.dtype)
-            for i, idx in enumerate(new_index):
+            new_values = []
+            for idx in new_index:
                 lv = self.get(idx, fill_value)
                 rv = other.get(idx, fill_value)
                 with np.errstate(all='ignore'):
-                    new_values[i] = func(lv, rv)
+                    new_values.append(func(lv, rv))
         else:
             new_index = self.index
             with np.errstate(all='ignore'):
-                new_values = func(self._values, other)
+                new_values = [func(lv, other) for lv in self._values]
             new_name = self.name
+
+        if self_is_ext and not is_categorical_dtype(self.values):
+            try:
+                new_values = self._values._from_sequence(new_values)
+            except TypeError:
+                pass
+
         return self._constructor(new_values, index=new_index, name=new_name)
 
     def combine_first(self, other):

pandas/tests/extension/category/test_categorical.py

@@ -2,6 +2,9 @@
 
 import pytest
 import numpy as np
+import pandas as pd
+
+import pandas.util.testing as tm
 
 from pandas.api.types import CategoricalDtype
 from pandas import Categorical
@@ -154,6 +157,17 @@ class TestMethods(base.BaseMethodsTests):
     def test_value_counts(self, all_data, dropna):
         pass
 
+    def test_combine(self):
+        # GH 20825
+        orig_data1 = make_data()
+        orig_data2 = make_data()
+        s1 = pd.Series(Categorical(orig_data1, ordered=True))
+        s2 = pd.Series(Categorical(orig_data2, ordered=True))
+        result = s1.combine(s2, lambda x1, x2: x1 <= x2)
+        expected = pd.Series([a <= b for (a, b) in
+                              zip(orig_data1, orig_data2)])
+        tm.assert_series_equal(result, expected)
+
 
 class TestCasting(base.BaseCastingTests):
     pass

pandas/tests/extension/decimal/array.py

@@ -28,7 +28,9 @@ class DecimalArray(ExtensionArray):
     dtype = DecimalDtype()
 
     def __init__(self, values):
-        assert all(isinstance(v, decimal.Decimal) for v in values)
+        for val in values:
+            if not isinstance(val, self.dtype.type):
+                raise TypeError
         values = np.asarray(values, dtype=object)
 
         self._data = values

pandas/tests/extension/decimal/test_decimal.py

@@ -138,6 +138,22 @@ def test_value_counts(self, all_data, dropna):
 
         tm.assert_series_equal(result, expected)
 
+    def test_combine(self):
+        # GH 20825
+        orig_data1 = make_data()
+        orig_data2 = make_data()
+        s1 = pd.Series(DecimalArray(orig_data1))
+        s2 = pd.Series(DecimalArray(orig_data2))
+        result = s1.combine(s2, lambda x1, x2: x1 <= x2)
+        expected = pd.Series([a <= b for (a, b) in
+                              zip(orig_data1, orig_data2)])
+        tm.assert_series_equal(result, expected)
+
+        result = s1.combine(s2, lambda x1, x2: x1 + x2)
+        expected = pd.Series(DecimalArray([a + b for (a, b) in
+                                           zip(orig_data1, orig_data2)]))
+        tm.assert_series_equal(result, expected)
+
 
 class TestCasting(BaseDecimal, base.BaseCastingTests):
     pass

pandas/tests/series/test_combine_concat.py

@@ -60,6 +60,19 @@ def test_append_duplicates(self):
         with tm.assert_raises_regex(ValueError, msg):
             pd.concat([s1, s2], verify_integrity=True)
 
+    def test_combine_scalar(self):
+        # GH 21248
+        # Note - combine() with another Series is tested elsewhere because
+        # it is used when testing operators
+        s = pd.Series([i * 10 for i in range(5)])
+        result = s.combine(3, lambda x, y: x + y)
+        expected = pd.Series([i * 10 + 3 for i in range(5)])
+        tm.assert_series_equal(result, expected)
+
+        result = s.combine(22, lambda x, y: min(x, y))
+        expected = pd.Series([min(i * 10, 22) for i in range(5)])
+        tm.assert_series_equal(result, expected)
+
     def test_combine_first(self):
         values = tm.makeIntIndex(20).values.astype(float)
         series = Series(values, index=tm.makeIntIndex(20))