ENH: Implement IntegerArray.sum (#33538)

Author: dsaxton

doc/source/whatsnew/v1.1.0.rst

@@ -662,6 +662,7 @@ Other
 - Bug in :meth:`Series.map` not raising on invalid ``na_action`` (:issue:`32815`)
 - Bug in :meth:`DataFrame.__dir__` caused a segfault when using unicode surrogates in a column name (:issue:`25509`)
 - Bug in :meth:`DataFrame.plot.scatter` caused an error when plotting variable marker sizes (:issue:`32904`)
+- :class:`IntegerArray` now implements the ``sum`` operation (:issue:`33172`)
 
 .. ---------------------------------------------------------------------------
 

pandas/compat/numpy/function.py

@@ -252,6 +252,7 @@ def validate_cum_func_with_skipna(skipna, args, kwargs, name):
 STAT_FUNC_DEFAULTS["out"] = None
 
 PROD_DEFAULTS = SUM_DEFAULTS = STAT_FUNC_DEFAULTS.copy()
+SUM_DEFAULTS["axis"] = None
 SUM_DEFAULTS["keepdims"] = False
 SUM_DEFAULTS["initial"] = None
 

pandas/core/arrays/integer.py

@@ -7,6 +7,7 @@
 from pandas._libs import lib, missing as libmissing
 from pandas._typing import ArrayLike
 from pandas.compat import set_function_name
+from pandas.compat.numpy import function as nv
 from pandas.util._decorators import cache_readonly
 
 from pandas.core.dtypes.base import ExtensionDtype
@@ -573,6 +574,13 @@ def _reduce(self, name: str, skipna: bool = True, **kwargs):
 
         return result
 
+    def sum(self, skipna=True, min_count=0, **kwargs):
+        nv.validate_sum((), kwargs)
+        result = masked_reductions.sum(
+            values=self._data, mask=self._mask, skipna=skipna, min_count=min_count
+        )
+        return result
+
     def _maybe_mask_result(self, result, mask, other, op_name: str):
         """
         Parameters

pandas/tests/arrays/integer/test_function.py

@@ -113,6 +113,26 @@ def test_value_counts_empty():
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.parametrize("skipna", [True, False])
+@pytest.mark.parametrize("min_count", [0, 4])
+def test_integer_array_sum(skipna, min_count):
+    arr = pd.array([1, 2, 3, None], dtype="Int64")
+    result = arr.sum(skipna=skipna, min_count=min_count)
+    if skipna and min_count == 0:
+        assert result == 6
+    else:
+        assert result is pd.NA
+
+
+@pytest.mark.parametrize(
+    "values, expected", [([1, 2, 3], 6), ([1, 2, 3, None], 6), ([None], 0)]
+)
+def test_integer_array_numpy_sum(values, expected):
+    arr = pd.array(values, dtype="Int64")
+    result = np.sum(arr)
+    assert result == expected
+
+
 # TODO(jreback) - these need testing / are broken
 
 # shift