BUG: Series.corr/cov raising with masked dtype (#51422)

Author: lukemanley

doc/source/whatsnew/v2.1.0.rst

@@ -132,7 +132,7 @@ Timezones
 
 Numeric
 ^^^^^^^
--
+- Bug in :meth:`Series.corr` and :meth:`Series.cov` raising ``AttributeError`` for masked dtypes (:issue:`51422`)
 -
 
 Conversion

pandas/core/nanops.py

@@ -1610,6 +1610,9 @@ def nancorr(
     if len(a) < min_periods:
         return np.nan
 
+    a = _ensure_numeric(a)
+    b = _ensure_numeric(b)
+
     f = get_corr_func(method)
     return f(a, b)
 
@@ -1668,6 +1671,9 @@ def nancov(
     if len(a) < min_periods:
         return np.nan
 
+    a = _ensure_numeric(a)
+    b = _ensure_numeric(b)
+
     return np.cov(a, b, ddof=ddof)[0, 1]
 
 

pandas/core/series.py

@@ -2643,9 +2643,12 @@ def corr(
         if len(this) == 0:
             return np.nan
 
+        this_values = np.asarray(this._values)
+        other_values = np.asarray(other._values)
+
         if method in ["pearson", "spearman", "kendall"] or callable(method):
             return nanops.nancorr(
-                this.values, other.values, method=method, min_periods=min_periods
+                this_values, other_values, method=method, min_periods=min_periods
             )
 
         raise ValueError(
@@ -2698,8 +2701,10 @@ def cov(
         this, other = self.align(other, join="inner", copy=False)
         if len(this) == 0:
             return np.nan
+        this_values = np.asarray(this._values)
+        other_values = np.asarray(other._values)
         return nanops.nancov(
-            this.values, other.values, min_periods=min_periods, ddof=ddof
+            this_values, other_values, min_periods=min_periods, ddof=ddof
         )
 
     @doc(

pandas/tests/frame/methods/test_cov_corr.py

@@ -356,7 +356,7 @@ def test_corrwith_mixed_dtypes(self, numeric_only):
         else:
             with pytest.raises(
                 TypeError,
-                match=r"unsupported operand type\(s\) for /: 'str' and 'int'",
+                match=r"Could not convert \['a' 'b' 'c' 'd'\] to numeric",
             ):
                 df.corrwith(s, numeric_only=numeric_only)
 

pandas/tests/series/methods/test_cov_corr.py

@@ -42,13 +42,14 @@ def test_cov(self, datetime_series):
         assert isna(ts1.cov(ts2, min_periods=12))
 
     @pytest.mark.parametrize("test_ddof", [None, 0, 1, 2, 3])
-    def test_cov_ddof(self, test_ddof):
+    @pytest.mark.parametrize("dtype", ["float64", "Float64"])
+    def test_cov_ddof(self, test_ddof, dtype):
         # GH#34611
         np_array1 = np.random.rand(10)
         np_array2 = np.random.rand(10)
 
-        s1 = Series(np_array1)
-        s2 = Series(np_array2)
+        s1 = Series(np_array1, dtype=dtype)
+        s2 = Series(np_array2, dtype=dtype)
 
         result = s1.cov(s2, ddof=test_ddof)
         expected = np.cov(np_array1, np_array2, ddof=test_ddof)[0][1]
@@ -57,9 +58,12 @@ def test_cov_ddof(self, test_ddof):
 
 class TestSeriesCorr:
     @td.skip_if_no_scipy
-    def test_corr(self, datetime_series):
+    @pytest.mark.parametrize("dtype", ["float64", "Float64"])
+    def test_corr(self, datetime_series, dtype):
         from scipy import stats
 
+        datetime_series = datetime_series.astype(dtype)
+
         # full overlap
         tm.assert_almost_equal(datetime_series.corr(datetime_series), 1)