Fix bug where nanops._has_infs doesn't work with many dtypes (issue #7357)

doc/source/v0.14.1.txt

@@ -219,6 +219,8 @@ Bug Fixes
   1-dimensional ``nan`` arrays (:issue:`7354`)
 - Bug where ``nanops.nanmedian`` doesn't work when ``axis==None``
   (:issue:`7352`)
+- Bug where ``nanops._has_infs`` doesn't work with many dtypes
+  (:issue:`7357`)
 
 
 

pandas/core/nanops.py

@@ -105,14 +105,18 @@ def _bn_ok_dtype(dt, name):
         return True
     return False
 
+
 def _has_infs(result):
     if isinstance(result, np.ndarray):
         if result.dtype == 'f8':
-            return lib.has_infs_f8(result)
+            return lib.has_infs_f8(result.ravel())
         elif result.dtype == 'f4':
-            return lib.has_infs_f4(result)
+            return lib.has_infs_f4(result.ravel())
+    try:
+        return np.isinf(result).any()
+    except (TypeError, NotImplementedError) as e:
+        # if it doesn't support infs, then it can't have infs
         return False
-    return np.isinf(result) or np.isneginf(result)
 
 
 def _get_fill_value(dtype, fill_value=None, fill_value_typ=None):
@@ -538,18 +542,20 @@ def _maybe_arg_null_out(result, axis, mask, skipna):
 
 
 def _get_counts(mask, axis):
-    if axis is not None:
-        count = (mask.shape[axis] - mask.sum(axis)).astype(float)
-    else:
-        count = float(mask.size - mask.sum())
+    if axis is None:
+        return float(mask.size - mask.sum())
 
-    return count
+    count = mask.shape[axis] - mask.sum(axis)
+    try:
+        return count.astype(float)
+    except AttributeError:
+        return np.array(count, dtype=float)
 
 
 def _maybe_null_out(result, axis, mask):
     if axis is not None and getattr(result, 'ndim', False):
         null_mask = (mask.shape[axis] - mask.sum(axis)) == 0
-        if null_mask.any():
+        if np.any(null_mask):
             if np.iscomplexobj(result):
                 result = result.astype('c16')
             else:
@@ -638,8 +644,16 @@ def nancov(a, b, min_periods=None):
 
 def _ensure_numeric(x):
     if isinstance(x, np.ndarray):
-        if x.dtype == np.object_:
+        if x.dtype.kind in ['i', 'b']:
             x = x.astype(np.float64)
+        elif x.dtype == np.object_:
+            try:
+                x = x.astype(np.complex128)
+            except:
+                x = x.astype(np.float64)
+            else:
+                if not np.any(x.imag):
+                    x = x.real
     elif not (com.is_float(x) or com.is_integer(x) or com.is_complex(x)):
         try:
             x = float(x)

pandas/tests/test_nanops.py

@@ -597,25 +597,27 @@ def check_bool(self, func, value, correct, *args, **kwargs):
                 break
 
     def test__has_infs(self):
-        pairs = [('arr_complex_1d', False),
-                 ('arr_int_1d', False),
-                 ('arr_bool_1d', False),
-                 ('arr_str_1d', False),
-                 ('arr_utf_1d', False),
-                 ('arr_complex_1d', False),
-                 ('arr_complex_nan_1d', False),
-
-                 ('arr_nan_nanj_1d', False)]
-        pairs_float = [('arr_float_1d', False),
-                       ('arr_nan_1d', False),
-                       ('arr_float_nan_1d', False),
-                       ('arr_nan_nan_1d', False),
-
-                       ('arr_float_inf_1d', True),
-                       ('arr_inf_1d', True),
-                       ('arr_nan_inf_1d', True),
-                       ('arr_float_nan_inf_1d', True),
-                       ('arr_nan_nan_inf_1d', True)]
+        pairs = [('arr_complex', False),
+                 ('arr_int', False),
+                 ('arr_bool', False),
+                 ('arr_str', False),
+                 ('arr_utf', False),
+                 ('arr_complex', False),
+                 ('arr_complex_nan', False),
+
+                 ('arr_nan_nanj', False),
+                 ('arr_nan_infj', True),
+                 ('arr_complex_nan_infj', True)]
+        pairs_float = [('arr_float', False),
+                       ('arr_nan', False),
+                       ('arr_float_nan', False),
+                       ('arr_nan_nan', False),
+
+                       ('arr_float_inf', True),
+                       ('arr_inf', True),
+                       ('arr_nan_inf', True),
+                       ('arr_float_nan_inf', True),
+                       ('arr_nan_nan_inf', True)]
 
         for arr, correct in pairs:
             val = getattr(self, arr)
@@ -630,6 +632,7 @@ def test__has_infs(self):
             try:
                 self.check_bool(nanops._has_infs, val, correct)
                 self.check_bool(nanops._has_infs, val.astype('f4'), correct)
+                self.check_bool(nanops._has_infs, val.astype('f2'), correct)
             except BaseException as exc:
                 exc.args += (arr,)
                 raise