Cleaned up call signature

Author: WillAyd

pandas/_libs/groupby_helper.pxi.in

@@ -882,12 +882,18 @@ def group_cummax_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
 @cython.boundscheck(False)
 @cython.wraparound(False)
 def group_any(ndarray[int64_t] out,
-              ndarray[int64_t] mask,
+              ndarray values,
               ndarray[int64_t] labels,
               bint skipna):
     cdef:
         Py_ssize_t i, N=len(labels)
         int64_t lab
+        ndarray[int64_t] mask
+
+    if values.dtype is np.object:
+        mask = np.array(bool(x) for x in values).astype(np.int64)
+    else:
+        mask = values.astype(np.bool).astype(np.int64)
 
     with nogil:
         for i in range(N):

pandas/core/groupby.py

@@ -1223,18 +1223,12 @@ class GroupBy(_GroupBy):
     @Appender(_doc_template)
     def any(self, skipna=True):
         """Returns True if any value in the group is truthful, else False"""
-        obj = self._obj_with_exclusions
-
         labels, _, _ = self.grouper.group_info
-
         output = collections.OrderedDict()
+
         for name, obj in self._iterate_slices():
             result = np.zeros(self.ngroups, dtype=np.int64)
-            if obj.dtype is np.object:
-                mask = np.array(bool(x) for x in obj.values)
-            else:
-                mask = obj.values.astype(np.bool)
-            libgroupby.group_any(result, mask.astype(np.int64), labels, skipna)
+            libgroupby.group_any(result, obj.values, labels, skipna)
             output[name] = result.astype(np.bool)
 
         return self._wrap_aggregated_output(output)