Simple stub of group_any

pandas/_libs/groupby_helper.pxi.in

@@ -791,3 +791,27 @@ def group_cummax_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
  out[i, j] = mval
 
 {{endfor}}
+
+@cython.boundscheck(False)
+@cython.wraparound(False)
+def group_any(ndarray[uint8_t, ndim=2] out,
+ ndarray[int64_t] counts,
+ ndarray[:, :] values,
+ ndarray[int64_t] labels,
+ bint skipna):
+ cdef:
+ Py_ssize_t i, N
+ ndarray[uint8_t] mask
+
+ N, _ = (<object> labels).shape
+
+ out = np.zeros_like(out)
+ mask = values[:, 0].astype(np.bool)
+
+ for i in range(N):
+ lab = labels[i]
+ if lab < 0:
+ continue
+
+ if mask[lab]:
+ out[lab, 0] = 1