BUG: don't mangle NaN-float-values and pd.NaT (GH 22295)

it is more or less the clean-up after PR pandas-dev#21904 and PR pandas-dev#22207, the underlying hash-map handles all cases correctly out-of-the box and thus no special handling is needed.

pandas/_libs/hashtable_class_helper.pxi.in

@@ -470,7 +470,6 @@ cdef class {{name}}HashTable(HashTable):
            int ret = 0
            {{dtype}}_t val
            khiter_t k
-           bint seen_na = 0
            {{name}}Vector uniques = {{name}}Vector()
            {{name}}VectorData *ud
 
@@ -479,30 +478,13 @@ cdef class {{name}}HashTable(HashTable):
         with nogil:
             for i in range(n):
                 val = values[i]
-                {{if float_group}}
-                if val == val:
-                    k = kh_get_{{dtype}}(self.table, val)
-                    if k == self.table.n_buckets:
-                        kh_put_{{dtype}}(self.table, val, &ret)
-                        if needs_resize(ud):
-                            with gil:
-                                uniques.resize()
-                        append_data_{{dtype}}(ud, val)
-                elif not seen_na:
-                    seen_na = 1
-                    if needs_resize(ud):
-                        with gil:
-                            uniques.resize()
-                    append_data_{{dtype}}(ud, NAN)
-                {{else}}
                 k = kh_get_{{dtype}}(self.table, val)
                 if k == self.table.n_buckets:
                     kh_put_{{dtype}}(self.table, val, &ret)
                     if needs_resize(ud):
                         with gil:
                             uniques.resize()
                     append_data_{{dtype}}(ud, val)
-                {{endif}}
         return uniques.to_array()
 
 {{endfor}}
@@ -854,19 +836,11 @@ cdef class PyObjectHashTable(HashTable):
         for i in range(n):
             val = values[i]
             hash(val)
+            k = kh_get_pymap(self.table, <PyObject*>val)
+            if k == self.table.n_buckets:
+                kh_put_pymap(self.table, <PyObject*>val, &ret)
+                uniques.append(val)
 
-            # `val is None` below is exception to prevent mangling of None and
-            # other NA values; note however that other NA values (ex: pd.NaT
-            # and np.nan) will still get mangled, so many not be a permanent
-            # solution; see GH 20866
-            if not checknull(val) or val is None:
-                k = kh_get_pymap(self.table, <PyObject*>val)
-                if k == self.table.n_buckets:
-                    kh_put_pymap(self.table, <PyObject*>val, &ret)
-                    uniques.append(val)
-            elif not seen_na:
-                seen_na = 1
-                uniques.append(nan)
 
         return uniques.to_array()