REF: use fused types for mode (pandas-dev#46089)

Author: jbrockmendel

pandas/_libs/hashtable_func_helper.pxi.in

@@ -240,63 +240,6 @@ cdef ismember_{{dtype}}(const {{dtype}}_t[:] arr, const {{dtype}}_t[:] values):
 # Mode Computations
 # ----------------------------------------------------------------------
 
-
-@cython.wraparound(False)
-@cython.boundscheck(False)
-{{if dtype == 'object'}}
-cdef mode_{{dtype}}(ndarray[{{dtype}}] values, bint dropna):
-{{else}}
-cdef mode_{{dtype}}(const {{dtype}}_t[:] values, bint dropna):
-{{endif}}
-    cdef:
-        {{if dtype == 'object'}}
-        ndarray[{{dtype}}] keys
-        ndarray[{{dtype}}] modes
-        {{else}}
-        {{dtype}}_t[:] keys
-        ndarray[{{dtype}}_t] modes
-        {{endif}}
-        int64_t[:] counts
-        int64_t count, max_count = -1
-        Py_ssize_t k, j = 0
-
-    keys, counts = value_count_{{dtype}}(values, dropna)
-
-    {{if dtype == 'object'}}
-    modes = np.empty(len(keys), dtype=np.object_)
-    {{else}}
-    modes = np.empty(len(keys), dtype=np.{{dtype}})
-    {{endif}}
-
-    {{if dtype != 'object'}}
-    with nogil:
-        for k in range(len(keys)):
-            count = counts[k]
-            if count == max_count:
-                j += 1
-            elif count > max_count:
-                max_count = count
-                j = 0
-            else:
-                continue
-
-            modes[j] = keys[k]
-    {{else}}
-    for k in range(len(keys)):
-        count = counts[k]
-        if count == max_count:
-            j += 1
-        elif count > max_count:
-            max_count = count
-            j = 0
-        else:
-            continue
-
-        modes[j] = keys[k]
-    {{endif}}
-
-    return modes[:j + 1]
-
 {{endfor}}
 
 
@@ -414,40 +357,51 @@ cpdef ismember(ndarray[htfunc_t] arr, ndarray[htfunc_t] values):
         raise TypeError(values.dtype)
 
 
-cpdef mode(ndarray[htfunc_t] values, bint dropna):
-    if htfunc_t is object:
-        return mode_object(values, dropna)
+@cython.wraparound(False)
+@cython.boundscheck(False)
+def mode(ndarray[htfunc_t] values, bint dropna):
+    # TODO(cython3): use const htfunct_t[:]
 
-    elif htfunc_t is int8_t:
-        return mode_int8(values, dropna)
-    elif htfunc_t is int16_t:
-        return mode_int16(values, dropna)
-    elif htfunc_t is int32_t:
-        return mode_int32(values, dropna)
-    elif htfunc_t is int64_t:
-        return mode_int64(values, dropna)
+    cdef:
+        ndarray[htfunc_t] keys
+        ndarray[htfunc_t] modes
 
-    elif htfunc_t is uint8_t:
-        return mode_uint8(values, dropna)
-    elif htfunc_t is uint16_t:
-        return mode_uint16(values, dropna)
-    elif htfunc_t is uint32_t:
-        return mode_uint32(values, dropna)
-    elif htfunc_t is uint64_t:
-        return mode_uint64(values, dropna)
+        int64_t[:] counts
+        int64_t count, max_count = -1
+        Py_ssize_t nkeys, k, j = 0
 
-    elif htfunc_t is float64_t:
-        return mode_float64(values, dropna)
-    elif htfunc_t is float32_t:
-        return mode_float32(values, dropna)
+    keys, counts = value_count(values, dropna)
+    nkeys = len(keys)
 
-    elif htfunc_t is complex128_t:
-        return mode_complex128(values, dropna)
-    elif htfunc_t is complex64_t:
-        return mode_complex64(values, dropna)
+    modes = np.empty(nkeys, dtype=values.dtype)
 
+    if htfunc_t is not object:
+        with nogil:
+            for k in range(nkeys):
+                count = counts[k]
+                if count == max_count:
+                    j += 1
+                elif count > max_count:
+                    max_count = count
+                    j = 0
+                else:
+                    continue
+
+                modes[j] = keys[k]
     else:
-        raise TypeError(values.dtype)
+        for k in range(nkeys):
+            count = counts[k]
+            if count == max_count:
+                j += 1
+            elif count > max_count:
+                max_count = count
+                j = 0
+            else:
+                continue
+
+            modes[j] = keys[k]
+
+    return modes[:j + 1]
 
 
 {{py: