PERF: Improve replace perf

asv_bench/benchmarks/replace.py

@@ -32,6 +32,30 @@ class replace_large_dict(object):
         self.s.replace(self.to_rep, inplace=True)
 
 
+class replace_convert(object):
+    goal_time = 0.5
+
+    def setup(self):
+        self.n = (10 ** 3)
+        self.to_ts = dict(((i, pd.Timestamp(i)) for i in range(self.n)))
+        self.to_td = dict(((i, pd.Timedelta(i)) for i in range(self.n)))
+        self.s = Series(np.random.randint(self.n, size=(10 ** 3)))
+        self.df = DataFrame({'A': np.random.randint(self.n, size=(10 ** 3)),
+                             'B': np.random.randint(self.n, size=(10 ** 3))})
+
+    def time_replace_series_timestamp(self):
+        self.s.replace(self.to_ts)
+
+    def time_replace_series_timedelta(self):
+        self.s.replace(self.to_td)
+
+    def time_replace_frame_timestamp(self):
+        self.df.replace(self.to_ts)
+
+    def time_replace_frame_timedelta(self):
+        self.df.replace(self.to_td)
+
+
 class replace_replacena(object):
     goal_time = 0.2
 

doc/source/whatsnew/v0.19.2.txt

@@ -21,6 +21,7 @@ Highlights include:
 Performance Improvements
 ~~~~~~~~~~~~~~~~~~~~~~~~
 
+- Improved performance of ``.replace()`` (:issue:`12745`)
 
 .. _whatsnew_0192.bug_fixes:
 

pandas/core/generic.py

@@ -3477,20 +3477,27 @@ class NDFrame(PandasObject):
                     res = self if inplace else self.copy()
                     for c, src in compat.iteritems(to_replace):
                         if c in value and c in self:
+                            # object conversion is handled in
+                            # series.replace which is called recursivelly
                             res[c] = res[c].replace(to_replace=src,
                                                     value=value[c],
-                                                    inplace=False, regex=regex)
+                                                    inplace=False,
+                                                    regex=regex)
                     return None if inplace else res
 
                 # {'A': NA} -> 0
                 elif not is_list_like(value):
-                    for k, src in compat.iteritems(to_replace):
-                        if k in self:
-                            new_data = new_data.replace(to_replace=src,
-                                                        value=value,
-                                                        filter=[k],
-                                                        inplace=inplace,
-                                                        regex=regex)
+                    keys = [(k, src) for k, src in compat.iteritems(to_replace)
+                            if k in self]
+                    keys_len = len(keys) - 1
+                    for i, (k, src) in enumerate(keys):
+                        convert = i == keys_len
+                        new_data = new_data.replace(to_replace=src,
+                                                    value=value,
+                                                    filter=[k],
+                                                    inplace=inplace,
+                                                    regex=regex,
+                                                    convert=convert)
                 else:
                     raise TypeError('value argument must be scalar, dict, or '
                                     'Series')

pandas/core/internals.py

@@ -622,7 +622,6 @@ class Block(PandasObject):
 
         original_to_replace = to_replace
         mask = isnull(self.values)
-
         # try to replace, if we raise an error, convert to ObjectBlock and
         # retry
         try:
@@ -1795,13 +1794,14 @@ class BoolBlock(NumericBlock):
         return issubclass(value.dtype.type, np.bool_)
 
     def replace(self, to_replace, value, inplace=False, filter=None,
-                regex=False, mgr=None):
+                regex=False, convert=True, mgr=None):
         to_replace_values = np.atleast_1d(to_replace)
         if not np.can_cast(to_replace_values, bool):
             return self
         return super(BoolBlock, self).replace(to_replace, value,
                                               inplace=inplace, filter=filter,
-                                              regex=regex, mgr=mgr)
+                                              regex=regex, convert=convert,
+                                              mgr=mgr)
 
 
 class ObjectBlock(Block):
@@ -3214,6 +3214,7 @@ class BlockManager(PandasObject):
         masks = [comp(s) for i, s in enumerate(src_list)]
 
         result_blocks = []
+        src_len = len(src_list) - 1
         for blk in self.blocks:
 
             # its possible to get multiple result blocks here
@@ -3223,8 +3224,9 @@ class BlockManager(PandasObject):
                 new_rb = []
                 for b in rb:
                     if b.dtype == np.object_:
+                        convert = i == src_len
                         result = b.replace(s, d, inplace=inplace, regex=regex,
-                                           mgr=mgr)
+                                           mgr=mgr, convert=convert)
                         new_rb = _extend_blocks(result, new_rb)
                     else:
                         # get our mask for this element, sized to this
@@ -4788,7 +4790,12 @@ def _putmask_smart(v, m, n):
 
     # change the dtype
     dtype, _ = _maybe_promote(n.dtype)
-    nv = v.astype(dtype)
+
+    if is_extension_type(v.dtype) and is_object_dtype(dtype):
+        nv = v.get_values(dtype)
+    else:
+        nv = v.astype(dtype)
+
     try:
         nv[m] = n[m]
     except ValueError: