diff --git a/distributed/protocol/__init__.py b/distributed/protocol/__init__.py
index 1e8a08b58a0..b597a4bad44 100644
--- a/distributed/protocol/__init__.py
+++ b/distributed/protocol/__init__.py
@@ -15,6 +15,10 @@
 def _register_numpy():
     from . import numpy
 
+@partial(register_serialization_lazy, "pandas")
+def _register_pandas():
+    from . import pandas
+
 @partial(register_serialization_lazy, "h5py")
 def _register_h5py():
     from . import h5py
diff --git a/distributed/protocol/pandas.py b/distributed/protocol/pandas.py
new file mode 100644
index 00000000000..a6774d59305
--- /dev/null
+++ b/distributed/protocol/pandas.py
@@ -0,0 +1,100 @@
+from __future__ import print_function, division, absolute_import
+
+import pickle
+import sys
+
+import pandas as pd
+
+from .serialize import register_serialization, serialize, deserialize
+
+
+def serialize_pandas_dataframe(df):
+    head = pickle.dumps(df.head(0))
+    headers = []
+    framess = []
+    compression = [None]
+    lengths = [len(head)]
+    for column in df.columns:
+        x = df[column].values
+        header, frames = serialize(x)
+        headers.append(header)
+        framess.append(frames)
+        compression.extend(header.pop('compression', [None] * len(frames)))
+        lengths.extend(header.pop('lengths', [len(f) for f in frames]))
+
+
+    # TODO: avoid if trivial index
+    x = df.index.values
+    index_header, index_frames = serialize(x)
+    compression.extend(index_header.pop('compression',
+                                        [None] * len(index_frames)))
+    lengths.extend(index_header.pop('lengths', [len(f) for f in index_frames]))
+
+    framess.append(index_frames)
+
+    header = {'frame-counts': [len(f) for f in framess],
+              'headers': headers,
+              'index-header': index_header,
+              'lengths': lengths}
+
+    if any(compression):
+        header['compression'] = compression
+
+    return header, [head] + sum(framess, [])
+
+
+def deserialize_pandas_dataframe(header, frames):
+    head = pickle.loads(frames[0])
+    n = 1
+    d = {}
+    for column, h, count in zip(head.columns, header['headers'], header['frame-counts']):
+        x = deserialize(h, frames[n:n + count])
+        n += count
+        d[column] = x
+
+    index = deserialize(header['index-header'], frames[n:])
+
+    df = pd.DataFrame(d, columns=head.columns, index=index)
+    df.index.name = head.index.name
+    return df
+
+
+def serialize_pandas_series(s):
+    value_header, value_frames = serialize(s.values)
+    index_header, index_frames = serialize(s.index)
+
+    compression = []
+    lengths = []
+    for h, f in [(value_header, value_frames), (index_header, index_frames)]:
+        compression.extend(h.pop('compression', [None] * len(f)))
+        lengths.extend(h.pop('lengths', [len(ff) for ff in f]))
+
+    header = {'name': s.name,
+              'value-header': value_header,
+              'index-header': index_header,
+              'n_value_frames': len(value_frames),
+              'index-name': s.index.name,
+              'lengths': lengths}
+
+    if any(compression):
+        header['compression'] = compression
+
+    return header, value_frames + index_frames
+
+
+def deserialize_pandas_series(header, frames):
+    values = deserialize(header['value-header'], frames[:header['n_value_frames']])
+    index = deserialize(header['index-header'], frames[header['n_value_frames']:])
+
+    return pd.Series(values,
+                     name=header['name'],
+                     index=pd.Index(index, name=header['index-name']))
+
+
+register_serialization(pd.DataFrame,
+                       serialize_pandas_dataframe,
+                       deserialize_pandas_dataframe)
+
+register_serialization(pd.Series,
+                       serialize_pandas_series,
+                       deserialize_pandas_series)
diff --git a/distributed/protocol/tests/test_pandas.py b/distributed/protocol/tests/test_pandas.py
index 506f063283e..da189125804 100644
--- a/distributed/protocol/tests/test_pandas.py
+++ b/distributed/protocol/tests/test_pandas.py
@@ -2,6 +2,7 @@
 
 from zlib import crc32
 
+import numpy as np
 import pandas as pd
 import pandas.util.testing as tm
 import pytest
@@ -32,13 +33,16 @@
     pd.DataFrame({'x': [b'a', b'b', b'c']}),
     pd.DataFrame({'x': pd.Categorical(['a', 'b', 'a'], ordered=True)}),
     pd.DataFrame({'x': pd.Categorical(['a', 'b', 'a'], ordered=False)}),
+    pd.Series(np.arange(10000000)),
+    pd.DataFrame({'x': np.arange(10000000)}),
     tm.makeCategoricalIndex(),
     tm.makeCustomDataframe(5, 3),
     tm.makeDataFrame(),
     tm.makeDateIndex(),
     tm.makeMissingDataframe(),
     tm.makeMixedDataFrame(),
-    tm.makeObjectSeries(),
+    pytest.mark.xfail(tm.makeObjectSeries(),
+                      reason='date to timestamp conversion'),
     tm.makePeriodFrame(),
     tm.makeRangeIndex(),
     tm.makeTimeDataFrame(),
@@ -48,10 +52,28 @@
 
 
 @pytest.mark.parametrize('df', dfs)
-def test_dumps_serialize_numpy(df):
+def test_serialize_pandas(df):
     header, frames = serialize(df)
     if 'compression' in header:
         frames = decompress(header, frames)
     df2 = deserialize(header, frames)
 
-    assert_eq(df, df2)
+    if isinstance(df, pd.DataFrame):
+        tm.assert_frame_equal(df, df2)
+    elif isinstance(df, pd.Series):
+        tm.assert_series_equal(df, df2)
+    else:
+        assert_eq(df, df2)
+
+
+@pytest.mark.parametrize('df', dfs)
+def test_dumps_pandas(df):
+    frames = dumps({'x': to_serialize(df)})
+    df2 = loads(frames)['x']
+
+    if isinstance(df, pd.DataFrame):
+        tm.assert_frame_equal(df, df2)
+    elif isinstance(df, pd.Series):
+        tm.assert_series_equal(df, df2)
+    else:
+        assert_eq(df, df2)