diff --git a/README.rst b/README.rst
index fa21005..4dc237a 100644
--- a/README.rst
+++ b/README.rst
@@ -415,6 +415,11 @@ Development
   with values other than the mode. (#144)
 
 
+1.6.1 (2018-04-16)
+******************
+* Preserve input data types when no transform is supplied (#138)
+
+
 1.6.0 (2017-10-28)
 ******************
 * Add column name to exception during fit/transform (#110).
@@ -504,3 +509,4 @@ Other contributors:
 * Ritesh Agrawal (@ragrawal)
 * Vitaley Zaretskey (@vzaretsk)
 * Zac Stewart (@zacstewart)
+* Timothy Sweetser (@hacktuarial)
diff --git a/sklearn_pandas/__init__.py b/sklearn_pandas/__init__.py
index 6d33c3e..fe3d189 100644
--- a/sklearn_pandas/__init__.py
+++ b/sklearn_pandas/__init__.py
@@ -1,4 +1,4 @@
-__version__ = '1.6.0'
+__version__ = '1.6.1'
 
 from .dataframe_mapper import DataFrameMapper  # NOQA
 from .cross_validation import cross_val_score, GridSearchCV, RandomizedSearchCV  # NOQA
diff --git a/sklearn_pandas/dataframe_mapper.py b/sklearn_pandas/dataframe_mapper.py
index 596aa76..2c92d94 100644
--- a/sklearn_pandas/dataframe_mapper.py
+++ b/sklearn_pandas/dataframe_mapper.py
@@ -315,6 +315,15 @@ def transform(self, X):
             stacked = np.hstack(extracted)
 
         if self.df_out:
+            # output different data types, if appropriate
+            dtypes = []
+            for ex in extracted:
+                if isinstance(ex, np.ndarray) or sparse.issparse(ex):
+                    dtypes += [ex.dtype] * ex.shape[1]
+                elif isinstance(ex, pd.DataFrame):
+                    dtypes += list(ex.dtypes)
+                else:
+                    raise TypeError(type(ex))
             # if no rows were dropped preserve the original index,
             # otherwise use a new integer one
             no_rows_dropped = len(X) == len(stacked)
@@ -323,8 +332,10 @@ def transform(self, X):
             else:
                 index = None
 
-            return pd.DataFrame(stacked,
-                                columns=self.transformed_names_,
-                                index=index)
+            df_out = pd.DataFrame(dict(zip(
+                self.transformed_names_,
+                [pd.Series(stacked[:, i], index=index, dtype=dtypes[i])
+                 for i in range(stacked.shape[1])])))
+            return df_out[self.transformed_names_]  # preserve order
         else:
             return stacked
diff --git a/tests/test_dataframe_mapper.py b/tests/test_dataframe_mapper.py
index 75da4fd..e55b678 100644
--- a/tests/test_dataframe_mapper.py
+++ b/tests/test_dataframe_mapper.py
@@ -829,3 +829,17 @@ def test_direct_cross_validation(iris_dataframe):
     scores = sklearn_cv_score(pipeline, data, labels)
     assert scores.mean() > 0.96
     assert (scores.std() * 2) < 0.04
+
+
+def test_heterogeneous_output_types_input_df(complex_dataframe):
+    """
+    Modify feat1, but pass feat2 and target (different types!)
+        through unmodified. This fails if input_df == False
+    """
+    complex_dataframe['feat1'] = complex_dataframe['feat1'].astype(float)
+    M = DataFrameMapper([
+        (['feat1'], StandardScaler())
+        ], input_df=True, df_out=True, default=None)
+    expected_dtypes = complex_dataframe.dtypes
+    actual_dtypes = M.fit_transform(complex_dataframe).dtypes
+    assert (expected_dtypes == actual_dtypes).all()