diff --git a/catalyst/exchange/utils/exchange_utils.py b/catalyst/exchange/utils/exchange_utils.py
index 3366c3965..b88a44836 100644
--- a/catalyst/exchange/utils/exchange_utils.py
+++ b/catalyst/exchange/utils/exchange_utils.py
@@ -718,9 +718,12 @@ def save_asset_data(folder, df, decimals=8):
 
 def forward_fill_df_if_needed(df, periods):
     df = df.reindex(periods)
-    df['volume'] = df['volume'].fillna(0.0)# volume should always be 0 (if there were no trades in this interval)
-    df['close'] = df.fillna(method='pad')  # ie pull the last close into this close
-    # now copy the close that was pulled down from the last timestep into this row, across into o/h/l
+    # volume should always be 0 (if there were no trades in this interval)
+    df['volume'] = df['volume'].fillna(0.0)
+    # ie pull the last close into this close
+    df['close'] = df.fillna(method='pad')
+    # now copy the close that was pulled down from the last timestep
+    # into this row, across into o/h/l
     df['open'] = df['open'].fillna(df['close'])
     df['low'] = df['low'].fillna(df['close'])
     df['high'] = df['high'].fillna(df['close'])
diff --git a/tests/exchange/test_exchange_utils.py b/tests/exchange/test_exchange_utils.py
index deebc9f15..ae5c07dc6 100644
--- a/tests/exchange/test_exchange_utils.py
+++ b/tests/exchange/test_exchange_utils.py
@@ -1,7 +1,8 @@
-from catalyst.exchange.utils.exchange_utils import transform_candles_to_df, forward_fill_df_if_needed, get_candles_df
+from catalyst.exchange.utils.exchange_utils import transform_candles_to_df, \
+    forward_fill_df_if_needed, get_candles_df
 
 from catalyst.testing.fixtures import WithLogger, ZiplineTestCase
-from pandas import Timestamp, Series, DataFrame
+from pandas import Timestamp, DataFrame
 
 import numpy as np
 
@@ -19,52 +20,76 @@ def test_transform_candles_to_series(self):
 
         candles = [{'high': 595, 'volume': 10, 'low': 594,
                     'close': 595, 'open': 594,
-                    'last_traded': Timestamp('2018-03-01 09:45:00+0000', tz='UTC')},
+                    'last_traded': Timestamp('2018-03-01 09:45:00+0000',
+                                             tz='UTC')
+                    },
                    {'high': 594, 'volume': 108, 'low': 592,
                     'close': 593, 'open': 592,
-                    'last_traded': Timestamp('2018-03-01 09:50:00+0000', tz='UTC')}]
+                    'last_traded': Timestamp('2018-03-01 09:50:00+0000',
+                                             tz='UTC')
+                    }]
 
         expected = [{'high': 595.0, 'volume': 10.0, 'low': 594.0,
-                    'close': 595.0, 'open': 594.0,
-                    'last_traded': Timestamp('2018-03-01 09:45:00+0000', tz='UTC')},
-                   {'high': 594.0, 'volume': 108.0, 'low': 592.0,
-                    'close': 593.0, 'open': 592.0,
-                    'last_traded': Timestamp('2018-03-01 09:50:00+0000', tz='UTC')},
-                   {'high': 593.0, 'volume': 0.0, 'low': 593.0,
-                    'close': 593.0, 'open': 593.0,
-                    'last_traded': Timestamp('2018-03-01 09:55:00+0000', tz='UTC')}
-                   ]
+                     'close': 595.0, 'open': 594.0,
+                     'last_traded': Timestamp('2018-03-01 09:45:00+0000',
+                                              tz='UTC')
+                     },
+                    {'high': 594.0, 'volume': 108.0, 'low': 592.0,
+                     'close': 593.0, 'open': 592.0,
+                     'last_traded': Timestamp('2018-03-01 09:50:00+0000',
+                                              tz='UTC')
+                     },
+                    {'high': 593.0, 'volume': 0.0, 'low': 593.0,
+                     'close': 593.0, 'open': 593.0,
+                     'last_traded': Timestamp('2018-03-01 09:55:00+0000',
+                                              tz='UTC')
+                     }]
 
         periods = [Timestamp('2018-03-01 09:45:00+0000', tz='UTC'),
                    Timestamp('2018-03-01 09:50:00+0000', tz='UTC'),
                    Timestamp('2018-03-01 09:55:00+0000', tz='UTC')]
 
-        observed_df = forward_fill_df_if_needed(transform_candles_to_df(candles), periods)
+        observed_df = forward_fill_df_if_needed(
+            transform_candles_to_df(candles),
+            periods)
         expected_df = transform_candles_to_df(expected)
 
         assert (expected_df.equals(observed_df))
 
         for field in ['volume', 'open', 'close', 'high', 'low']:
-            assert(self.get_specific_field_from_df(observed_df, field, asset).equals(
-                get_candles_df({asset:candles}, field, '5T', 3, end_dt=periods[2])))
+            field_dt = self.get_specific_field_from_df(observed_df,
+                                                       field,
+                                                       asset)
+            assert (field_dt.equals(get_candles_df({asset: candles},
+                                                   field, '5T', 3,
+                                                   end_dt=periods[2])))
 
         candles = [{'high': 595, 'volume': 10, 'low': 594,
                     'close': 595, 'open': 594,
-                    'last_traded': Timestamp('2018-03-01 09:45:00+0000', tz='UTC')},
+                    'last_traded': Timestamp('2018-03-01 09:45:00+0000',
+                                             tz='UTC')
+                    },
                    {'high': 594, 'volume': 108, 'low': 592,
                     'close': 593, 'open': 592,
-                    'last_traded': Timestamp('2018-03-01 09:55:00+0000', tz='UTC')}]
+                    'last_traded': Timestamp('2018-03-01 09:55:00+0000',
+                                             tz='UTC')
+                    }]
 
         expected = [{'high': 595.0, 'volume': 10.0, 'low': 594.0,
                      'close': 595.0, 'open': 594.0,
-                     'last_traded': Timestamp('2018-03-01 09:45:00+0000', tz='UTC')},
+                     'last_traded': Timestamp('2018-03-01 09:45:00+0000',
+                                              tz='UTC')
+                     },
                     {'high': 595.0, 'volume': 0.0, 'low': 595.0,
                      'close': 595.0, 'open': 595.0,
-                     'last_traded': Timestamp('2018-03-01 09:50:00+0000', tz='UTC')},
+                     'last_traded': Timestamp('2018-03-01 09:50:00+0000',
+                                              tz='UTC')
+                     },
                     {'high': 594.0, 'volume': 108.0, 'low': 592.0,
                      'close': 593.0, 'open': 592.0,
-                     'last_traded': Timestamp('2018-03-01 09:55:00+0000', tz='UTC')}
-                    ]
+                     'last_traded': Timestamp('2018-03-01 09:55:00+0000',
+                                              tz='UTC')
+                     }]
 
         df = transform_candles_to_df(candles)
         observed_df = forward_fill_df_if_needed(df, periods)
@@ -72,26 +97,39 @@ def test_transform_candles_to_series(self):
         assert (transform_candles_to_df(expected).equals(observed_df))
 
         for field in ['volume', 'open', 'close', 'high', 'low']:
-            assert(self.get_specific_field_from_df(observed_df, field, asset).equals(
-                get_candles_df({asset:candles}, field, '5T', 3, end_dt=periods[2])))
+            field_dt = self.get_specific_field_from_df(observed_df,
+                                                       field,
+                                                       asset)
+            assert(field_dt.equals(get_candles_df({asset: candles},
+                                                  field, '5T', 3,
+                                                  end_dt=periods[2])))
 
         candles = [{'high': 595, 'volume': 10, 'low': 594,
                     'close': 595, 'open': 594,
-                    'last_traded': Timestamp('2018-03-01 09:50:00+0000', tz='UTC')},
+                    'last_traded': Timestamp('2018-03-01 09:50:00+0000',
+                                             tz='UTC')
+                    },
                    {'high': 594, 'volume': 108, 'low': 592,
                     'close': 593, 'open': 592,
-                    'last_traded': Timestamp('2018-03-01 09:55:00+0000', tz='UTC')}]
+                    'last_traded': Timestamp('2018-03-01 09:55:00+0000',
+                                             tz='UTC')
+                    }]
 
         expected = [{'high': np.NaN, 'volume': 0.0, 'low': np.NaN,
                      'close': np.NaN, 'open': np.NaN,
-                     'last_traded': Timestamp('2018-03-01 09:45:00+0000', tz='UTC')},
+                     'last_traded': Timestamp('2018-03-01 09:45:00+0000',
+                                              tz='UTC')
+                     },
                     {'high': 595, 'volume': 10, 'low': 594,
                      'close': 595, 'open': 594,
-                     'last_traded': Timestamp('2018-03-01 09:50:00+0000', tz='UTC')},
+                     'last_traded': Timestamp('2018-03-01 09:50:00+0000',
+                                              tz='UTC')
+                     },
                     {'high': 594, 'volume': 108, 'low': 592,
                      'close': 593, 'open': 592,
-                     'last_traded': Timestamp('2018-03-01 09:55:00+0000', tz='UTC')}
-                    ]
+                     'last_traded': Timestamp('2018-03-01 09:55:00+0000',
+                                              tz='UTC')
+                     }]
 
         df = transform_candles_to_df(candles)
         observed_df = forward_fill_df_if_needed(df, periods)
@@ -99,7 +137,11 @@ def test_transform_candles_to_series(self):
         assert (transform_candles_to_df(expected).equals(observed_df))
         # Not the same due to dropna - commenting out for now
         """
-        for field in ['volume', 'open', 'close', 'high', 'low']:
-            assert(self.get_specific_field_from_df(observed_df, field, asset).equals(
-                get_candles_df({asset:candles}, field, '5T', 3, end_dt=periods[2])))
-        """
\ No newline at end of file
+                for field in ['volume', 'open', 'close', 'high', 'low']:
+            field_dt = self.get_specific_field_from_df(observed_df,
+                                                       field,
+                                                       asset)
+            assert(field_dt.equals(get_candles_df({asset:candles},
+                                                  field, '5T', 3,
+                                                  end_dt=periods[2])))
+        """