diff --git a/tests/test_assets.py b/tests/test_assets.py
index 66f8248b..94569080 100644
--- a/tests/test_assets.py
+++ b/tests/test_assets.py
@@ -718,3 +718,25 @@ class AssetFinderTestCase(TestCase):
 
         # No contracts exist after 12/14/2015, so we should get none
         self.assertIsNone(finder.lookup_future_by_expiration('AD', dt, jan_16))
+
+    def test_map_identifier_list_to_sids(self):
+
+        # Build an empty finder and some Assets
+        dt = pd.Timestamp('2014-01-01', tz='UTC')
+        finder = AssetFinder()
+        asset1 = Equity(1, symbol="AAPL")
+        asset2 = Equity(2, symbol="GOOG")
+        asset200 = Future(200, symbol="CLK15")
+        asset201 = Future(201, symbol="CLM15")
+
+        # Check for correct mapping and types
+        pre_map = [asset1, asset2, asset200, asset201]
+        post_map = finder.map_identifier_list_to_sids(pre_map, dt)
+        self.assertListEqual([1, 2, 200, 201], post_map)
+        for sid in post_map:
+            self.assertIsInstance(sid, int)
+
+        # Change order and check mapping again
+        pre_map = [asset201, asset2, asset200, asset1]
+        post_map = finder.map_identifier_list_to_sids(pre_map, dt)
+        self.assertListEqual([201, 2, 200, 1], post_map)
diff --git a/tests/test_history.py b/tests/test_history.py
index a29ef469..5a515e23 100644
--- a/tests/test_history.py
+++ b/tests/test_history.py
@@ -437,7 +437,7 @@ def handle_data(context, data):
 
         _, df = factory.create_test_df_source(sim_params)
         df = df.astype(np.float64)
-        source = DataFrameSource(df, sids=[0])
+        source = DataFrameSource(df)
 
         test_algo = TradingAlgorithm(
             script=algo_text,
diff --git a/tests/test_sources.py b/tests/test_sources.py
index 3664acdd..2e2c7c23 100644
--- a/tests/test_sources.py
+++ b/tests/test_sources.py
@@ -27,6 +27,7 @@ from zipline.sources import (DataFrameSource,
                              RandomWalkSource)
 from zipline.utils import tradingcalendar as calendar_nyse
 from zipline.finance.trading import with_environment
+from zipline.assets import AssetFinder
 
 
 class TestDataFrameSource(TestCase):
@@ -43,7 +44,7 @@ class TestDataFrameSource(TestCase):
 
     def test_df_sid_filtering(self):
         _, df = factory.create_test_df_source()
-        source = DataFrameSource(df, sids=[0])
+        source = DataFrameSource(df)
         assert 1 not in [event.sid for event in source], \
             "DataFrameSource should only stream selected sid 0, not sid 1."
 
@@ -63,8 +64,8 @@ class TestDataFrameSource(TestCase):
             self.assertTrue(isinstance(event['volume'], int))
             self.assertTrue(isinstance(event['arbitrary'], float))
 
-    @with_environment()
-    def test_yahoo_bars_to_panel_source(self, env=None):
+    def test_yahoo_bars_to_panel_source(self):
+        finder = AssetFinder()
         stocks = ['AAPL', 'GE']
         start = pd.datetime(1993, 1, 1, 0, 0, 0, 0, pytz.utc)
         end = pd.datetime(2002, 1, 1, 0, 0, 0, 0, pytz.utc)
@@ -75,10 +76,15 @@ class TestDataFrameSource(TestCase):
 
         check_fields = ['sid', 'open', 'high', 'low', 'close',
                         'volume', 'price']
-        source = DataPanelSource(data)
+
+        copy_panel = data.copy()
+        copy_panel.items = finder.map_identifier_list_to_sids(
+            data.items, data.major_axis[0]
+        )
+        source = DataPanelSource(copy_panel)
         sids = [
             asset.sid for asset in
-            [env.asset_finder.lookup_symbol(symbol, as_of_date=end)
+            [finder.lookup_symbol(symbol, as_of_date=end)
              for symbol in stocks]
         ]
         stocks_iter = cycle(sids)
diff --git a/tests/test_transforms_talib.py b/tests/test_transforms_talib.py
index 5b9f50a1..203d0190 100644
--- a/tests/test_transforms_talib.py
+++ b/tests/test_transforms_talib.py
@@ -98,7 +98,7 @@ class TestTALIB(TestCase):
         zipline_transforms = [ta.MA(timeperiod=10),
                               ta.MA(timeperiod=25)]
         talib_fn = talib.abstract.MA
-        algo = TALIBAlgorithm(talib=zipline_transforms)
+        algo = TALIBAlgorithm(talib=zipline_transforms, identifiers=[0])
         algo.run(self.source)
         # Test if computed values match those computed by pandas rolling mean.
         sid = 0
diff --git a/zipline/algorithm.py b/zipline/algorithm.py
index 375793fc..41a4aa65 100644
--- a/zipline/algorithm.py
+++ b/zipline/algorithm.py
@@ -39,7 +39,6 @@ from zipline.errors import (
     UnsupportedCommissionModel,
     UnsupportedOrderParameters,
     UnsupportedSlippageModel,
-    SidNotFound,
 )
 
 from zipline.finance.trading import TradingEnvironment
@@ -461,10 +460,22 @@ class TradingAlgorithm(object):
  __init__().""", UserWarning)
                 overwrite_sim_params = False
         elif isinstance(source, pd.DataFrame):
-            # if DataFrame provided, wrap in DataFrameSource
-            source = DataFrameSource(source)
+            # if DataFrame provided, map columns to sids and wrap
+            # in DataFrameSource
+            copy_frame = source.copy()
+            copy_frame.columns = self.asset_finder.map_identifier_list_to_sids(
+                source.columns, source.index[0]
+            )
+            source = DataFrameSource(copy_frame)
+
         elif isinstance(source, pd.Panel):
-            source = DataPanelSource(source)
+            # If Panel provided, map items to sids and wrap
+            # in DataPanelSource
+            copy_panel = source.copy()
+            copy_panel.items = self.asset_finder.map_identifier_list_to_sids(
+                source.items, source.major_axis[0]
+            )
+            source = DataPanelSource(copy_panel)
 
         if isinstance(source, list):
             self.set_sources(source)
diff --git a/zipline/assets/assets.py b/zipline/assets/assets.py
index c14c93f5..51d592cb 100644
--- a/zipline/assets/assets.py
+++ b/zipline/assets/assets.py
@@ -18,6 +18,7 @@ from itertools import chain
 from numbers import Integral
 import numpy as np
 import operator
+import warnings
 
 from logbook import Logger
 import pandas as pd
@@ -531,6 +532,30 @@ class AssetFinder(object):
             self._lookup_generic_scalar(obj, as_of_date, matches, missing)
         return matches, missing
 
+    def map_identifier_list_to_sids(self, index, as_of_date):
+        """
+        This method is for use in sanitizing a user's DataFrame inputs.
+        Takes the given indices, inserts them in to the AssetFinder as
+        identifiers, rebuilds the Assets, and returns a new object that
+        contains the sids of the given identifiers.
+
+        :param index: The index to be mapped
+        :return: The new index of sids
+        """
+        # Populate the caches with the given indices
+        self.consume_identifiers(index)
+        self.populate_cache()
+
+        # Find all of the newly built assets corresponding to the indices
+        found, missing = self.lookup_generic(index, as_of_date)
+
+        # Handle missing assets
+        if len(missing) > 0:
+            warnings.warn("Missing assets for identifiers: " + missing)
+
+        # Return a list of the sids of the found assets
+        return [asset.sid for asset in found]
+
     def insert_metadata(self, identifier, **kwargs):
         """
         Inserts the given metadata kwargs to the entry for the given
diff --git a/zipline/examples/pairtrade.py b/zipline/examples/pairtrade.py
index ca71d8f9..ffb37d53 100755
--- a/zipline/examples/pairtrade.py
+++ b/zipline/examples/pairtrade.py
@@ -23,7 +23,6 @@ import pytz
 from zipline.algorithm import TradingAlgorithm
 from zipline.transforms import batch_transform
 from zipline.utils.factory import load_from_yahoo
-from zipline.sources.data_frame_source import DataFrameSource
 
 
 @batch_transform
@@ -121,10 +120,9 @@ if __name__ == '__main__':
     end = datetime(2002, 1, 1, 0, 0, 0, 0, pytz.utc)
     data = load_from_yahoo(stocks=['PEP', 'KO'], indexes={},
                            start=start, end=end)
-    source = DataFrameSource(data)
 
     pairtrade = Pairtrade()
-    results = pairtrade.run(source)
+    results = pairtrade.run(data)
     data['spreads'] = np.nan
 
     ax1 = plt.subplot(211)
diff --git a/zipline/sources/data_frame_source.py b/zipline/sources/data_frame_source.py
index d42fdf5a..77241812 100644
--- a/zipline/sources/data_frame_source.py
+++ b/zipline/sources/data_frame_source.py
@@ -18,7 +18,6 @@ Tools to generate data sources.
 """
 import numpy as np
 import pandas as pd
-import datetime
 
 from zipline.gens.utils import hash_args
 
@@ -41,19 +40,13 @@ class DataFrameSource(DataSource):
     @with_environment()
     def __init__(self, data, env=None, **kwargs):
         assert isinstance(data.index, pd.tseries.index.DatetimeIndex)
-
+        assert isinstance(data.columns, pd.Int64Index)
+        # TODO is ffilling correct/necessary?
+        # Forward fill prices
         self.data = data.fillna(method='ffill')
         # Unpack config dictionary with default values.
         self.start = kwargs.get('start', self.data.index[0])
         self.end = kwargs.get('end', self.data.index[-1])
-
-        # Remap sids based on the trading environment
-        env.update_asset_finder(
-            identifiers=kwargs.get('sids', self.data.columns)
-        )
-        self.data.columns, _ = env.asset_finder.lookup_generic(
-            self.data.columns, datetime.datetime.now()
-        )
         self.sids = self.data.columns
 
         # Hash_value for downstream sorting.
@@ -118,20 +111,15 @@ class DataPanelSource(DataSource):
     @with_environment()
     def __init__(self, data, env=None, **kwargs):
         assert isinstance(data.major_axis, pd.tseries.index.DatetimeIndex)
-
+        # Only accept integer SIDs as the items of the Panel
+        assert isinstance(data.items, pd.Int64Index)
+        # TODO is ffilling correct/necessary?
+        # forward fill with volumes of 0
         self.data = data.fillna(value={'volume': 0})
         self.data = self.data.fillna(method='ffill')
         # Unpack config dictionary with default values.
         self.start = kwargs.get('start', self.data.major_axis[0])
         self.end = kwargs.get('end', self.data.major_axis[-1])
-
-        # Remap sids based on the trading environment
-        env.update_asset_finder(
-            identifiers=kwargs.get('sids', self.data.items)
-        )
-        self.data.items, _ = env.asset_finder.lookup_generic(
-            self.data.items, datetime.datetime.now()
-        )
         self.sids = self.data.items
 
         # Hash_value for downstream sorting.