diff --git a/.travis.yml b/.travis.yml
index 6127485..b5baf96 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -13,6 +13,7 @@ install:
 - pip install nose nose-parameterized
 - pip install wheel
 - pip install twine
+- pip install pandas
 script:
 - coverage run --source=oandapyV20 setup.py test
 after_success:
diff --git a/oandapyV20/contrib/factories/__init__.py b/oandapyV20/contrib/factories/__init__.py
index 22447f0..542ad7a 100644
--- a/oandapyV20/contrib/factories/__init__.py
+++ b/oandapyV20/contrib/factories/__init__.py
@@ -1,5 +1,9 @@
 from .history import InstrumentsCandlesFactory
+from .csv import CSVFactory
+from .dataframe import DataFrameFactory
 
 __all__ = (
     'InstrumentsCandlesFactory',
+    'CSVFactory',
+    'DataFrameFactory',
 )
diff --git a/oandapyV20/contrib/factories/conv.py b/oandapyV20/contrib/factories/conv.py
new file mode 100644
index 0000000..394661a
--- /dev/null
+++ b/oandapyV20/contrib/factories/conv.py
@@ -0,0 +1,27 @@
+# -*- coding: utf-8 -*-
+from collections import OrderedDict
+
+column_map_tohlcv = OrderedDict([
+    ('time', 'Time'),
+    ('mid:o', 'Open'),
+    ('mid:h', 'High'),
+    ('mid:l', 'Low'),
+    ('mid:c', 'Close'),
+    ('volume', 'Volume')
+])
+
+
+def convrec(r, m):
+    """convrec - convert OANDA candle record.
+
+    return array of values, dynamically constructed, corresponding
+    with config in mapping m.
+    """
+    v = []
+    for keys in [x.split(":") for x in m.keys()]:
+        _v = r.get(keys[0])
+        for k in keys[1:]:
+            _v = _v.get(k)
+        v.append(_v)
+
+    return v
diff --git a/oandapyV20/contrib/factories/csv.py b/oandapyV20/contrib/factories/csv.py
new file mode 100644
index 0000000..de65a93
--- /dev/null
+++ b/oandapyV20/contrib/factories/csv.py
@@ -0,0 +1,28 @@
+# -*- coding: utf-8 -*-
+from .conv import convrec, column_map_tohlcv
+
+
+def CSVFactory(r, conv=convrec, column_map=column_map_tohlcv, delim=","):
+    """CSVFactory - convert candlerecords to CSV strings.
+
+    Dynamically convert candlerecords to CSV strings by the configuration
+    passed by *conf*.
+
+    >>> column_map_tcv = OrderedDict([
+    ...   ('time', 'Time'),
+    ...   ('mid:c', 'Close'),
+    ...   ('volume', 'Volume')
+    ... ])
+    >>> params = {"count": 50,
+    ...           "granularity": "D"}
+    >>> instr = "EUR_USD"
+    >>> r = instruments.InstrumentsCandles(instrument=instr, params=params)
+    >>> api.request(r)
+    >>> for _r in CSVFactory(r.response):
+    >>>     print(_r)
+    >>> for _r in CSVFactory(r.response, column_map=column_map_tcv, delim="|"):
+    >>>     print(_r)
+    """
+    for rec in r.get('candles'):
+        # make all values strings before join
+        yield delim.join([str(x) for x in list(conv(rec, column_map))])
diff --git a/oandapyV20/contrib/factories/dataframe.py b/oandapyV20/contrib/factories/dataframe.py
new file mode 100644
index 0000000..c31a5b1
--- /dev/null
+++ b/oandapyV20/contrib/factories/dataframe.py
@@ -0,0 +1,31 @@
+# -*- coding: utf-8 -*-
+import pandas as pd
+
+from .conv import convrec, column_map_tohlcv
+
+
+def DataFrameFactory(r, column_map=column_map_tohlcv, conv=convrec):
+    """DataFrameFactory - return a dataframe for candles.
+
+    create a DataFrame from candle records by dynamically converting them
+    accoring the column_map config.
+
+    >>> column_map_tcv = OrderedDict([
+    ...   ('time', 'Time'),
+    ...   ('mid:c', 'Close'),
+    ...   ('volume', 'Volume')
+    ... ])
+    >>> params = {"count": 50,
+    ...           "granularity": "D"}
+    >>> instr = "EUR_USD"
+    >>> r = instruments.InstrumentsCandles(instrument=instr, params=params)
+    >>> api.request(r)
+    >>> for _r in DataFrameFactory(r.response):
+    >>>     print(_r.head())
+    >>> for _r in DataFrameFactory(r.response, column_map=column_map_tcv):
+    >>>     print(_r.head())
+    """
+    df = pd.DataFrame([list(conv(_r, column_map)) for _r in r.get('candles')])
+    df.columns = list(column_map.values())
+    df = df.set_index('Time')
+    return df