MAINT: Switch treasury curves from Series to DataFrame.

Instead of using a pandas Series of with dictionaries as the
values treasury curves, use a DataFrame which more naturally fits
the data type of a having a timeseries with mulitple values.

Should allow easier slicing/manipulation of the treasury curves,
e.g. getting 10 year curves would now be:
```
treasury_curves['10year']
```

zipline/finance/risk/risk.py

@@ -187,7 +187,7 @@ def alpha(algorithm_period_return, treasury_period_return,
 def get_treasury_rate(treasury_curves, treasury_duration, day):
     rate = None
 
-    curve = treasury_curves[day]
+    curve = treasury_curves.ix[day]
     # 1month note data begins in 8/2001,
     # so we can use 3month instead.
     idx = TREASURY_DURATIONS.index(treasury_duration)
@@ -238,7 +238,7 @@ def choose_treasury(treasury_curves, start_date, end_date):
     end_day = end_date.replace(hour=0, minute=0, second=0, microsecond=0)
     search_day = None
 
-    if end_day in treasury_curves:
+    if end_day in treasury_curves.index:
         rate = get_treasury_rate(treasury_curves,
                                  treasury_duration,
                                  end_day)

zipline/finance/trading.py

@@ -85,9 +85,9 @@ class TradingEnvironment(object):
         self.benchmark_returns, treasury_curves_map = \
             load(self.bm_symbol)
 
-        self.treasury_curves = pd.Series(treasury_curves_map)
+        self.treasury_curves = pd.DataFrame(treasury_curves_map).T
         if max_date:
-            self.treasury_curves = self.treasury_curves[:max_date]
+            self.treasury_curves = self.treasury_curves.ix[:max_date, :]
 
         self.full_trading_day = datetime.timedelta(hours=6, minutes=30)
         self.early_close_trading_day = datetime.timedelta(hours=3, minutes=30)

zipline/utils/factory.py

@@ -104,7 +104,7 @@ def create_random_simulation_parameters():
             len(treasury_curves) - 1
         )
 
-        start_dt = treasury_curves.keys()[random_index]
+        start_dt = treasury_curves.index[random_index]
         end_dt = start_dt + timedelta(days=365)
 
         now = datetime.utcnow().replace(tzinfo=pytz.utc)