Fix for now removed how kwarg to df.resample.

Support agg() instead, and allow agg_args and agg_kwargs to be passed to
to_timeseries().

Author: aisipos

django_pandas/managers.py

@@ -135,7 +135,8 @@ def to_pivot_table(self, fieldnames=(), verbose=True,
     def to_timeseries(self, fieldnames=(), verbose=True,
                       index=None, storage='wide',
                       values=None, pivot_columns=None, freq=None,
-                      coerce_float=True, rs_kwargs=None):
+                      coerce_float=True, rs_kwargs=None, agg_args=None,
+                      agg_kwargs=None):
         """
         A convenience method for creating a time series DataFrame i.e the
         DataFrame index will be an instance of  DateTime or PeriodIndex
@@ -195,6 +196,12 @@ def to_timeseries(self, fieldnames=(), verbose=True,
         rs_kwargs:  A dictonary of keyword arguments based on the
                     ``pandas.DataFrame.resample`` method
 
+        agg_kwargs:  A dictonary of keyword arguments to send to the
+                    ``pandas.DataFrame.resample().agg()`` method
+
+        agg_args:  A list of positional arguments to send to the
+                    ``pandas.DataFrame.resample().agg()`` method
+
         verbose:  If  this is ``True`` then populate the DataFrame with the
                   human readable versions of any foreign key fields else use
                   the primary keys values else use the actual values set
@@ -233,7 +240,11 @@ def to_timeseries(self, fieldnames=(), verbose=True,
                               values=values)
 
         if freq is not None:
-            df = df.resample(freq, **rs_kwargs)
+            if agg_kwargs is None:
+                agg_kwargs=dict(func='mean')
+            if agg_args is None:
+                agg_args=[]
+            df = df.resample(freq, **rs_kwargs).agg(*agg_args, **agg_kwargs)
 
         return df
 

django_pandas/tests/test_manager.py

@@ -119,10 +119,12 @@ def test_longstorage(self):
 
     def test_resampling(self):
         qs = LongTimeSeries.objects.all()
-        rs_kwargs = {'how': 'sum', 'kind': 'period'}
+        rs_kwargs = {'kind': 'period'}
+        agg_kwargs = {'func': 'sum'}
         df = qs.to_timeseries(index='date_ix', pivot_columns='series_name',
                               values='value', storage='long',
-                              freq='M', rs_kwargs=rs_kwargs)
+                              freq='M', rs_kwargs=rs_kwargs,
+                              agg_kwargs=agg_kwargs)
 
         self.assertEqual([d.month for d in qs.dates('date_ix', 'month')],
                          df.index.month.tolist())