ENH: add fill_value to resample as per GH3715

Author: nchmura4

pandas/core/generic.py

@@ -4131,7 +4131,7 @@ def between_time(self, start_time, end_time, include_start=True,
 
     def resample(self, rule, how=None, axis=0, fill_method=None, closed=None,
                  label=None, convention='start', kind=None, loffset=None,
-                 limit=None, base=0, on=None, level=None):
+                 limit=None, base=0, on=None, level=None, fill_value=None):
         """
         Convenience method for frequency conversion and resampling of time
         series.  Object must have a datetime-like index (DatetimeIndex,
@@ -4166,8 +4166,10 @@ def resample(self, rule, how=None, axis=0, fill_method=None, closed=None,
 
             .. versionadded:: 0.19.0
 
-        Notes
-        -----
+        fill_value: scalar, optional
+            Value to use for missing values, applied before resampling
+
+            .. version added:: 0.19.2
 
         To learn more about the offset strings, please see `this link
         <http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases>`__.
@@ -4273,6 +4275,10 @@ def resample(self, rule, how=None, axis=0, fill_method=None, closed=None,
         from pandas.tseries.resample import (resample,
                                              _maybe_process_deprecations)
         axis = self._get_axis_number(axis)
+
+        if(fill_value is not None):
+            self = self.fillna(fill_value)
+
         r = resample(self, freq=rule, label=label, closed=closed,
                      axis=axis, kind=kind, loffset=loffset,
                      convention=convention,

pandas/tseries/tests/test_resample.py

@@ -361,6 +361,25 @@ def test_fillna(self):
         with self.assertRaises(ValueError):
             r.fillna(0)
 
+    def test_fill_value(self):
+        # setup
+        rng = pd.date_range('1/1/2016', periods=10, freq='2S')
+        ts = pd.Series(np.arange(len(rng)), index=rng)
+        ts2 = pd.Series(np.random.rand(len(rng)), index=rng)
+        df = pd.DataFrame({'one': ts, 'two': ts2})
+
+        # upsample to get NaN values
+        ts_up = ts.resample('1S').asfreq()
+        df_up = df.resample('1S').asfreq()
+
+        expected_ts = ts_up.fillna(2).resample('2S').sum()
+        actual_ts = ts_up.resample('2S',fill_value=2).sum()
+        assert_series_equal(expected_ts, actual_ts)
+
+        expected_df = df_up.fillna(1.5).resample('2S').sum()
+        actual_df = df_up.resample('2S', fill_value=1.5).sum()
+        assert_frame_equal(expected_df, actual_df)
+
     def test_apply_without_aggregation(self):
 
         # both resample and groupby should work w/o aggregation