Include predictions for missing y (NaN) dates in the history (#2530)

Co-authored-by: Imad Rahmouni <[email protected]>

Author: imad24

python/prophet/forecaster.py

@@ -1130,7 +1130,7 @@ def preprocess(self, df: pd.DataFrame, **kwargs) -> ModelInputData:
         history = df[df['y'].notnull()].copy()
         if history.shape[0] < 2:
             raise ValueError('Dataframe has less than 2 non-NaN rows.')
-        self.history_dates = pd.to_datetime(pd.Series(history['ds'].unique(), name='ds')).sort_values()
+        self.history_dates = pd.to_datetime(pd.Series(df['ds'].unique(), name='ds')).sort_values()
 
         self.history = self.setup_dataframe(history, initialize_scales=True)
         self.set_auto_seasonalities()

python/prophet/tests/test_prophet.py

@@ -244,6 +244,16 @@ def test_make_future_dataframe(self, daily_univariate_ts, backend):
         assert len(future) == 3
         assert np.all(future["ds"].values == correct.values)
 
+    def test_make_future_dataframe_include_history(self, daily_univariate_ts, backend):
+        train = daily_univariate_ts.head(468 // 2).copy()
+        #cover history with NAs
+        train.loc[train.sample(10).index, "y"] = np.nan
+        
+        forecaster = Prophet(stan_backend=backend)
+        forecaster.fit(train)
+        future = forecaster.make_future_dataframe(periods=3, freq="D", include_history=True)
+
+        assert len(future) == train.shape[0] + 3
 
 class TestProphetTrendComponent:
     def test_invalid_growth_input(self, backend):