Include imputed clean

tests/test_sdk.py

@@ -208,6 +208,17 @@ def test_get_historical_pandas(self):
         self.assertIn("point_time", df.columns)
         self.assertIn("value", df.columns)
 
+    def test_get_historical_pandas_include_imputed(self):
+        start = datetime.now() - timedelta(days=7)
+        end = datetime.now()
+        df = self.historical.get_historical_pandas(start, end, REGION, include_imputed_marker=True)
+
+        self.assertIsInstance(df, pd.DataFrame)
+        self.assertGreaterEqual(len(df), 1)
+        self.assertIn("point_time", df.columns)
+        self.assertIn("value", df.columns)
+        self.assertIn("imputed_data_used", df.columns)
+
     def test_get_historical_pandas_meta(self):
         start = datetime.now() - timedelta(days=7)
         end = datetime.now()

watttime/api.py

@@ -370,6 +370,7 @@ def get_historical_jsons(
             Literal["co2_moer", "co2_aoer", "health_damage"]
         ] = "co2_moer",
         model: Optional[Union[str, date]] = None,
+        include_imputed_marker: bool = False,
     ) -> List[dict]:
         """
         Base function to scrape historical data, returning a list of .json responses.
@@ -391,6 +392,9 @@ def get_historical_jsons(
         url = "{}/v3/historical".format(self.url_base)
         params = {"region": region, "signal_type": signal_type}
 
+        if include_imputed_marker:
+            params["include_imputed_marker"] = "true"
+
         start, end = self._parse_dates(start, end)
         chunks = self._get_chunks(start, end)
 
@@ -421,6 +425,7 @@ def get_historical_pandas(
         ] = "co2_moer",
         model: Optional[Union[str, date]] = None,
         include_meta: bool = False,
+        include_imputed_marker: bool = False,
     ):
         """
         Return a pd.DataFrame with point_time, and values.
@@ -434,7 +439,9 @@ def get_historical_pandas(
         Returns:
             pd.DataFrame: _description_
         """
-        responses = self.get_historical_jsons(start, end, region, signal_type, model)
+        responses = self.get_historical_jsons(
+            start, end, region, signal_type, model, include_imputed_marker
+        )
         df = pd.json_normalize(
             responses, record_path="data", meta=["meta"] if include_meta else []
         )
@@ -452,6 +459,7 @@ def get_historical_csv(
             Literal["co2_moer", "co2_aoer", "health_damage"]
         ] = "co2_moer",
         model: Optional[Union[str, date]] = None,
+        include_imputed_marker: bool = False,
     ):
         """
         Retrieves historical data from a specified start date to an end date and saves it as a CSV file.
@@ -467,7 +475,9 @@ def get_historical_csv(
         Returns:
             None, results are saved to a csv file in the user's home directory.
         """
-        df = self.get_historical_pandas(start, end, region, signal_type, model)
+        df = self.get_historical_pandas(
+            start, end, region, signal_type, model, include_imputed_marker
+        )
 
         out_dir = Path.home() / "watttime_historical_csvs"
         out_dir.mkdir(exist_ok=True)