Merge pull request #523 from openeemeter/bugfix/nan_zeroes_for_electr…

…icity

have HourlyBaselineData/HourlyReportingData where is_electricity=True NaN zero rows

CHANGELOG.md

@@ -4,6 +4,7 @@ Changelog
 Development
 -----------
 
+* Fix bug where HourlyBaselineData and HourlyReportingData wasn't actually NaNning zero rows when `is_electricity=True`.
 * Constrain eemeter daily model balance points to T_min_seg and T_max_seg rather than T_min and T_max.
 
 4.0.7

eemeter/eemeter/models/hourly/data.py

@@ -33,7 +33,7 @@ def __init__(self, df: pd.DataFrame, is_electricity_data: bool):
             df["observed"] = np.nan
 
         if is_electricity_data:
-            df[df["observed"] == 0]["observed"] = np.nan
+            df.loc[df["observed"] == 0, "observed"] = np.nan
 
         df = self._correct_frequency(df)
 
@@ -85,7 +85,7 @@ def from_series(
 class HourlyBaselineData(HourlyReportingData):
     def __init__(self, df: pd.DataFrame, is_electricity_data: bool):
         if is_electricity_data:
-            df[df["observed"] == 0]["observed"] = np.nan
+            df.loc[df["observed"] == 0, "observed"] = np.nan
 
         df = self._correct_frequency(df)
 

tests/test_json_serialization.py

@@ -120,6 +120,21 @@ def test_json_billing():
     assert total_metered_savings == total_metered_savings_loaded
 
 
+def test_json_hourly_with_zeros():
+    meter_data, temperature_data, sample_metadata = load_sample(
+        "il-electricity-cdd-hdd-hourly"
+    )
+    meter_data["value"] = 0
+    baseline = HourlyBaselineData.from_series(
+        meter_data, temperature_data, is_electricity_data=True
+    )
+    assert baseline.df["observed"].isnull().all()
+    reporting = HourlyReportingData.from_series(
+        meter_data, temperature_data, is_electricity_data=True
+    )
+    assert reporting.df["observed"].isnull().all()
+
+
 def test_json_hourly():
     meter_data, temperature_data, sample_metadata = load_sample(
         "il-electricity-cdd-hdd-hourly"
@@ -212,4 +227,4 @@ def test_legacy_deserialization_hourly(request):
         metered_savings_dataframe["observed"] - metered_savings_dataframe["predicted"]
     ).sum()
 
-    assert round(total_metered_savings, 2) == -52893.66
+    assert round(total_metered_savings, 2) == -52454.02