update on both .shift() and [index].iloc[column] deprecation warning (#…

…510) * update on both .shift() and [index].iloc[column] deprecation warning of pandas Signed-off-by: Jonita Ruiter <[email protected]> * Format Python code with Black Signed-off-by: black <[email protected]> * trying to fix black format fail Signed-off-by: Jonita Ruiter <[email protected]> * Format Python code with Black Signed-off-by: black <[email protected]> * trying to fix black format fail2 Signed-off-by: Jonita Ruiter <[email protected]> --------- Signed-off-by: Jonita Ruiter <[email protected]> Signed-off-by: black <[email protected]> Co-authored-by: black <[email protected]>
OpenSTEF · Feb 20, 2024 · 0ccf134 · 0ccf134
1 parent 5616be9
commit 0ccf134
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diff --git a/openstef/feature_engineering/lag_features.py b/openstef/feature_engineering/lag_features.py
@@ -43,7 +43,7 @@ def generate_lag_feature_functions(
     for minutes in lag_times_minutes:  # Add intraday-lag functions (lags in minutes)
 
         def func(x, shift=minutes):
-            return x.shift(freq="T", periods=1 * shift)
+            return x.shift(freq="min", periods=1 * shift)
 
         new = {"T-" + str(int(minutes)) + "min": func}
         lag_functions.update(new)

diff --git a/openstef/model/standard_deviation_generator.py b/openstef/model/standard_deviation_generator.py
@@ -72,8 +72,9 @@ def _calculate_standard_deviation(
         # For the time starts with 00, 01, 02, etc. TODO (MAKE MORE ELEGANT SOLUTION THAN A LOOP)
         for hour in range(24):
             hour_error = error[error.index == hour]
-            result["stdev"].iloc[hour] = np.std(hour_error)
-            result["hour"].iloc[hour] = hour
+
+            result.loc[hour, "stdev"] = np.std(hour_error)
+            result.loc[hour, "hour"] = hour
 
         result = result.astype("float")
 

diff --git a/test/unit/pipeline/test_create_basecase.py b/test/unit/pipeline/test_create_basecase.py
@@ -28,7 +28,7 @@ def setUp(self) -> None:
             - (forecast_input.index.max() - timedelta(days=7))
         ).total_seconds()
         forecast_input = forecast_input.shift(
-            freq="T", periods=int(int(offset_seconds / 60.0 / 15.0) * 15)
+            freq="min", periods=int(int(offset_seconds / 60.0 / 15.0) * 15)
         )
 
         self.forecast_input = forecast_input