[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

scripts/build_energy_totals.py

@@ -609,7 +609,7 @@ def fill_missing_years(fill_values: pd.Series) -> pd.Series:
     - The function groups the data by the 'country' level and computes the mean for each group.
     - Zero values in the original Series are replaced by the mean value of their respective country group.
     """
-    means = fill_values.groupby(level='country').transform('mean')
+    means = fill_values.groupby(level="country").transform("mean")
     return fill_values.where(fill_values != 0, means)
 
 
@@ -686,10 +686,10 @@ def build_energy_totals(
     y = to_fill.get_level_values("year")
 
     # take total final energy consumption from Eurostat
-    eurostat_sector = 'Agriculture & forestry'
+    eurostat_sector = "Agriculture & forestry"
     slicer = idx[c, y, :, :, eurostat_sector]
 
-    fill_values = eurostat.loc[slicer]["Total all products"].groupby(level=[0,1]).sum()
+    fill_values = eurostat.loc[slicer]["Total all products"].groupby(level=[0, 1]).sum()
     # fill missing years for some countries by mean over the other years
     fill_values = fill_missing_years(fill_values)
     df.loc[to_fill, "total agriculture"] = fill_values
@@ -698,9 +698,12 @@ def build_energy_totals(
     uses = ["electricity", "heat", "machinery"]
 
     for use in uses:
-        avg = (idees["total agriculture electricity"]
-               /idees["total agriculture"]).mean()
-        df.loc[to_fill, f"total agriculture {use}"] = df.loc[to_fill, "total agriculture"] * avg
+        avg = (
+            idees["total agriculture electricity"] / idees["total agriculture"]
+        ).mean()
+        df.loc[to_fill, f"total agriculture {use}"] = (
+            df.loc[to_fill, "total agriculture"] * avg
+        )
 
     # divide cooking/space/water according to averages in EU28