Less precise results

src/simstadt/results/energy_grid.py

@@ -56,11 +56,11 @@ class EnergyGridResults(SimStadtResults):
             KPI("Number of inhabitants", df.attrs["number_of_people"], precision=0),
             KPI("Most common archetype", archetype_share, f"% ({most_common_archetype})", precision=0),
             KPI("Total heated area", total_heated_area, "m²", precision=0),
-            KPI("Total electricity demand", total_elec_kwh / 1000, "MWh / a", precision=1),
-            KPI("Specific electricity demand", total_elec_kwh / total_heated_area, "kWh / (m² · a)", precision=1),
-            KPI("Total heat demand", total_heat_kwh / 1000, "MWh / a", precision=1),
-            KPI("Specific heat demand", total_heat_kwh / total_heated_area, "kWh / (m² · a)", precision=1),
-            KPI("Total PV production", df["pv_production"].sum() / 1000, "MWh / a", precision=1),
+            KPI("Total electricity demand", total_elec_kwh / 1000, "MWh / a", precision=0),
+            KPI("Specific electricity demand", total_elec_kwh / total_heated_area, "kWh / (m² · a)", precision=0),
+            KPI("Total heat demand", total_heat_kwh / 1000, "MWh / a", precision=0),
+            KPI("Specific heat demand", total_heat_kwh / total_heated_area, "kWh / (m² · a)", precision=0),
+            KPI("Total PV production", df["pv_production"].sum() / 1000, "MWh / a", precision=0),
             KPI("Average temperature", float(df["ambient_temperature"].mean()), "°C", precision=1),
         ]