address deprecation warnings

scripts/add_electricity.py

@@ -327,7 +327,9 @@ def attach_load(n, regions, load, nuts3_shapes, ua_md_gdp, countries, scaling=1.
         axis=1,
     )
 
-    n.madd("Load", substation_lv_i, bus=substation_lv_i, p_set=load)
+    n.madd(
+        "Load", substation_lv_i, bus=substation_lv_i, p_set=load
+    )  # carrier="electricity"
 
 
 def update_transmission_costs(n, costs, length_factor=1.0):
@@ -504,8 +506,8 @@ def attach_conventional_generators(
                     snakemake.input[f"conventional_{carrier}_{attr}"], index_col=0
                 ).iloc[:, 0]
                 bus_values = n.buses.country.map(values)
-                n.generators[attr].update(
+                n.generators.update(
-                    n.generators.loc[idx].bus.map(bus_values).dropna()
+                    {attr: n.generators.loc[idx].bus.map(bus_values).dropna()}
                 )
             else:
                 # Single value affecting all generators of technology k indiscriminantely of country
@@ -749,8 +751,8 @@ def attach_OPSD_renewables(n: pypsa.Network, tech_map: Dict[str, List[str]]) ->
         caps = caps.groupby(["bus"]).Capacity.sum()
         caps = caps / gens_per_bus.reindex(caps.index, fill_value=1)
 
-        n.generators.p_nom.update(gens.bus.map(caps).dropna())
+        n.generators.update({"p_nom": gens.bus.map(caps).dropna()})
-        n.generators.p_nom_min.update(gens.bus.map(caps).dropna())
+        n.generators.update({"p_nom_min": gens.bus.map(caps).dropna()})
 
 
 def estimate_renewable_capacities(

scripts/add_existing_baseyear.py

@@ -48,7 +48,7 @@ def add_build_year_to_new_assets(n, baseyear):
             "series"
         ) & n.component_attrs[c.name].status.str.contains("Input")
         for attr in n.component_attrs[c.name].index[selection]:
-            c.pnl[attr].rename(columns=rename, inplace=True)
+            c.pnl[attr] = c.pnl[attr].rename(columns=rename)
 
 
 def add_existing_renewables(df_agg):

scripts/base_network.py

@@ -138,7 +138,9 @@ def _load_buses_from_eg(eg_buses, europe_shape, config_elec):
     )
 
     buses["carrier"] = buses.pop("dc").map({True: "DC", False: "AC"})
-    buses["under_construction"] = buses["under_construction"].fillna(False).astype(bool)
+    buses["under_construction"] = buses.under_construction.where(
+        lambda s: s.notnull(), False
+    ).astype(bool)
 
     # remove all buses outside of all countries including exclusive economic zones (offshore)
     europe_shape = gpd.read_file(europe_shape).loc[0, "geometry"]
@@ -525,9 +527,9 @@ def _set_countries_and_substations(n, config, country_shapes, offshore_shapes):
     gb = buses.loc[substation_b].groupby(
         ["x", "y"], as_index=False, group_keys=False, sort=False
     )
-    bus_map_low = gb.apply(prefer_voltage, "min")
+    bus_map_low = gb.apply(prefer_voltage, "min", include_groups=False)
     lv_b = (bus_map_low == bus_map_low.index).reindex(buses.index, fill_value=False)
-    bus_map_high = gb.apply(prefer_voltage, "max")
+    bus_map_high = gb.apply(prefer_voltage, "max", include_groups=False)
     hv_b = (bus_map_high == bus_map_high.index).reindex(buses.index, fill_value=False)
 
     onshore_b = pd.Series(False, buses.index)

scripts/build_biomass_potentials.py

@@ -132,14 +132,14 @@ def disaggregate_nuts0(bio):
     pop = build_nuts_population_data()
 
     # get population in nuts2
-    pop_nuts2 = pop.loc[pop.index.str.len() == 4]
+    pop_nuts2 = pop.loc[pop.index.str.len() == 4].copy()
     by_country = pop_nuts2.total.groupby(pop_nuts2.ct).sum()
-    pop_nuts2.loc[:, "fraction"] = pop_nuts2.total / pop_nuts2.ct.map(by_country)
+    pop_nuts2["fraction"] = pop_nuts2.total / pop_nuts2.ct.map(by_country)
 
     # distribute nuts0 data to nuts2 by population
     bio_nodal = bio.loc[pop_nuts2.ct]
     bio_nodal.index = pop_nuts2.index
-    bio_nodal = bio_nodal.mul(pop_nuts2.fraction, axis=0)
+    bio_nodal = bio_nodal.mul(pop_nuts2.fraction, axis=0).astype(float)
 
     # update inplace
     bio.update(bio_nodal)

scripts/build_gas_network.py

@@ -114,12 +114,10 @@ def prepare_dataset(
     df["p_nom_diameter"] = df.diameter_mm.apply(diameter_to_capacity)
     ratio = df.p_nom / df.p_nom_diameter
     not_nordstream = df.max_pressure_bar < 220
-    df.p_nom.update(
+    df["p_nom"] = df.p_nom_diameter.where(
-        df.p_nom_diameter.where(
+        (df.p_nom <= 500)
-            (df.p_nom <= 500)
+        | ((ratio > correction_threshold_p_nom) & not_nordstream)
-            | ((ratio > correction_threshold_p_nom) & not_nordstream)
+        | ((ratio < 1 / correction_threshold_p_nom) & not_nordstream)
-            | ((ratio < 1 / correction_threshold_p_nom) & not_nordstream)
-        )
     )
 
     # lines which have way too discrepant line lengths
@@ -130,12 +128,10 @@ def prepare_dataset(
         axis=1,
     )
     ratio = df.eval("length / length_haversine")
-    df["length"].update(
+    df["length"] = df.length_haversine.where(
-        df.length_haversine.where(
+        (df["length"] < 20)
-            (df["length"] < 20)
+        | (ratio > correction_threshold_length)
-            | (ratio > correction_threshold_length)
+        | (ratio < 1 / correction_threshold_length)
-            | (ratio < 1 / correction_threshold_length)
-        )
     )
 
     return df

scripts/build_line_rating.py

@@ -98,7 +98,7 @@ def calculate_line_rating(n, cutout):
     -------
     xarray DataArray object with maximal power.
     """
-    relevant_lines = n.lines[~n.lines["underground"]]
+    relevant_lines = n.lines[~n.lines["underground"]].copy()
     buses = relevant_lines[["bus0", "bus1"]].values
     x = n.buses.x
     y = n.buses.y

scripts/build_population_layouts.py

@@ -83,7 +83,8 @@ if __name__ == "__main__":
 
         # correct for imprecision of Iinv*I
         pop_ct = nuts3.loc[nuts3.country == ct, "pop"].sum()
-        pop_cells_ct *= pop_ct / pop_cells_ct.sum()
+        if pop_cells_ct.sum() != 0:
+            pop_cells_ct *= pop_ct / pop_cells_ct.sum()
 
         # The first low density grid cells to reach rural fraction are rural
         asc_density_i = density_cells_ct.sort_values().index

scripts/build_retro_cost.py

@@ -297,8 +297,8 @@ def prepare_building_stock_data():
         errors="ignore",
     )
 
-    u_values.subsector.replace(rename_sectors, inplace=True)
+    u_values["subsector"] = u_values.subsector.replace(rename_sectors)
-    u_values.btype.replace(rename_sectors, inplace=True)
+    u_values["btype"] = u_values.btype.replace(rename_sectors)
 
     # for missing weighting of surfaces of building types assume MFH
     u_values["assumed_subsector"] = u_values.subsector
@@ -306,8 +306,8 @@ def prepare_building_stock_data():
         ~u_values.subsector.isin(rename_sectors.values()), "assumed_subsector"
     ] = "MFH"
 
-    u_values.country_code.replace({"UK": "GB"}, inplace=True)
+    u_values["country_code"] = u_values.country_code.replace({"UK": "GB"})
-    u_values.bage.replace({"Berfore 1945": "Before 1945"}, inplace=True)
+    u_values["bage"] = u_values.bage.replace({"Berfore 1945": "Before 1945"})
     u_values = u_values[~u_values.bage.isna()]
 
     u_values.set_index(["country_code", "subsector", "bage", "type"], inplace=True)

scripts/cluster_network.py

@@ -488,7 +488,9 @@ if __name__ == "__main__":
                     gens.efficiency, bins=[0, low, high, 1], labels=labels
                 ).astype(str)
                 carriers += [f"{c} {label} efficiency" for label in labels]
-                n.generators.carrier.update(gens.carrier + " " + suffix + " efficiency")
+                n.generators.update(
+                    {"carrier": gens.carrier + " " + suffix + " efficiency"}
+                )
         aggregate_carriers = carriers
 
     if n_clusters == len(n.buses):

scripts/prepare_network.py

@@ -269,8 +269,8 @@ def set_line_nom_max(
         hvdc = n.links.index[n.links.carrier == "DC"]
         n.links.loc[hvdc, "p_nom_max"] = n.links.loc[hvdc, "p_nom"] + p_nom_max_ext
 
-    n.lines.s_nom_max.clip(upper=s_nom_max_set, inplace=True)
+    n.lines["s_nom_max"] = n.lines.s_nom_max.clip(upper=s_nom_max_set)
-    n.links.p_nom_max.clip(upper=p_nom_max_set, inplace=True)
+    n.links["p_nom_max"] = n.links.p_nom_max.clip(upper=p_nom_max_set)
 
 
 if __name__ == "__main__":

scripts/solve_network.py

@@ -418,7 +418,7 @@ def add_CCL_constraints(n, config):
     Example
     -------
     scenario:
-        opts: [Co2L-CCL-24H]
+        opts: [Co2L-CCL-24h]
     electricity:
         agg_p_nom_limits: data/agg_p_nom_minmax.csv
     """
@@ -463,7 +463,7 @@ def add_EQ_constraints(n, o, scaling=1e-1):
     Example
     -------
     scenario:
-        opts: [Co2L-EQ0.7-24H]
+        opts: [Co2L-EQ0.7-24h]
 
     Require each country or node to on average produce a minimal share
     of its total electricity consumption itself. Example: EQ0.7c demands each country
@@ -527,7 +527,7 @@ def add_BAU_constraints(n, config):
     Example
     -------
     scenario:
-        opts: [Co2L-BAU-24H]
+        opts: [Co2L-BAU-24h]
     electricity:
         BAU_mincapacities:
             solar: 0
@@ -564,7 +564,7 @@ def add_SAFE_constraints(n, config):
     config.yaml requires to specify opts:
 
     scenario:
-        opts: [Co2L-SAFE-24H]
+        opts: [Co2L-SAFE-24h]
     electricity:
         SAFE_reservemargin: 0.1
     Which sets a reserve margin of 10% above the peak demand.