From 1625d9db75244d1951a5cf9cc0c395452ddc2438 Mon Sep 17 00:00:00 2001 From: Fabian Neumann Date: Tue, 12 Apr 2022 14:37:05 +0200 Subject: [PATCH] address recent deprecations (#235) * address recent deprecations * address recent deprecations in pd.read_csv --- scripts/add_existing_baseyear.py | 4 ++-- scripts/build_biomass_potentials.py | 2 +- scripts/build_gas_input_locations.py | 2 +- scripts/build_industrial_production_per_country.py | 6 +++--- scripts/build_industry_sector_ratios.py | 3 +-- scripts/build_population_layouts.py | 2 +- scripts/prepare_sector_network.py | 11 +++++------ 7 files changed, 14 insertions(+), 16 deletions(-) diff --git a/scripts/add_existing_baseyear.py b/scripts/add_existing_baseyear.py index bb35e378..13863e10 100644 --- a/scripts/add_existing_baseyear.py +++ b/scripts/add_existing_baseyear.py @@ -153,8 +153,8 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas df_agg.Fueltype = df_agg.Fueltype.map(rename_fuel) # assign clustered bus - busmap_s = pd.read_csv(snakemake.input.busmap_s, index_col=0, squeeze=True) - busmap = pd.read_csv(snakemake.input.busmap, index_col=0, squeeze=True) + busmap_s = pd.read_csv(snakemake.input.busmap_s, index_col=0).squeeze() + busmap = pd.read_csv(snakemake.input.busmap, index_col=0).squeeze() inv_busmap = {} for k, v in busmap.iteritems(): diff --git a/scripts/build_biomass_potentials.py b/scripts/build_biomass_potentials.py index c9a2594d..c80c6b46 100644 --- a/scripts/build_biomass_potentials.py +++ b/scripts/build_biomass_potentials.py @@ -149,7 +149,7 @@ def build_nuts2_shapes(): nuts2.rename(index={"ME00": "ME", "MK00": "MK"}, inplace=True) - return nuts2.append(missing) + return pd.concat([nuts2, missing]) def area(gdf): diff --git a/scripts/build_gas_input_locations.py b/scripts/build_gas_input_locations.py index 1b823d6d..c08d92de 100644 --- a/scripts/build_gas_input_locations.py +++ b/scripts/build_gas_input_locations.py @@ -26,7 +26,7 @@ def build_gas_input_locations(lng_fn, planned_lng_fn, entry_fn, prod_fn, countri planned_lng = pd.read_csv(planned_lng_fn) planned_lng.geometry = planned_lng.geometry.apply(wkt.loads) planned_lng = gpd.GeoDataFrame(planned_lng, crs=4326) - lng = lng.append(planned_lng, ignore_index=True) + lng = pd.concat([lng, planned_lng], ignore_index=True) # Entry points from outside the model scope entry = read_scigrid_gas(entry_fn) diff --git a/scripts/build_industrial_production_per_country.py b/scripts/build_industrial_production_per_country.py index eadfb224..f21b711a 100644 --- a/scripts/build_industrial_production_per_country.py +++ b/scripts/build_industrial_production_per_country.py @@ -115,14 +115,14 @@ def get_energy_ratio(country): # estimate physical output, energy consumption in the sector and country fn = f"{eurostat_dir}/{eb_names[country]}.XLSX" df = pd.read_excel(fn, sheet_name='2016', index_col=2, - header=0, skiprows=1, squeeze=True) + header=0, skiprows=1).squeeze('columns') e_country = df.loc[eb_sectors.keys( ), 'Total all products'].rename(eb_sectors) fn = f'{jrc_dir}/JRC-IDEES-2015_Industry_EU28.xlsx' df = pd.read_excel(fn, sheet_name='Ind_Summary', - index_col=0, header=0, squeeze=True) + index_col=0, header=0).squeeze('columns') assert df.index[48] == "by sector" year_i = df.columns.get_loc(year) @@ -142,7 +142,7 @@ def industry_production_per_country(country): fn = f'{jrc_dir}/JRC-IDEES-2015_Industry_{jrc_country}.xlsx' sheet = sub_sheet_name_dict[sector] df = pd.read_excel(fn, sheet_name=sheet, - index_col=0, header=0, squeeze=True) + index_col=0, header=0).squeeze('columns') year_i = df.columns.get_loc(year) df = df.iloc[find_physical_output(df), year_i] diff --git a/scripts/build_industry_sector_ratios.py b/scripts/build_industry_sector_ratios.py index a6ef9066..16c9de9e 100644 --- a/scripts/build_industry_sector_ratios.py +++ b/scripts/build_industry_sector_ratios.py @@ -78,9 +78,8 @@ def load_idees_data(sector, country="EU28"): sheet_name=list(sheets.values()), index_col=0, header=0, - squeeze=True, usecols=usecols, - ) + ).squeeze('columns') for k, v in sheets.items(): idees[k] = idees.pop(v) diff --git a/scripts/build_population_layouts.py b/scripts/build_population_layouts.py index 6c229797..fa5c7d28 100644 --- a/scripts/build_population_layouts.py +++ b/scripts/build_population_layouts.py @@ -33,7 +33,7 @@ if __name__ == '__main__': urban_fraction = pd.read_csv(snakemake.input.urban_percent, header=None, index_col=0, - names=['fraction'], squeeze=True) / 100. + names=['fraction']).squeeze() / 100. # fill missing Balkans values missing = ["AL", "ME", "MK"] diff --git a/scripts/prepare_sector_network.py b/scripts/prepare_sector_network.py index 56f448fa..f81516a9 100644 --- a/scripts/prepare_sector_network.py +++ b/scripts/prepare_sector_network.py @@ -279,7 +279,7 @@ def create_network_topology(n, prefix, carriers=["DC"], connector=" -> ", bidire topo_reverse = topo.copy() topo_reverse.rename(columns=swap_buses, inplace=True) topo_reverse.index = topo_reverse.apply(make_index, axis=1) - topo = topo.append(topo_reverse) + topo = pd.concat([topo, topo_reverse]) return topo @@ -686,7 +686,7 @@ def prepare_data(n): ## Get overall demand curve for all vehicles - traffic = pd.read_csv(snakemake.input.traffic_data_KFZ, skiprows=2, usecols=["count"], squeeze=True) + traffic = pd.read_csv(snakemake.input.traffic_data_KFZ, skiprows=2, usecols=["count"]).squeeze() #Generate profiles transport_shape = generate_periodic_profiles( @@ -741,7 +741,7 @@ def prepare_data(n): ## derive plugged-in availability for PKW's (cars) - traffic = pd.read_csv(snakemake.input.traffic_data_Pkw, skiprows=2, usecols=["count"], squeeze=True) + traffic = pd.read_csv(snakemake.input.traffic_data_Pkw, skiprows=2, usecols=["count"]).squeeze() avail_max = options.get("bev_avail_max", 0.95) avail_mean = options.get("bev_avail_mean", 0.8) @@ -1888,8 +1888,7 @@ def add_biomass(n, costs): transport_costs = pd.read_csv( snakemake.input.biomass_transport_costs, index_col=0, - squeeze=True - ) + ).squeeze() # add biomass transport biomass_transport = create_network_topology(n, "biomass transport ", bidirectional=False) @@ -2521,7 +2520,7 @@ if __name__ == "__main__": fn = snakemake.config['results_dir'] + snakemake.config['run'] + '/csvs/carbon_budget_distribution.csv' if not os.path.exists(fn): build_carbon_budget(o, fn) - co2_cap = pd.read_csv(fn, index_col=0, squeeze=True) + co2_cap = pd.read_csv(fn, index_col=0).squeeze() limit = co2_cap[investment_year] break for o in opts: