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

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pre-commit-ci[bot] 2024-03-14 17:11:26 +00:00
parent 88dba98512
commit a6ea15ea4a
3 changed files with 9 additions and 5 deletions
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4
scripts/build_district_heat_share.py
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@ -33,7 +33,9 @@ if __name__ == "__main__":
pop_layout = pd.read_csv(snakemake.input.clustered_pop_layout, index_col=0)
year = str(snakemake.params.energy_totals_year)
district_heat_share = pd.read_csv(snakemake.input.district_heat_share, index_col=0)[year]
district_heat_share = pd.read_csv(snakemake.input.district_heat_share, index_col=0)[
year
]
# make ct-based share nodal
district_heat_share = district_heat_share.reindex(pop_layout.ct).fillna(0)

8
scripts/build_energy_totals.py
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@ -419,7 +419,7 @@ def build_energy_totals(countries, eurostat, swiss, idees):
# add swiss energy data
df = pd.concat([df.drop("CH", errors='ignore'), swiss]).sort_index()
df = pd.concat([df.drop("CH", errors="ignore"), swiss]).sort_index()
# get values for missing countries based on Eurostat EnergyBalances
# divide cooking/space/water according to averages in EU28
@ -724,7 +724,7 @@ def build_transport_data(countries, population, idees):
countries_without_ch = set(countries) - {"CH"}
new_index = pd.MultiIndex.from_product(
[countries_without_ch, transport_data.index.levels[1]],
names=["country", "year"]
names=["country", "year"],
)
transport_data = transport_data.reindex(index=new_index)
@ -750,7 +750,9 @@ def build_transport_data(countries, population, idees):
cars_pp = transport_data["number cars"] / population
fill_values = {year: cars_pp.mean() * population for year in transport_data.index.levels[1]}
fill_values = {
year: cars_pp.mean() * population for year in transport_data.index.levels[1]
}
fill_values = pd.DataFrame(fill_values).stack()
fill_values = pd.DataFrame(fill_values, columns=["number cars"])
fill_values.index.names = ["country", "year"]

2
scripts/build_transport_demand.py
View File

@ -25,7 +25,7 @@ logger = logging.getLogger(__name__)
def build_nodal_transport_data(fn, pop_layout, year):
transport_data = pd.read_csv(fn, index_col=[0, 1])
transport_data = transport_data.xs(min(2015, year), level='year')
transport_data = transport_data.xs(min(2015, year), level="year")
nodal_transport_data = transport_data.loc[pop_layout.ct].fillna(0.0)
nodal_transport_data.index = pop_layout.index