From a143ab7122e7ec8311bbb0d2fdcb5d05fd075a8e Mon Sep 17 00:00:00 2001 From: Fabian Neumann Date: Tue, 24 Nov 2020 13:44:02 +0100 Subject: [PATCH] energy_totals: only fix 'BA' if in list of countries --- scripts/build_energy_totals.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/scripts/build_energy_totals.py b/scripts/build_energy_totals.py index 1682ac40..0cfa709b 100644 --- a/scripts/build_energy_totals.py +++ b/scripts/build_energy_totals.py @@ -378,12 +378,12 @@ def build_energy_totals(): clean_df.loc[missing,"total aviation passenger"] = clean_df.loc[missing,["total domestic aviation passenger","total international aviation passenger"]].sum(axis=1) clean_df.loc[missing,"total aviation freight"] = clean_df.loc[missing,["total domestic aviation freight","total international aviation freight"]].sum(axis=1) + if "BA" in clean_df.index: + #fix missing data for BA (services and road energy data) + missing = (clean_df.loc["BA"] == 0.) - #fix missing data for BA (services and road energy data) - missing = (clean_df.loc["BA"] == 0.) - - #add back in proportional to RS with ratio of total residential demand - clean_df.loc["BA",missing] = clean_df.loc["BA","total residential"]/clean_df.loc["RS","total residential"]*clean_df.loc["RS",missing] + #add back in proportional to RS with ratio of total residential demand + clean_df.loc["BA",missing] = clean_df.loc["BA","total residential"]/clean_df.loc["RS","total residential"]*clean_df.loc["RS",missing] clean_df.to_csv(snakemake.output.energy_name)