a5d1cf98f0ec5c72fb48336cafaf31bf11e6128e,src/pudl/analysis/mcoe.py,,mcoe,#Any#Any#Any#Any#Any#,311

Before Change

    mcoe_out["total_fuel_cost"] = \
        mcoe_out.total_mmbtu * mcoe_out.fuel_cost_per_mmbtu

    simplified_gens_eia860 = pudl_out.gens_eia860().drop([
        "plant_id_pudl",
        "plant_name_eia",
        "utility_id_eia",
        "utility_id_pudl",
        "utility_name_eia",
        "fuel_type_count",
        "fuel_type_code_pudl"
    ], axis=1)
    mcoe_out = pudl.helpers.merge_on_date_year(
        mcoe_out, simplified_gens_eia860, on=["plant_id_eia", "generator_id"])

After Change

    drop_cols = [x for x in pudl_out.gens_eia860().columns
                 if x in pudl_out.fuel_cost().columns and x not in merge_cols]
    // start with the generators table so we have all of the generators
    mcoe_out = pudl.helpers.merge_on_date_year(
        pudl_out.fuel_cost().drop(drop_cols, axis=1),
        pudl_out.gens_eia860(),
        on=[x for x in merge_cols if x != "report_date"],
        how="inner",
    )
    // Bring together the fuel cost and capacity factor dataframes, which
    // also include heat rate information.
    mcoe_out = pd.merge(
        mcoe_out,

Instances