30703a7036f9bfd58ba23c2872887f1820ef928e,pudl/outputs.py,,fuel_ferc1_df,#Any#,94

Before Change

    // Build a SELECT statement that gives us information from several different
    // tables that are relevant to FERC Fuel.
    fuel_ferc1_select = sa.sql.select([
        pt["fuel_ferc1"].c.report_year,
        pt["utilities_ferc"].c.respondent_id,
        pt["utilities_ferc"].c.respondent_name,
        pt["utilities_ferc"].c.util_id_pudl,
        pt["plants_ferc"].c.plant_id_pudl,
        pt["fuel_ferc1"].c.plant_name,
        pt["fuel_ferc1"].c.fuel,
        pt["fuel_ferc1"].c.fuel_qty_burned,
        pt["fuel_ferc1"].c.fuel_avg_mmbtu_per_unit,
        pt["fuel_ferc1"].c.fuel_cost_per_unit_burned,
        pt["fuel_ferc1"].c.fuel_cost_per_unit_delivered,
        pt["fuel_ferc1"].c.fuel_cost_per_mmbtu,
        pt["fuel_ferc1"].c.fuel_cost_per_mwh,
        pt["fuel_ferc1"].c.fuel_mmbtu_per_mwh]).\
        where(sa.sql.and_(
            pt["utilities_ferc"].c.respondent_id ==
            pt["fuel_ferc1"].c.respondent_id,

After Change

    pu_ferc = plants_utils_ferc_df(pudl_engine)

    out_df = pd.merge(fuel_df, pu_ferc, on=["respondent_id", "plant_name"])
    out_df = out_df.drop("id", axis=1)

    out_df = out_df[[
        "report_year",
        "respondent_id",

Instances