a6c04a52a63efc1729062ec2b5c4ef5f8bfddbed,src/pudl/output/eia923.py,,fuel_receipts_costs_eia923,#Any#Any#Any#Any#Any#,129

Before Change

    pu_eia = pudl.output.eia860.plants_utils_eia860(pudl_engine,
                                                    start_date=start_date,
                                                    end_date=end_date)
    out_df = pudl.helpers.merge_on_date_year(
        frc_df, pu_eia, on=["plant_id_eia"])

    // Drop any records where we"ve failed to get the 860 data merged in...
    out_df = out_df.dropna(subset=["utility_id_eia", "utility_name_eia"])

    if freq is None:
        // There are a couple of invalid records with no specified fuel.
        out_df = out_df.dropna(subset=["fuel_group_code"])

    first_cols = ["report_date",
                  "plant_id_eia",
                  "plant_id_pudl",
                  "plant_name_eia",
                  "utility_id_eia",
                  "utility_id_pudl",
                  "utility_name_eia", ]

    // Re-arrange the columns for easier readability:
    out_df = pudl.helpers.organize_cols(out_df, first_cols)

    // Clean up the types of a few columns...
    out_df["plant_id_eia"] = out_df.plant_id_eia.astype(int)
    out_df["plant_id_pudl"] = out_df.plant_id_pudl.astype(int)
    out_df["utility_id_eia"] = out_df.utility_id_eia.astype(int)
    out_df["utility_id_pudl"] = out_df.utility_id_pudl.astype(int)

    return out_df

After Change

                                                    start_date=start_date,
                                                    end_date=end_date)

    out_df = (
        pudl.helpers.merge_on_date_year(frc_df, pu_eia, on=["plant_id_eia"])
        .dropna(subset=["utility_id_eia"])
        .pipe(
            pudl.helpers.organize_cols,
            cols=[
                "report_date",
                "plant_id_eia",
                "plant_id_pudl",
                "plant_name_eia",
                "utility_id_eia",
                "utility_id_pudl",
                "utility_name_eia",
            ]
        )
        .astype({
            "plant_id_eia": "Int64",
            "plant_id_pudl": "Int64",
            "utility_id_eia": "Int64",
            "utility_id_pudl": "Int64",
        })
    )

    if freq is None:
        // There are a couple of invalid records with no specified fuel.
        out_df = out_df.dropna(subset=["fuel_group_code"])

Instances