fbd16b4f301f09b8868b60a4762700f3251e2cdc,src/pudl/transform/ferc1.py,,plant_in_service,#Any#Any#,977

Before Change

    // organized by the previously reported columns:
    categorized_pis = pd.DataFrame()
    for category in pis_df.columns.levels[0]:
        tmp_df = pis_df.loc[:, category].copy()
        tmp_df["amount_type"] = category
        categorized_pis = pd.concat([categorized_pis, tmp_df])
    categorized_pis.columns.name = None
    pis_df = (

After Change

        dict: The dictionary of the transformed DataFrames.

    
    pis_df = (
        unpack_table(
            ferc1_df=ferc1_raw_dfs["plant_in_service_ferc1"],
            table_name="f1_plant_in_srvce",
            data_rows=slice(None),  // Gotta catch "em all!
            data_cols=[
                "begin_yr_bal",
                "addition",
                "retirements",
                "adjustments",
                "transfers",
                "yr_end_bal"
            ])
        .pipe(  // Convert top level of column index into a categorical column:
            cols_to_cats,
            cat_name="amount_type",
            col_cats={
                "begin_yr_bal": "starting_balance",
                "addition": "additions",
                "retirements": "retirements",
                "adjustments": "adjustments",
                "transfers": "transfers",
                "yr_end_bal": "ending_balance",
            })
        .rename_axis(columns=None)
        .pipe(_clean_cols, "f1_plant_in_srvce")
        .set_index([
            "utility_id_ferc1",
            "report_year",
            "amount_type",
            "record_id"])
        .reset_index()
    )

    // Get rid of the columns corresponding to "header" rows in the FERC
    // form, which should *never* contain data... but in about 2 dozen cases,
    // they do. See this issue on Github for more information:

Instances