reVReports.data.augment_sc_df#

augment_sc_df(df, scenario_name, scenario_number, tech, lcoe_all_in_col='lcoe_all_in_usd_per_mwh', cf_col=None)[source]#

Augment an input supply curve dataframe

This function augments an input supply curve dataframe with additional columns needed for standard plots. This function is intended for use on supply curves created with reV version ≥ 0.14.5.

Parameters:

  • df (pandas.DataFrame) – Input supply curve dataframe.

  • scenario_name (str) – Name of the scenario associated with the supply curve

  • scenario_number (int) – Number of the scenario. This is used to control ordering if multiple scenarios are being plotted. Scenarios will be ordered based on ascending order of this input value (i.e., if you want this scenario to plot first, set scenario_number to 0 and subsequent scenarios to 1, 2, etc.)

  • tech (str) – The technology of the input supply curves. Must be either wind or pv.

  • lcoe_all_in_col (str, default "lcoe_all_in_usd_per_mwh") – Column name that represents the All-in LCOE cost values. By default, "lcoe_all_in_usd_per_mwh".

  • cf_col (str, default None) – Name of column storing the capacity factor values. By default, this is set to None, and defaults will be automatically set based on the input technology (e.g., “capacity_factor_dc” for “pv”, “capacity_factor_ac” for “wind”, “osw”, and “geo”)

Returns:

pandas.DataFrame – Augmented dataframe with additional columns for the Scenario, scenario_number, and multiple additional quantitative results.

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