leaf_engine.etl.fuel

This module calculates fuel-related columns. The ‘estimate…’ functions can also be used directly in the mappings.

Functions

_get_fuel_price(→ pandas.DataFrame)

estimate_fuel_surcharge(→ pandas.Series)

param df:

<DataFrame> shipments to operate on. Must contain:

estimate_linehaul(→ pandas.Series)

Calculates linehaul from spend, FSC, and accessorials.

estimate_linehaul_zero_peg(→ pandas.Series)

Calculates the baseline (zero peg) fuel costs baked into the linehaul.

fuel_pipeline(df)

Module Contents

leaf_engine.etl.fuel._get_fuel_price() → pandas.DataFrame
Return type:

pandas.DataFrame

leaf_engine.etl.fuel.estimate_fuel_surcharge(df: pandas.DataFrame, mileage: str = 'company_miles') → pandas.Series
Parameters:

  • df (pandas.DataFrame) – <DataFrame> shipments to operate on. Must contain:

  • df['fuel_increment'] – <float> bucket/step size to hit for charge increase.

  • df['charge_increment'] – <float> amount to raise the fuel charge.

  • mileage (str) –

Returns:

<Series> fuel surcharge column.

Return type:

df[‘fuel_surcharge’]

leaf_engine.etl.fuel.estimate_linehaul(df: pandas.DataFrame) → pandas.Series

Calculates linehaul from spend, FSC, and accessorials.

Args: df: <DataFrame> with linehaul, spend, and FSC columns.

Returns: df[‘linehaul’]: <Series> linehaul column.

Parameters:

df (pandas.DataFrame) –

Return type:

pandas.Series

leaf_engine.etl.fuel.estimate_linehaul_zero_peg(df: pandas.DataFrame, mileage: str = 'company_miles') → pandas.Series

Calculates the baseline (zero peg) fuel costs baked into the linehaul. Subtracts those costs from the linehaul and saves the delta to ‘linehaul_zero_peg’.

Args: df: <DataFrame> with linehaul, mileage, and fuel schedule columns. mileage: <String> of the name of the column containing mileage (defaults to ‘company_miles’ at mapping stage, else uses ‘pcm_miles’).

Returns: df[‘linehaul_zero_peg’]: <Series> linehaul_zero_peg column.

Parameters:
Return type:

pandas.Series

leaf_engine.etl.fuel.fuel_pipeline(df)