compute

Functions

`_write_result_to_csv`(result, file_name)
`get_carrier_churn_lanes`(→ pandas.DataFrame)
`get_contract_weight`(→ float)
`get_corridor_candidates`(→ pandas.DataFrame)
`get_corridor_oppys`(→ pandas.DataFrame)
`get_dashboard_kpis`(→ pandas.DataFrame)
`get_dat_trend_rolling`(→ pandas.DataFrame)
`get_final_candidate_total_alloc`(→ pandas.DataFrame)
`get_flex_candidates`(→ pandas.DataFrame)
`get_flex_oppys`(→ pandas.DataFrame)
`get_forecast_day_cutoff`(→ int)
`get_high_spend_vol_lanes`(→ pandas.DataFrame)
`get_high_vol_lanes`(→ pandas.DataFrame)
`get_kma_markets`(→ pandas.DataFrame)
`get_lane_daily_loads`(→ pandas.DataFrame)
`get_load_actual_mkt_lh`(→ pandas.DataFrame)
`get_load_dat_lh`(→ pandas.DataFrame)
`get_load_dat_trend`(→ pandas.DataFrame)
`get_load_pga_revenue`(→ pandas.DataFrame)
`get_loads_mkt`(→ pandas.DataFrame)
`get_mkt_18mo_max_rpm`(→ float)
`get_mkt_18mo_mean_rpm`(→ float)
`get_mkt_current_rpm`(→ float)
`get_mkt_max_mean`(→ pandas.DataFrame)
`get_network_candidates`(→ pandas.DataFrame)
`get_network_oppys`(→ pandas.DataFrame)
`get_oppy_metrics`(→ pandas.DataFrame)
`get_origin_risk`(→ pandas.DataFrame)
`get_overall_spend_variability`(→ float)
`get_power_lane_annual_lh_loads`(→ pandas.DataFrame)
`get_power_lane_fleet_type`(→ pandas.DataFrame)
`get_power_lane_name`(→ pandas.DataFrame)
`get_risk_metrics`(→ pandas.DataFrame)
`get_rpm_trend_w_fcst`(→ pandas.DataFrame)
`get_ship_rate_day_cutoff`(→ int)
`get_spend_variability_breakdown`(→ pandas.DataFrame)
`get_spot_weight`(→ pandas.DataFrame)
`get_top_lanes`(→ pandas.DataFrame)
`get_total_daily_revenue`(→ pandas.DataFrame)
`get_total_spend_trend_w_fcst`(→ pandas.DataFrame)
`get_total_variability`(→ float)
`get_trip_type_weighting`(→ pandas.DataFrame)
`get_window_start_date`(→ datetime.datetime)

Module Contents

compute._write_result_to_csv(result: pandas.DataFrame, file_name: str)

Parameters:

result (pandas.DataFrame) –
file_name (str) –

compute.get_carrier_churn_lanes(gtm_loads: pandas.DataFrame, window_start_date: datetime.datetime) → pandas.DataFrame

Parameters:

gtm_loads (pandas.DataFrame) –
window_start_date (datetime.datetime) –

Return type:

pandas.DataFrame

compute.get_contract_weight(spot_weight: float) → float

Parameters:: spot_weight (float) –
Return type:: float

compute.get_corridor_candidates(load_dat_lh: pandas.DataFrame, corridors: pandas.DataFrame) → pandas.DataFrame

Parameters:

load_dat_lh (pandas.DataFrame) –
corridors (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_corridor_oppys(corridor_candidates: pandas.DataFrame, power_lane_annual_lh_loads: pandas.DataFrame) → pandas.DataFrame

Parameters:

corridor_candidates (pandas.DataFrame) –
power_lane_annual_lh_loads (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_dashboard_kpis(load_actual_mkt_lh: pandas.DataFrame, window_start_date: datetime.datetime, pga_loads: pandas.DataFrame, load_dat_lh: pandas.DataFrame, overall_spend_variability: float, total_variability: float, total_daily_revenue: pandas.DataFrame) → pandas.DataFrame

Parameters:

load_actual_mkt_lh (pandas.DataFrame) –
window_start_date (datetime.datetime) –
pga_loads (pandas.DataFrame) –
load_dat_lh (pandas.DataFrame) –
overall_spend_variability (float) –
total_variability (float) –
total_daily_revenue (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_dat_trend_rolling(dat_trend: pandas.DataFrame) → pandas.DataFrame

Parameters:: dat_trend (pandas.DataFrame) –
Return type:: pandas.DataFrame

compute.get_final_candidate_total_alloc(load_dat_lh: pandas.DataFrame, corridor_candidates: pandas.DataFrame, flex_candidates: pandas.DataFrame, network_candidates: pandas.DataFrame, power_lane_fleet_type: pandas.DataFrame) → pandas.DataFrame

Parameters:

load_dat_lh (pandas.DataFrame) –
corridor_candidates (pandas.DataFrame) –
flex_candidates (pandas.DataFrame) –
network_candidates (pandas.DataFrame) –
power_lane_fleet_type (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_flex_candidates(lane_quick_ref: pandas.DataFrame, load_dat_lh: pandas.DataFrame) → pandas.DataFrame

Parameters:

lane_quick_ref (pandas.DataFrame) –
load_dat_lh (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_flex_oppys(flex_candidates: pandas.DataFrame, power_lane_annual_lh_loads: pandas.DataFrame) → pandas.DataFrame

Parameters:

flex_candidates (pandas.DataFrame) –
power_lane_annual_lh_loads (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_forecast_day_cutoff() → int

Return type:: int

compute.get_high_spend_vol_lanes(load_actual_mkt_lh: pandas.DataFrame, window_start_date: datetime.datetime, power_lane_name: pandas.DataFrame) → pandas.DataFrame

Parameters:

load_actual_mkt_lh (pandas.DataFrame) –
window_start_date (datetime.datetime) –
power_lane_name (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_high_vol_lanes(power_lane_load_vol: pandas.DataFrame, lane_daily_loads: pandas.DataFrame, load_actual_mkt_lh: pandas.DataFrame, power_lane_name: pandas.DataFrame) → pandas.DataFrame

Parameters:

power_lane_load_vol (pandas.DataFrame) –
lane_daily_loads (pandas.DataFrame) –
load_actual_mkt_lh (pandas.DataFrame) –
power_lane_name (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_kma_markets() → pandas.DataFrame

Return type:: pandas.DataFrame

compute.get_lane_daily_loads(load_dat_lh: pandas.DataFrame) → pandas.DataFrame

Parameters:: load_dat_lh (pandas.DataFrame) –
Return type:: pandas.DataFrame

compute.get_load_actual_mkt_lh(power_lane_fleet_type: pandas.DataFrame, load_dat_trend: pandas.DataFrame, load_dat_lh: pandas.DataFrame, dat_trend: pandas.DataFrame, window_start_date: datetime.datetime, spot_weight: float, contract_weight: float) → pandas.DataFrame

Parameters:

power_lane_fleet_type (pandas.DataFrame) –
load_dat_trend (pandas.DataFrame) –
load_dat_lh (pandas.DataFrame) –
dat_trend (pandas.DataFrame) –
window_start_date (datetime.datetime) –
spot_weight (float) –
contract_weight (float) –

Return type:

pandas.DataFrame

compute.get_load_dat_lh(dat_table: pandas.DataFrame, kma_markets: pandas.DataFrame, loads_mkt: pandas.DataFrame, ship_rate_day_cutoff: int) → pandas.DataFrame

Parameters:

dat_table (pandas.DataFrame) –
kma_markets (pandas.DataFrame) –
loads_mkt (pandas.DataFrame) –
ship_rate_day_cutoff (int) –

Return type:

pandas.DataFrame

compute.get_load_dat_trend(dat_trend_rolling: pandas.DataFrame, load_dat_lh: pandas.DataFrame) → pandas.DataFrame

Parameters:

dat_trend_rolling (pandas.DataFrame) –
load_dat_lh (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_load_pga_revenue(load_dat_lh: pandas.DataFrame) → pandas.DataFrame

Parameters:: load_dat_lh (pandas.DataFrame) –
Return type:: pandas.DataFrame

compute.get_loads_mkt(gtm_loads: pandas.DataFrame, kma_markets: pandas.DataFrame) → pandas.DataFrame

Parameters:

gtm_loads (pandas.DataFrame) –
kma_markets (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_mkt_18mo_max_rpm(dat_trend_rolling: pandas.DataFrame, trip_type_weighting: pandas.DataFrame, contract_weight: float, spot_weight: float) → float

Parameters:

dat_trend_rolling (pandas.DataFrame) –
trip_type_weighting (pandas.DataFrame) –
contract_weight (float) –
spot_weight (float) –

Return type:

float

compute.get_mkt_18mo_mean_rpm(dat_trend_rolling: pandas.DataFrame, trip_type_weighting: pandas.DataFrame, contract_weight: float, spot_weight: float) → float

Parameters:

dat_trend_rolling (pandas.DataFrame) –
trip_type_weighting (pandas.DataFrame) –
contract_weight (float) –
spot_weight (float) –

Return type:

float

compute.get_mkt_current_rpm(dat_trend_rolling: pandas.DataFrame, trip_type_weighting: pandas.DataFrame, contract_weight: float, spot_weight: float) → float

Parameters:

dat_trend_rolling (pandas.DataFrame) –
trip_type_weighting (pandas.DataFrame) –
contract_weight (float) –
spot_weight (float) –

Return type:

float

compute.get_mkt_max_mean(load_dat_lh: pandas.DataFrame, mkt_18mo_mean_rpm: float, mkt_18mo_max_rpm: float, mkt_current_rpm: float) → pandas.DataFrame

Parameters:

load_dat_lh (pandas.DataFrame) –
mkt_18mo_mean_rpm (float) –
mkt_18mo_max_rpm (float) –
mkt_current_rpm (float) –

Return type:

pandas.DataFrame

compute.get_network_candidates(network_moves: pandas.DataFrame, lane_quick_ref: pandas.DataFrame) → pandas.DataFrame

Parameters:

network_moves (pandas.DataFrame) –
lane_quick_ref (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_network_oppys(network_candidates: pandas.DataFrame, power_lane_annual_lh_loads: pandas.DataFrame) → pandas.DataFrame

Parameters:

network_candidates (pandas.DataFrame) –
power_lane_annual_lh_loads (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_oppy_metrics(corridor_oppys: pandas.DataFrame, flex_oppys: pandas.DataFrame, network_oppys: pandas.DataFrame) → pandas.DataFrame

Parameters:

corridor_oppys (pandas.DataFrame) –
flex_oppys (pandas.DataFrame) –
network_oppys (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_origin_risk(high_vol_lanes: pandas.DataFrame, lane_quick_ref: pandas.DataFrame, carrier_churn_lanes: pandas.DataFrame, high_spend_vol_lanes: pandas.DataFrame) → pandas.DataFrame

Parameters:

high_vol_lanes (pandas.DataFrame) –
lane_quick_ref (pandas.DataFrame) –
carrier_churn_lanes (pandas.DataFrame) –
high_spend_vol_lanes (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_overall_spend_variability(load_actual_mkt_lh: pandas.DataFrame, window_start_date: datetime.datetime) → float

Parameters:

load_actual_mkt_lh (pandas.DataFrame) –
window_start_date (datetime.datetime) –

Return type:

float

compute.get_power_lane_annual_lh_loads(load_actual_mkt_lh: pandas.DataFrame, power_lane_name: pandas.DataFrame) → pandas.DataFrame

Parameters:

load_actual_mkt_lh (pandas.DataFrame) –
power_lane_name (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_power_lane_fleet_type(load_dat_lh: pandas.DataFrame) → pandas.DataFrame

Parameters:: load_dat_lh (pandas.DataFrame) –
Return type:: pandas.DataFrame

compute.get_power_lane_name(lane_quick_ref: pandas.DataFrame) → pandas.DataFrame

Parameters:: lane_quick_ref (pandas.DataFrame) –
Return type:: pandas.DataFrame

compute.get_risk_metrics(high_vol_lanes: pandas.DataFrame, carrier_churn_lanes: pandas.DataFrame, high_spend_vol_lanes: pandas.DataFrame) → pandas.DataFrame

Parameters:

high_vol_lanes (pandas.DataFrame) –
carrier_churn_lanes (pandas.DataFrame) –
high_spend_vol_lanes (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_rpm_trend_w_fcst(load_actual_mkt_lh: pandas.DataFrame, spot_weight: float, contract_weight: float, window_start_date: datetime.datetime, top_lanes: pandas.DataFrame, current_forecast: pandas.DataFrame, mkt_18mo_mean_rpm: float, mkt_18mo_max_rpm: float, mkt_current_rpm: float) → pandas.DataFrame

Parameters:

load_actual_mkt_lh (pandas.DataFrame) –
spot_weight (float) –
contract_weight (float) –
window_start_date (datetime.datetime) –
top_lanes (pandas.DataFrame) –
current_forecast (pandas.DataFrame) –
mkt_18mo_mean_rpm (float) –
mkt_18mo_max_rpm (float) –
mkt_current_rpm (float) –

Return type:

pandas.DataFrame

compute.get_ship_rate_day_cutoff() → int

Return type:: int

compute.get_spend_variability_breakdown(lane_daily_loads: pandas.DataFrame, window_start_date: datetime.datetime, load_pga_revenue: pandas.DataFrame, overall_spend_variability: float, total_variability: float) → pandas.DataFrame

Parameters:

lane_daily_loads (pandas.DataFrame) –
window_start_date (datetime.datetime) –
load_pga_revenue (pandas.DataFrame) –
overall_spend_variability (float) –
total_variability (float) –

Return type:

pandas.DataFrame

compute.get_spot_weight(load_dat_lh: pandas.DataFrame) → pandas.DataFrame

Parameters:: load_dat_lh (pandas.DataFrame) –
Return type:: pandas.DataFrame

compute.get_top_lanes(load_actual_mkt_lh: pandas.DataFrame) → pandas.DataFrame

Parameters:: load_actual_mkt_lh (pandas.DataFrame) –
Return type:: pandas.DataFrame

compute.get_total_daily_revenue(lane_daily_loads: pandas.DataFrame, load_pga_revenue: pandas.DataFrame) → pandas.DataFrame

Parameters:

lane_daily_loads (pandas.DataFrame) –
load_pga_revenue (pandas.DataFrame) –

Return type:

pandas.DataFrame

compute.get_total_spend_trend_w_fcst(load_actual_mkt_lh: pandas.DataFrame, window_start_date: datetime.datetime, load_pga_revenue: pandas.DataFrame, top_lanes: pandas.DataFrame, lane_daily_loads: pandas.DataFrame, spot_weight: float, contract_weight: float, mkt_18mo_mean_rpm: float, mkt_18mo_max_rpm: float, mkt_current_rpm: float) → pandas.DataFrame