vortexasdk.endpoints.fleet_utilisation_quantity_timeseries

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FleetUtilisationQuantityTimeseries

FleetUtilisationQuantityTimeseries(self)

Please note: you will require a subscription to our Freight module to access this endpoint.

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FleetUtilisationQuantityTimeseries.search(self, timeseries_frequency: str = None, timeseries_unit: str = None, timeseries_property: str = None, filter_products: Union[str, List[str]] = None, filter_charterers: Union[str, List[str]] = None, filter_owners: Union[str, List[str]] = None, filter_origins: Union[str, List[str]] = None, filter_destinations: Union[str, List[str]] = None, filter_vessels: Union[str, List[str]] = None, filter_vessel_classes: Union[str, List[str]] = None, filter_vessel_flags: Union[str, List[str]] = None, filter_vessel_ice_class: Union[str, List[str]] = None, filter_vessel_propulsion: Union[str, List[str]] = None, filter_vessel_tags: Union[List[vortexasdk.api.shared_types.Tag], vortexasdk.api.shared_types.Tag] = None, filter_vessel_risk_levels: Union[str, List[str]] = None, filter_vessel_scrubbers: str = 'disabled', filter_vessel_age_min: int = None, filter_vessel_age_max: int = None, filter_vessel_dwt_min: int = None, filter_vessel_dwt_max: int = None, filter_ship_to_ship: bool = None, filter_charterer_exists: bool = None, filter_activity: str = None, filter_time_min: datetime.datetime = datetime.datetime(2019, 10, 1, 0, 0), filter_time_max: datetime.datetime = datetime.datetime(2019, 10, 1, 1, 0), filter_vessel_status: Union[str, List[str]] = None, exclude_origins: Union[str, List[str]] = None, exclude_destinations: Union[str, List[str]] = None, exclude_products: Union[str, List[str]] = None, exclude_vessels: Union[str, List[str]] = None, exclude_vessel_classes: Union[str, List[str]] = None, exclude_charterers: Union[str, List[str]] = None, exclude_owners: Union[str, List[str]] = None, exclude_vessel_flags: Union[str, List[str]] = None, exclude_vessel_ice_class: Union[str, List[str]] = None, exclude_vessel_propulsion: Union[str, List[str]] = None, exclude_vessel_tags: Union[List[vortexasdk.api.shared_types.Tag], vortexasdk.api.shared_types.Tag] = None, exclude_vessel_risk_levels: Union[str, List[str]] = None) -> vortexasdk.endpoints.breakdown_result.BreakdownResult

Sum of cargoes quantity for each day. For frequencies other than ‘day’, the values returned are calculated by summing each daily cargo quantity bucket and returning the total.

Arguments

  • timeseries_unit: A numeric metric to be calculated for each time bucket. Must be one of 'b', 'bpd', 't', 'tpd', 'c', 'cpd', corresponding to barrels, barrels per day, metric tonnes, metric tonnes per day, cargo movement count, cargo movement count per day, respectively.

  • timeseries_frequency: Frequency denoting the granularity of the time series. Must be one of the following: 'day', 'week', 'doe_week', 'month', 'quarter', 'year'.

  • timeseries_property: Property on the vessel movement used to build the value of the aggregation. By default it is “quantity”. Must be one of the following: 'quantity’, ‘vessel_class’, ‘vessel_flag’, ‘origin_region’, ‘origin_trading_region’, ‘origin_trading_sub_region’, ‘origin_country’, ‘origin_port’, ‘origin_terminal’, ‘destination_region’, ‘destination_trading_region’, ‘destination_trading_sub_region’, ‘destination_country’, ‘destination_port’, ‘destination_terminal’, 'product_group', 'product_group_product', 'product_category', 'product_grade'.

  • filter_time_min: The UTC start date of the time filter.

  • filter_time_max: The UTC end date of the time filter.

  • filter_products: A product ID, or list of product IDs to filter on.

  • filter_charterers: A charterer entity ID, or list of product IDs to filter on.

  • filter_owners: An owner ID, or list of owner IDs to filter on.

  • filter_origins: A geography ID, or list of geography IDs to filter on.

  • filter_destinations: A geography ID, or list of geography IDs to filter on.

  • filter_vessels: A vessel ID, or list of vessel IDs to filter on.

  • filter_vessel_classes: A vessel class, or list of vessel classes to filter on.

  • filter_vessel_flags: A vessel flag ID, or list of vessel flag IDs to filter on.

  • filter_vessel_ice_class: A vessel ice class ID, or list of vessel ice class IDs to filter on.

  • filter_vessel_propulsion: A vessel propulsion ID, or list of vessel propulsion IDs to filter on.

  • filter_vessel_tag: A time bound vessel tag, or list of time bound vessel tags to filter on.

  • filter_vessel_risk_levels: A vessel risk level, or list of vessel risk levels to filter on.

  • filter_vessel_scrubbers: Either inactive 'disabled', or included 'inc' or excluded 'exc'.

  • filter_vessel_age_min: A number between 1 and 100 (representing years).

  • filter_vessel_age_max: A number between 1 and 100 (representing years).

  • filter_vessel_age_min: A number between 0 and 550000.

  • filter_vessel_age_max: A number between 0 and 550000.

  • filter_activity: Movement activity on which to base the time filter. Must be one of: 'loading_state', 'oil_on_water_state', 'unloading_state', 'ship_to_ship', 'storing_state', 'transiting_state'

  • filter_vessel_status: The vessel status on which to base the filter. Enter 'vessel_status_ballast' for ballast vessels, 'vessel_status_laden_known' for laden vessels with known cargo (i.e. a type of cargo that Vortexa currently tracks) or 'any_activity' for any other vessels.

  • filter_charterer_exists: A boolean to include or exclude the records to those that have a charterer.

  • filter_ship_to_ship: A boolean to include or exclude the records to those that are involved in an STS.

  • exclude_filter_products: A product ID, or list of product IDs to exclude.

  • exclude_filter_charterers: A charterer entity ID, or list of product IDs to exclude.

  • exclude_filter_owners: An owner ID, or list of owner IDs to exclude.

  • exclude_filter_origins: A geography ID, or list of geography IDs to exclude.

  • exclude_filter_destinations: A geography ID, or list of geography IDs to exclude.

  • exclude_filter_vessels: A vessel ID, or list of vessel IDs to exclude.

  • exclude_filter_vessel_classes: A vessel class, or list of vessel classes to exclude.

  • exclude_filter_vessel_ice_class: A vessel ice class ID, or list of vessel ice class IDs to exclude.

  • exclude_filter_vessel_propulsion: A vessel propulsion ID, or list of vessel propulsion IDs to exclude.

  • exclude_filter_vessel_tag: A time bound vessel tag, or list of time bound vessel tags to exclude.

  • exclude_filter_vessel_risk_levels: A vessel risk level, or list of vessel risk levels to exclude.

Returns

BreakdownResult

Example

Ton days demand of vessels from the Middle East over the last 7 days.

>>> from vortexasdk import FleetUtilisationQuantityTimeseries
>>> from datetime import datetime
>>> search_result = FleetUtilisationQuantityTimeseries().search(
...    filter_vessel_status="vessel_status_laden_known",
...    filter_origins="80aa9e4f3014c3d96559c8e642157edbb2b684ea0144ed76cd20b3af75110877",
...    filter_time_min=datetime(2021, 1, 11),
...    filter_time_max=datetime(2021, 1, 18),
...    timeseries_unit="t",
...    timeseries_frequency="day",
...    timeseries_property="quantity")
>>> df = search_result.to_df()

Gives the following:

key value count breakdown.0.label breakdown.0.value breakdown.0.count
7 2021-01-18 00:00:00+00:00 69661114 688 "quantity" 69661114 688
0 2021-01-11 00:00:00+00:00 73208724 738 "quantity" 73208724 738
1 2021-01-12 00:00:00+00:00 73586280 732 "quantity" 73586280 732
2 2021-01-13 00:00:00+00:00 74638888 736 "quantity" 74638888 736
3 2021-01-14 00:00:00+00:00 74958932 746 "quantity" 74958932 746
4 2021-01-15 00:00:00+00:00 74230202 737 "quantity" 74230202 737
5 2021-01-16 00:00:00+00:00 73723336 738 "quantity" 73723336 738
6 2021-01-17 00:00:00+00:00 74216473 751 "quantity" 74216473 751