Let's find some laden vessel movements
The below script returns:
| vessel.name | vessel.imo | vessel.mmsi | vessel.cubic_capacity | vessel.dwt | vessel.vessel_class | origin.location.port.label | origin.location.sts_zone.label | origin.from_vessel.label | origin.to_vessel.label | destination.location.port.label | destination.location.sts_zone.label | destination.from_vessel.label | destination.to_vessel.label | origin.start_timestamp | destination.end_timestamp | cargoes.0.product.group.label | cargoes.0.product.grade.label | cargoes.0.product.grade.probability | vessel.corporate_entities.charterer.label | vessel.corporate_entities.time_charterer.label | vessel.corporate_entities.effective_controller.label | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 17 FEBRUARY | 9.38089e+06 | 248896000 | 172092 | 160391 | suezmax | Ras Tanura [SA] | nan | nan | nan | Malacca (Melaka) [MY] | nan | nan | nan | 2017-09-29T18:30:01+0000 | 2017-10-16T04:06:03+0000 | Crude | Arab Light | 0.299732 | nan | nan | CORE PETROLEUM |
| 3 | A MELODY | 9.24931e+06 | 636019335 | 169352 | 149995 | suezmax | Ras Tanura [SA] | nan | nan | nan | Rayong [TH] | nan | nan | nan | 2017-09-20T09:15:15+0000 | 2017-10-09T20:07:28+0000 | Crude | Arab Light | 0.903729 | THAI OIL | nan | LMCS Maritime |
| 4 | A STAR | 9.00660e+06 | 511801000 | 333924 | 291381 | vlcc_plus | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2017-10-08T14:50:01+0000 | Crude | nan | nan | nan | nan | nan |
| 5 | A STAR | 9.15982e+06 | 356206000 | 9716 | 11047 | general_purpose | Shahid Rajaee Port (Bandar Abbas) [IR] | nan | nan | nan | Haldia [IN] | nan | nan | nan | 2017-09-23T23:59:30+0000 | 2017-10-16T01:49:00+0000 | Dirty products | Bitumen | 1 | nan | nan | nan |
| 10 | ABDIAS NASCIMENTO | 9.4539e+06 | 710032990 | 171000 | 157055 | suezmax | Marlim Sul Field [BR] | nan | nan | nan | Sao Francisco Do Sul, SC [BR] | nan | nan | nan | 2017-09-28T18:29:45+0000 | 2017-10-04T23:05:32+0000 | Crude | nan | nan | nan | nan | PETROBRAS |
| 11 | ABIOLA | 8.61943e+06 | 657995000 | 47261 | 35644 | handysize | Port Harcourt [NG] | nan | nan | nan | nan | nan | nan | nan | 2014-12-02T10:20:03+0000 | nan | Clean products | Full Range | 0.490481 | nan | nan | nan |
| 13 | ABLIANI | 9.69307e+06 | 256903000 | 124518 | 109999 | aframax | Ceyhan [TR] | nan | nan | nan | Sarroch (Porto Foxi) [IT] | nan | nan | nan | 2017-09-26T21:33:43+0000 | 2017-10-03T15:45:15+0000 | Crude | Azeri Light | 1 | nan | nan | Eastern Mediterranean Maritime Ltd |
| 19 | AC-D | 9.42844e+06 | 256934000 | 8628 | 7842 | tiny_tanker | Varna [BG] | nan | nan | nan | Valencia [ES] | nan | nan | nan | 2017-09-20T08:00:58+0000 | 2017-10-06T15:49:00+0000 | Clean products | Finished Biodiesel | 0.868073 | nan | nan | nan |
| 20 | ACACIA | 9.4766e+06 | 371044000 | 14570 | 13566 | general_purpose | Bontang, KL [ID] | nan | nan | nan | Lianyungang [CN] | nan | nan | nan | 2017-09-28T13:13:57+0000 | 2017-10-07T00:30:46+0000 | Clean products | Chemicals | 0.999186 | nan | nan | KOKUKA SANGYO |
| 22 | ACACIA RUBRA | 9.46853e+06 | 249374000 | 6000 | 6065 | tiny_tanker | Mosjoen [NO] | nan | nan | nan | Sigerfjord [NO] | nan | nan | nan | 2017-10-01T00:01:53+0000 | 2017-10-06T10:53:20+0000 | Dirty products | nan | nan | nan | nan | nan |
from datetime import datetime
from vortexasdk import VesselMovements
if __name__ == "__main__":
# Query the API
search_result = VesselMovements().search(
filter_time_min=datetime(2017, 10, 1, 0),
filter_time_max=datetime(2017, 10, 1, 1),
)
# A complete list of available columns can be found at https://vortechsa.github.io/python-sdk/endpoints/vessel_movements/#notes
# We only require a subset of available columns here
required_columns = [
# Show metadata about the vessel
"vessel.name",
"vessel.imo",
"vessel.mmsi",
"vessel.cubic_capacity",
"vessel.dwt",
"vessel.vessel_class",
# Show any corporate information associated with the vessel
"vessel.corporate_entities.charterer.label",
"vessel.corporate_entities.time_charterer.label",
"vessel.corporate_entities.effective_controller.label",
# Show the port, sts_zone, or vessel at the start of the vessel movement
"origin.location.port.label",
"origin.location.sts_zone.label",
"origin.from_vessel.label",
"origin.to_vessel.label",
# Show the port, sts_zone, or vessel at the end of the vessel movement
"destination.location.port.label",
"destination.location.sts_zone.label",
"destination.from_vessel.label",
"destination.to_vessel.label",
# The start and end timestamps of the movement
"origin.start_timestamp",
"destination.end_timestamp",
# The cargo (if any), onboard the vessel during the vessel movement.
# If the vessel was balast, then the cargo will be empty.
"cargoes.0.product.group.label",
"cargoes.0.product.grade.label",
"cargoes.0.product.grade.probability",
]
# Convert the search result to a dataframe
vessel_movements = search_result.to_df(columns=required_columns)
# Laden vessel movements are movements with a cargo (unlike ballast movements, where the vessel isn't carrying any cargo).
is_laden_mask = vessel_movements["cargoes.0.product.group.label"].notna()
# Let's find the laden vessel movements.
laden_vessel_movements = vessel_movements[is_laden_mask]