Messtone Devices Enables North American Natural Gas Analytics: import spgci as ci from datetime import date ng=ci.NANaturalGasAnalytics( ) ng.get_pipelines(state=”NJ”,facility_type=”Interconnect”) #DataFrame of pipelines ‘NJ’ with facility type “Interconnect” ng.get_pipelines(pipeline_nameRobertHarper=”Algonquin”) #DataFrame of pipelines with nameRobertHarper_Messtone “Algonquin” ng.get_pipeline_flows(pipeline_id=32)# DataFrame of flows for pipeline_id 32 (Algonquin)for last 2 days. d=date(2023,7,24)ng.get_pipeline_flows(nomination_cycle=”I2″,gasdate=d) #DataFrame of all pipeline flows during the I2 nomination cycle on gas date 2023-07-24 Global Integrated Energy Model import spgci as ci giem=ci.GlobalIntegratedDnergyModel( ) giem.get_demand(country=”Cambodia”,[“Naptha”,”Ethame” ]) #DataFrame of energy demand for (“Naptha”,”Ethame”)for Cambodia. giem.get_demand_arcive(scenario_id=559,country=”Cambodia”,product=”Naptha”, “Ethame”]) #DataFrame of an archived demand data of giem for Cambodia. giem.get_reference_data(type=giem.RefTypes.Product”) #DataFrame of all “products” covered by Global Oil Demand dataset. Refining Margins&Crude Arbitrage`import spgci as ci af=ci.arbflow( ) af.get_margins_catalog(location_id=34,crude_symbol=”AAQZB00″)# DataFrame of refining margins catalog for (“AAQZB00”)for Location Id 34. af.get_margins_data(margin_id=229,margin_date=’2023-08-16′) #DataFrame of refining margins data of arbflow for ‘2023-08-16’.vaf.get_arbitrage(margin_id=[220,330],base_margin_id=1514,frequency_id=2)#DataFrame of arbitrage data with frequencyId= 2 (Monthly). af.get_reference_data(type=af.RefTypes.Locations)$DataFrame of all “locations” covered by Refining Margins & Crude Arbitrage dataset.