Event News
Added May 27, 2021

Event highlights: How to use Python to turn the tide

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Vortexa’s Python Software Development Kit (SDK) allows you to explore real-time global waterborne oil and LNG movements with minimal coding knowledge and setup costs.

In this webinar, Vortexa’s industry experts Amy Lees, Product Specialist and Christos Hadjinikolis, Senior Software Engineer, explored how to effectively use the SDK to interrogate extensive cargo movements data (over 2000 crude movements spanning a 2 year period) and analysed clear trends in the quality of the crude slate going into ARA (Amsterdam, Rotterdam, Antwerp). 

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The Vortexa Analytics platform and SDK work cohesively together to surface invaluable and unique data insights to inform critical trading decisions. This webinar demonstrates the power of harnessing both Vortexa products in tandem, by exploring how to evaluate crude imports into the ARA using Python, and how to utilise data analytics to edge out competitors. The SDK offers greater flexibility and even more data than Vortexa’s analytics platform; allowing clients to look at specific API and sulphur qualities of different crude grades. 

The webinar focused on three principal areas including:

  • Using Python in the energy trading industry
  • Crude flows, specifically into the ARA Region
  • Data analysis benefits for market players
Core takeaways from the session:
  • Downward trend in sulphur content of the crude grades going into ARA
Screenshot 2021-05-27 at 14.40.17

  • Upward trend in the average API of crude grades going into ARA 

Screenshot 2021-05-27 at 14.40.33

  • This means that the overall crude slate for ARA refiners is lighter and sweeter 
  • Python SDK is superior to Excel when quickly analysing extensive datasets 
  • Vortexa’s API and Python SDK can be used to extrapolate data for any product, time period or region in real-time
What to expect from the Python SDK 
  • Analysts can examine the world’s waterborne oil LNG movements with minimum coding knowledge. Clear examples lead users along a gradual learning curve.
  • Data Scientists can use an interactive python toolkit, deeply integrated with pandas. Data Scientists can use the SDK to efficiently combine multiple data sources, and methodically extract features relevant to both production & prototype models.
  • Software & Data Engineers can rely on a modular, clean, test-driven, open-source SDK, built & maintained by a committed team of world-class engineers. We welcome contributions, please check out our contributing guide!

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