Arming commodity experts with Vortexa’s Python SDK
Data Scientists care about data science, not engineering. Analysts need clear information at their fingertips, without hassle. Good engineers care deeply about the longevity of the systems they build, and waste no time with unnecessary low-level details.
Who should read this?
Analystsstarting to code
Data Scientiststhat would prefer to focus on science
10xEngineersthat expect effective abstractions
Modern data science requires both surgical precision and broad stroke data collection. Algorithms often need vast amounts of data to function effectively, while algorithm builders need pinpoint control to inspect the finer details.
It’s no small feat to navigate through millions of global waterborne oil movements. It requires a keen eye and a fair degree of patience to explore live ship-to-ship transfers, terminal-level cargo imports, and historic national export figures.
Asdiscussed earlier, there are multiple ways to access our data. Here we will focus on Vortexa’s Python SDK.
Analystscan examine the world’s waterborne oil movements with minimum coding knowledge.Clear exampleslead users along a gradual learning curve.
Data Scientistscan 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 Engineerscan rely on a modular, clean, test-driven, open-source SDK, built &maintainedby a committed team of world-class engineers. We welcome contributions, please check out ourcontributing guide!
As a Data Scientist myself, it’s an interesting time to be in the industry. Data Scientists are becoming increasingly redundant, yet increasingly powerful at the same time. Advances inAutoMLand tools likeLudwigallow you to build production-grade machine learning models in only a few lines of code.
Such powerful tooling lets us focus on understanding the data itself, doing away with details concerning hyper-parameter optimisation or type detection.
The SDK also aligns with this tool-driven mindset. At Vortexa, we’ve found it invaluable to build powerful tooling that simplifies the process of handling data. We hope you find the SDK similarly valuable.