Time Series Analysis in Python: Easy Tools for Scientific Insight

(Muhammad Sakib Khan Inan, Rubaiath E Ulfath) Time series data is everywhere. Across industries such as environmental monitoring, financial market analysis, power and energy systems, and scientific discovery, organisations rely on analysing large volumes of complex time series data to make smart and informed decisions that help keep the world running smoothly. Two of the most critical tasks in time series analysis are Time Series Classification and Time Series Forecasting. Python’s data science ecosystem for time series analysis has grown significantly in recent years. In this talk, we will introduce the modern landscape of time series tools available in Python. We will demonstrate the usability, algorithmic diversity, and interface design of libraries such as Sktime, Aeon, and Nixtla (NeuralForecast, MLForecast). These libraries will serve as examples to show how easy they are to use, what kinds of algorithms they provide, and how their application programming interfaces are structured to support efficient and intuitive development. Whether your goal is to classify environmental patterns or forecast future trends, these tools can simplify and accelerate your time series analysis workflow.

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Fri Sep 12 13:50:00 2025 at Ballroom 2