This masterclass explores the fundamentals of time series analysis using Python and pandas, providing practical techniques for working with time-indexed data. Topics include slicing and summarizing time series, using pandas statistical functions, managing frequencies and date ranges, and performing operations like moving averages, expanding windows, and return on investment calculations. Attendees will gain actionable insights to analyze trends and patterns in time-dependent datasets effectively.
Learning Outcomes:
- Understand how to manipulate and analyze time-indexed data with pandas.
- Apply statistical and aggregation techniques to uncover time series trends.
- Perform advanced operations like moving averages and investment return calculations.
Target Audience
This talk is designed for data analysts, researchers, and Python enthusiasts who work with time-dependent data and want to enhance their skills in time series analysis. It’s particularly suited for those interested in analyzing trends, making forecasts, or evaluating investment returns using Python and pandas.
This module is standalone and aimed at both a technical and non-technical audience. There will be some python code and live demonstrations of time series analysis
