Finding and Preparing Time Series Data

Finding high-quality, reliable time series data is the first and often most challenging step in any forecasting or analysis project. Whether you need historical GDP figures, energy price fluctuations, or climate records, knowing where to look and how to clean this data is essential. This course guides you through the process of discovering reputable open data sources, downloading complex temporal datasets, and preparing them for analysis. You will transition from searching aimlessly for data to confidently structuring raw time series records for modeling. \n\nWhat you'll learn:\n- Locate high-quality public time series datasets across finance, climatology, and economics\n- Understand key time series structures, regular vs. irregular intervals, and metadata standards\n- Clean raw temporal data by handling missing values, duplicates, and timezone alignments\n- Format dates and times correctly using modern data standards and programming libraries\n- Parse and aggregate data from diverse formats like CSV, JSON, and API endpoints\n- Establish reproducible workflows for downloading and updating historical datasets\n\nThe course begins with foundational concepts of time series data structures and reference terminology. From there, you will explore major global data repositories and work through written explanations on importing, cleaning, and aligning temporal records. This text-based course is designed for beginner data analysts, aspiring data scientists, and researchers who want to work with real-world time series data, requiring no advanced programming experience. Start building your foundation in time series data collection and preparation today.