Part 4: Visualization and Data Presentation

Chapter 19: Jupyter, Pandas, and Interactive Development

Foundational~120 min

Learning Objectives

  • Set up JupyterLab with scientific extensions for efficient development
  • Apply effective notebook patterns: clear cells, imports at top, reproducibility
  • Use Pandas for loading, filtering, and analyzing tabular experiment data
  • Convert notebooks to scripts and back for production workflows

Sections

Prerequisites

💬 Discussion

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