Python for Industrial Ecology

The course gives an introduction to data processing, data analysis, and visualisation in the field of environmental science.

• Python packages for data science: NumPy, Pandas, GeoPandas, Matplotlib
• Python development environment (VScode, Anaconda, Linter, extensions)
• Writing clear scripts that are easy to follow
• Data and code documentation and management
• Presentation of results:
  • Scientific presentation
  • Innovation pitch

The course is designed for industrial ecology students and provides the programming skills needed in the following courses (IO analysis, LCA, MFA).

Knowledge

• Understand and can use Python programming terminology
• Know the benefits and drawbacks of different data and code management strategies
• Can explain the concepts of circular economy and business models
• Can explain why systems perspective is important in sustainability analysis
• Can give various examples of Python applications for sustainability analysis

Skills

• Can independently create a Python project and write well documented, efficient, and reusable code
• Can create, modify, delete, and use Python environments
• Can import, export, and process large datasets with Pandas
• Can create clear and useful plots with Pandas and Matplotlib
• Can communicate clearly the results of a Python Project
  • Presenting/pitching skills
  • Written skills

General competence

• Understand the challenges of working with sustainability datasets
• Become comfortable using programming as a tool to handle data, conduct computations, and visualize results
• Acquire a template for a Python project that can be reused in the future

• Lectures
• Discussions in plenary or groups
• Academic debating
• VSC demos
• Online programming tasks and self-study
• Hackaton
• Python project
• Presentation (scientific presentation or sustainable innovation pitch)