Python programming skills are essential for working with, analyzing, and deriving insights from environmental data. In this intensive EDS 217 course, students will develop fundamental skills in Python programming with a focus on environmental data science applications. Topics covered include basic Python syntax, data structures, functions, libraries commonly used in data science (e.g., pandas, numpy, matplotlib, seaborn), and introductory data analysis and visualization techniques.
The goal of EDS 217 (Essentials of Python for Environmental Data Science) is to prepare incoming MEDS students with the Python programming skills required for their data science courses and projects in the program. By the end of the course, students should be able to:
- Write, interpret, and debug Python code for data manipulation and analysis
- Utilize key Python libraries for environmental data science (e.g., pandas, numpy, seaborn, matplotlib)
- Perform basic data analysis and create visualizations using Python
- Apply Python programming skills to conduct environmental data science analyses
- Collaborate with peers on coding projects and communicate results effectively
- Understand best practices in Python programming and project organization
This course uses Python 3.11 with carefully selected data science libraries:
- NumPy 2.3+ - Numerical computing with enhanced performance
- Pandas 2.3+ - Data manipulation and analysis
- Matplotlib 3.9+ - Static plotting and visualization
- Seaborn 0.13+ - Statistical data visualization
- JupyterLab 4.4+ - Interactive development environment
- SciPy - Scientific computing functions
- Plotly - Interactive visualizations
- Scikit-learn - Machine learning basics
- Requests - Web data access and APIs
- BeautifulSoup4 - Web scraping and HTML parsing
- OpenPyXL/XlrD - Excel file support
- Statsmodels - Statistical modeling
All packages include version pinning for educational stability while ensuring access to modern features.
Visit the course page on the Bren Website.
Before working with the course materials, you'll need to set up your Python environment:
- 📋 Standard Setup - Complete guide for setting up the conda environment
- ⚡ Fast Setup - Quick setup using mamba for faster installation
- 🔄 Environment Migration - Guide for migrating from older environments
If you're contributing to the course website or need to build the documentation:
- 🔨 Building Documentation - Complete guide for building and deploying the website
- Scripts automatically activate the
eds217_2025environment - Includes progress indicators and local serving options
- Scripts automatically activate the
- ⚙️ Kernel Fix Guide - Fix Jupyter kernel issues if packages aren't importing
Found something that doesn't look quite right? Feel free to file an issue and include a concise, clear description, along with a link to the location on the website. Screenshots are always appreciated as well!
EDS 217 builds upon the foundations laid by numerous other introductory python programming courses and the overall course design of other MEDS classes. We would like to acknowledge the contributions of former students and colleagues whose materials and insights have helped shape this course.