Python for Geosciences

Catalog description

Credits 3. 3 Lecture Hours. 1 Lab Hour. COURSE OVERVIEW. This course introduces core Python programming for scientific applications, emphasizing one- and two-dimensional geospatial analysis, plotting and working with large geophysical datasets. Students learn modern programming practices, including object-oriented design, while building notebooks and scripts that read and write data, detect and handle errors and perform complete end-to-end analyses. The learning journey moves from fundamentals (data structures, loops, functions) to scientific libraries (NumPy, matplotlib, pandas, Cartopy, xarray) and a final project where students analyze a dataset of their choice. This course is open to students with no prior programming experience. RELEVANCE AND APPLICATION. Python is a cornerstone of contemporary geoscience, climate, environmental data and data science workflows. This course cultivates workforce-ready skills — data ingestion, cleaning, analysis, visualization, mapping and communication — that transfer directly to research labs, government agencies, non-profits and industry roles. The final project strengthens portfolio-quality evidence of applied proficiency and prepares students for advanced study and data-driven decision-making in their communities. KEY TOPICS AND THEMES. Key themes include reading and writing standard data formats; core language fluency with variables, containers, loops and functions; object-oriented programming; numerical computing with NumPy; 1D and 2D plotting with matplotlib; time series analysis with pandas; geospatial mapping with Cartopy and shapefiles; and working with NetCDF via xarray for local and remote datasets, with consistent attention to error identification and best practices in visualization and reproducible workflows. Prerequisite: Junior or senior classification or approval of instructor.