This repository contains course contents for HWRS 401/501 "Tools for Data Handling and Analysis in Water, Weather, & Climate" also known as "HAS Tools". This course is intended to introduce the basics of the modern data science stack for water, weather, and climate research. Folks from other Earth/environmental fields should also find useful lessons here.
The structure of this repository is roughly as follows:
admin: Contains details related to administration of the class including the syllabus and notes about structuring the course.slides: Contains slides from lectures (as appropriate) as pdf files or jupyter notebooks.coding_modules: Code that will be used for hands-on portions of the course.data: Sample datasets that will be used in class.cheat_sheets: Some cheat sheets for remembering various commands/concepts.exercises: Copies of homework assignments - do not use these - please use the homework assignments in your individual repositories.
- Weds, Aug 28 - Overview of Git and start of using VSCode codespaces
- Fri, Aug 30 - Review of Git and walthrough for VSCode codespaces + homework 1
- Fri, Aug 30 - Supplemental walkthrough for codespaces + homework 1
- Weds, Sept 4 - Starting with codespaces and python
- Fri, Sept 6 - Continuing initial python overview
- Mon, Sept 9 - Python functions and module imports
- Weds, Sept 11 - Intro to numpy
- Supplemental - Submitting HW2 changes to github
- Fri, Sept 13 - Prerecorded intro to matplotlib
- Fri, Sept 13 - Short in class session
- Mon, Sept 16 - Some details about matplotlib plots
- Supplemental - Fixing merge conflicts
- Weds, Sept 18 - hw2 walkthrough, merge conflicts
- Mon, Sept 23 - pandas stuff
- Weds, Sept 25 - Data access via apis
- Fri, Sept 27 - Timeseries analysis
- Supplemental Example - Project Euler
- Supplemental Example - Calculating Pi via Monte Carlo methods
- Mon, Oct 7 - Geospatial data representations: vector data
- Mon, Oct 14 - Raster data & labeled arrays
- Fri, Oct 18 - Groupby, resample, and rolling
- Mon, Oct 28 - Python scripts & modules
- Weds, Oct 30 - The command line
- Fri, Nov 1 - Building command line interfaces
- Mon, Nov 3 - Managing python environments with conda
- Weds, Nov 5 - Writing clean code
- Weds, Nov 13 - Forecast 2 overview
Throughout the course we'll be amassing a lot of different resources that you can use.
- Automate the Boring Stuff with Python - Great for getting started!
- Browser based Jupyter Lab environment
- USGS National Water Information Systems Mapper
- Python data science handbook (free online textbook)
- Earth data science textbook (free)
- xarray tutorial
- Data Analysis in the Water Science (course materials)
- Spatiotemporal Data Analysis (course materials)
As we come together throughout the semester more details and resources will be shared here - keep an eye out! 👀