One goal of the Carbonate CZ RCN is to build capacity within the carbonate CZ science community by providing resources and training in state of the art techniques used to study carbonate CZs.
These resources introduce users to Python in Colab (a free online platform from google for running Python codes) and provide references and examples of useful Python codes for hydrology. They are not an introduction to Python programming, but help users share codes and motivate new users to get to know Python.
Feel free to share additional tools and we will post. Email the data tools team: firstname.lastname@example.org
Python resources (one page handouts)
- Highlighted Python Libraries
- Data Processing Tools Python
What is Colab?
Colab is a product from Google Research that allows anybody to write and execute arbitrary python code through the browser. It requires no setup to use, while providing free access to run Jupyter notebooks. For more information: https://research.google.com/colaboratory/faq.html
- NWIS_USGS_Extraction.ipynb (Lindsey Aman Cromwell)
- Olm water chemistry packages (Matt Covington)
- Basic geochemical calculations
- Reading and manipulating data from dataloggers
- Geochemical calculations using data from dataloggers
Tutorial videos from Lindsey Aman Cromwell, West Virginia University
CUAHSI HydroShare is a tool for collaboration around data in the RCN or your other research groups. Use the instructions to join the free Carbonate Critical RCN data group to enable further collaboration or create your own group.
To learn more about CUAHSI Hydroshare, you can view the help files at www.hydroshare.org. or listen to our RCN webinar. In the webinar, you will learn how to upload data, fill in metadata and keywords, and share your data sets. You will find out how to share data sets privately among trusted colleagues, or make them available to the public. Keep in touch our our RCN listerv to learn more about collaboration around data using HydroShare.
Virtual field trip Nittany Valley Karst Springs narrated by Dr. Will White
- Data organization resources
- Additional tutorials