Data can be unruly. By learning to more efficiently and effectively manage research data, researchers can make projects smoother, avoid headaches and love their data.
Spreadsheets are a solid starting point for researchers to manage data, but the limitations can be frustrating. If you’re ready to take your research data to the next level with free and open-source software capable of automating tasks and promoting reproducibility, this intermediate class is for you.
This class is designed for graduate-level and post-doc researchers who’ve taken a beginner Python class (or equivalent), from any discipline, who want to more efficiently and effectively manage and analyze their data.
This class will increase your understanding and skills through hands-on training guided by CSU Libraries’ data specialists. This class starts where the Introduction to Python class left off and covers automation and charting techniques.
The material used as part of this workshop has been adapted from the Data Carpentry's: Data Analysis and Visualization in Python lessons https://datacarpentry.org/python-ecology-lesson/
What you need to bring to the workshop:
What we’re bringing to the workshops: