RCDM Workshop Series

Description:

Curious about using Python for your research but not sure where to start? This beginner-friendly workshop is designed to make your first steps in Python smooth and accessible. We will teach you how to assign and work with variables, use simple functions and libraries, and handle data with Pandas. No coding experience required. This is not a technical session on installing Python or how the language works on computers – just the essentials to start using Python with confidence.

Topics covered:

• Using Jupyter Notebook interface for coding tasks and reproducible research

• Creating and assigning variables and using built-in functions

• Checking and understanding Python’s data types (integer, float, string, and boolean)

• Introducing Pandas for loading data and getting information from them

Presenters:

• Larissa do Carmo-Inácio, RCDM Graduate Assistant

Registration Link:

Click here to register

Description:

Curious about what your data can show? This beginner-friendly workshop is the perfect next step after learning the basics of Python. You’ll get hands-on experience creating simple plots using Pandas and Matplotlib, and explore the powerful Pyplot and Seaborn libraries. Learn how to customize your visualizations to better tell the story in your data and how to save your plots for future use. No advanced coding knowledge required! Join us in this workshop to bring your data to life.

Topics covered:

• Creating simple plots using Pandas and Matplotlib

• Introduction to Pyplot and Seaborn Libraries 

• Customizing plots using Pyplot and Seaborn

• Saving your Plots and storing your work

Presenter:

• Larissa do Carmo-Inácio, RCDM Graduate Assistant

Registration Link:

Click here to register

Description:

Want to run statistical analyses in Python but not sure which tools to use? This workshop walks you through how to carry out statistical analyses in Python – focused on the coding tasks and not on how to interpret your results. Learn to generate frequency tables and correlation matrices using Pandas, perform regression models (Linear, OLS, and Logistic) with Statsmodels, and export clean, publishable tables for your manuscripts.

Topics covered:

• Creating frequency tables and correlation matrices using Pandas and Seaborn

• Running regression models (Linear, OLS, Logistic) with Statsmodels

• Exporting tables to .docx files using python-docx

• Finding resources within UGA: Statistical Consulting Center

Presenter:

• Larissa do Carmo-Inácio, RCDM Graduate Assistant

Registration Link:

Click here to register

Description:

The University of Georgia recently adopted a new Research Data Stewardship policy developed by UGA’s Research Data Management Advisory Council (RDMAC). This policy focuses on issues of ownership, sharing, and retention of research data in response to federal public access and data management requirements. Additionally, the RDMAC is promoting steps to improve UGA’s services and infrastructure to support research data management, such as the UGA Libraries’ new institutional repository, UGA Open Scholar, and research data management planning consultation services offered through Research and Computational Data Management (RCDM). Join us to learn more about this new policy, supporting guidance, and related services and support offerings.

Presenters:

• Emily Gore, Deputy University Librarian

• Nate Nibbelink, Associate Vice President, Strategic Research Growth

• Beth Woods, Director of Research and Computational Data Management

More information and to register:

https://research.uga.edu/research-insights/live/