Join members of the Research and Computational Data Management (RCDM) team for walk-in research data consultations in the Data Studio @ Main and the McBay Science Library on Wednesdays from 12:00 – 1:30 p.m.
Team members are available to assist UGA faculty, students, and staff with topics including:
Join members of the Research and Computational Data Management (RCDM) team for walk-in research data consultations in the Data Studio @ Main and the McBay Science Library on Wednesdays from 12:00 – 1:30 p.m.
Team members are available to assist UGA faculty, students, and staff with topics including:
Join members of the Research and Computational Data Management (RCDM) team for walk-in research data consultations in the Data Studio @ Main and the McBay Science Library on Wednesdays from 12:00 – 1:30 p.m.
Team members are available to assist UGA faculty, students, and staff with topics including:
Join members of the Research and Computational Data Management (RCDM) team for walk-in research data consultations in the Data Studio @ Main and the McBay Science Library on Wednesdays from 12:00 – 1:30 p.m.
Team members are available to assist UGA faculty, students, and staff with topics including:
Join members of the Research and Computational Data Management (RCDM) team for walk-in research data consultations in the Data Studio @ Main and the McBay Science Library on Wednesdays from 12:00 – 1:30 p.m.
Team members are available to assist UGA faculty, students, and staff with topics including:
Join members of the Research and Computational Data Management (RCDM) team for walk-in research data consultations in the Data Studio @ Main and the McBay Science Library on Wednesdays from 12:00 – 1:30 p.m.
Team members are available to assist UGA faculty, students, and staff with topics including:
Description:
Description:
Interested in creating good visualizations for your research but unsure how to get started? This beginner-friendly workshop introduces the fundamentals of turning data into aesthetically pleasing graphics using Python’s most popular visualization libraries. You’ll apply core plotting concepts and create basic charts to communicate your findings effectively. No prior coding or visualization experience is required. This session was designed to give you the essential tools to begin visualizing data with confidence.
Presenter:
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:
