Our staff specialize in a variety of approaches for working with research data including Python, R, etc. for data visualization, modelling, statistical analysis, and many other topics related to preparing and analyzing research data from a broad spectrum of disciplines. Drop-in and bookable consultations available to those with all levels of experience.
To learn more and book a consult, visit: https://csc.ok.ubc.ca/consultations/research-data-consultation/
The R & Python Blog addresses common data issues and data analysis tasks.
The blog posts here were created by Research Data Consultants. If you find yourself with a question that has not been answered by the blog posts currently available, feel free to reach out to schedule a one-on-one consultation.
Workshop materials are available at https://csc-ubc-okanagan.github.io/workshops/
Workshop schedule and registration can be found at https://csc.ok.ubc.ca/workshops/
| Title | Series | Description |
|---|---|---|
| Learning R | Data | A series of introductory workshops intended for individuals with little to no familiarity with R or similar tools that rely on a scripted environment. Working through a common data science pipeline, we look at importing, exploring, filtering and visualizing research data. We also explore fundamental concepts in programming that relate to statistical computing, such as iterating over data with loops and building conditional statements. Intended as a low barrier entry into the world of using your computer to engage with data outside of graphical tools like Excel or SPSS. |
| Python for Data Analysis | Data | A series of introductory workshops intended for individuals with little to no familiarity with Python or similar tools that rely on a scripted environment. Working through a common data science pipeline, we look at importing, exploring, filtering and visualizing research data. We also explore fundamental concepts in programming that relate to statistical computing, such as iterating over data with loops and building conditional statements. Intended as a low barrier entry into the world of using your computer to engage with data outside of graphical tools like Excel or SPSS. |
| Research Data Management | Researcher Toolkit | A two-part workshop on Research Data Managment covering best practices in file naming, file format selection, managing back ups and addressing deposit. Part of the larger Researcher Toolkit series, which aims to introduce participants to a variety of research tools and concepts, and build core competencies applicable across the research lifecycle. |
| Introduction to the shell | Researcher Toolkit | A two-part series on the shell, introducing interacting through a terminal, and basic shell commands, such as navigating through directories, moving, deleting, reading files, etc. Part of the larger Researcher Toolkit series, which aims to introduce participants to a variety of research tools and concepts, and build core competencies applicable across the research lifecycle. |
| Introduction to Git, GitHub, and GitHub Pages | Researcher Toolkit | A three-part series on Git, GitHub, and GitHub pages. Start by exploring file versioning with Git, then connect to a remote repository for back up and collaborative editing, and finally publish a simple, static website to share your work. Part of the larger Researcher Toolkit series, which aims to introduce participants to a variety of research tools and concepts, and build core competencies applicable across the research lifecycle. |