Learn how to use Python and/or R programming languages for data analysis (via Zoom)
Learn programming skills for computational research during the R workshop series and the Python workshop series. Attend any or all of the sessions. Brought to you as a part of the UW Libraries Graduate Support workshop series. Open to all UW-Madison students, faculty, and staff.
Location: Instruction online via Zoom. Connection information will be sent in advance. Workshops will not be recorded.
The R Series
*Registration required. Registration is by workshop, not for the entire series. See links below to register for individual workshops. Sessions are filling up fast!
To find out more about this series, see: https://researchguides.library.wisc.edu/R
Friday, September 20, 10am-12pm
R Programming: R Basics
Register: https://go.wisc.edu/mwzmu0
This workshop is for the absolute beginner wanting to slowly walk through the process of getting started with R, a programming language commonly used for data analysis. The session will introduce you to the RStudio interface for coding in R. We will work through setting up a project directory, cover key concepts and terminology, and load and inspect a dataset.
This workshop is geared toward programming novices, so no previous experience is required.
Friday, September 27, 10am-12pm
R Programming: R Basics (repeat)
Register: https://go.wisc.edu/ios5k1
This workshop is an exact repeat of the September 20th “R Programming: R Basics” workshop (see above).
Friday, October 4, 10am-12pm
R Programming: Data Wrangling
Register: https://go.wisc.edu/zx7b11
Data is rarely perfect out of the box. This workshop will cover how to manipulate datasets using an R package called dplyr. After this session, you will be able to select rows and columns, add new columns, remove missing data and create summary tables of your data.
A basic working knowledge of R and RStudio (e.g., functions, operators, data types) would be helpful for you to get the most out of this session.
Friday, October 11, 10am-12pm
R Programming: Data Visualization
Register: https://go.wisc.edu/3480bq
So you’re familiar with R, but want to do more with your plots than the base graphics package. This workshop will show you how to use the ggplot2 package in R. After this session, you will be able to create a variety of plot types, alter their aesthetics, and create custom themes.
A working knowledge of R, RStudio, and dplyr would be helpful for you to get the most out of this session.
Friday, October 18, 10am-12pm
R Programming: Reports
Register: https://go.wisc.edu/s52531
One way to automate your reports is to create files with human readable text and machine readable code. This workshop will cover creating reproducible reports of this type in RStudio using Quarto. After this session, you will be able to create Quarto documents, add formatted text and executable code blocks, and render the document into a final report.
A working knowledge of R and RStudio would be helpful for you to get the most out of this session.
Friday, October 25, 10am-12:30pm
R Programming: README Files in RStudio
Register: https://go.wisc.edu/23sblv
Documenting your analysis in a way that is understandable to a colleague (or yourself 3 months later) can be challenging. README files are text documents that record your computational environment, methodologies, and more. After this session, you will be able to use Quarto in RStudio to create a README file template.
A working knowledge of R and RStudio, and some experience with a markdown language would be helpful for you to get the most out of this session.
The Python Series
*Registration required. Registration is by workshop, not for the entire series. See links below to register for individual workshops. Sessions are filling up fast!
To find out more about this series, see: https://researchguides.library.wisc.edu/python
Tuesday, September 17, 10am-12pm
Python Programming: Introduction
Register: https://go.wisc.edu/wwsod8
This workshop is for the absolute beginner wanting to slowly walk through the process of getting started with Python, a programming language commonly used for data analysis. We’ll work through installation and setup of some helpful software and introduce basic concepts and terminology used in Python. Finally, we’ll work together to create your first simple but useful program!
This workshop is geared toward programming novices, so no previous experience is required.
Tuesday, September 24, 10am-12pm
Python Programming: Introduction (repeat)
Register: https://go.wisc.edu/ah44bj
This workshop is an exact repeat of the September 17th “Python: Introduction” workshop (see above).
Tuesday, October 1, 10am-12pm
Python Programming: Loops, Lists, and Functions
Register: https://go.wisc.edu/ay0m55
This workshop will take a deeper dive into Python, covering essential topics such as automating tasks using loops, lists, and functions.
Prerequisite: Understanding of basic Python concepts (e.g., variables, data types) is helpful.
Tuesday, October 8, 10am-12pm
Python Programming: Spreadsheets and Data Manipulation
Register: https://go.wisc.edu/x0q10i
Real-world data can be messy. This workshop will cover a range of topics related to organizing and manipulating spreadsheet data for more effective analysis. We’ll use pandas, a popular and free data analysis library written for Python.
Prerequisite: Understanding of basic Python concepts (e.g., functions, operators, data types) is helpful.
Tuesday, October 15, 10am-12pm
Python Programming: Data Visualization with Seaborn
Register: https://go.wisc.edu/uto86g
In this workshop, we will explore different methods and tools for visualizing data. We’ll use seaborn, a popular and free data visualization library written for Python.
Prerequisite: Understanding of basic Python concepts (e.g., functions, operators, data types) is helpful.
Workshop Organizers
Heather Shimon
Heather Shimon is a Science and Engineering Librarian specializing research data management.
Questions? heather.shimon@wisc.edu
Trisha Adamus
Trisha Adamus is a Health Sciences Librarian at Ebling Library specializing data services.
Questions? adamus@wisc.edu
Dave Bloom
Dave Bloom is a Science and Engineering Librarian specializing in research data management.
Questions? david.bloom@wisc.edu
Lisa Abler
Lisa Abler is a Science and Engineering Librarian specializing in research data management.
Questions? lisa.abler@wisc.edu
Instructors:
Imraan Alas, Researcher
Chris Endemann, Data Science Facilitator, Data Science Hub
Erwin Lares, Data Science Platform Lead, Research Cyberinfrastructure, Division of Information Technology (DoIT)
Casey Schacher, Research Storage Lead, Research Cyberinfrastructure, Division of Information Technology (DoIT)
John Shadle, Health Equity Survey Analyst, University Health Services
Sarah Stevens, Director, Data Science Hub
Helpers:
Katie Dunn, Electronic Resources Librarian, University of Wisconsin Law Library
Sarah Graves, Scientist, Forest & Wildlife Ecology
Corey Halpin, Software Engineer, Internet Scout
Todd Hayes-Birchler, Database Administrator, School of Medicine and Public Health
Annika Pratt, Research Assistant, Plant Pathology
Caitlin Roa, Academic Program Specialist, Department of Psychology
Angel Tang, Science & Engineering Librarian, UW-Madison Libraries
Kimberlie Vera, Research Assistant, Forest & Wildlife Ecology
Sarah Whitcomb, Research Scientist, USDA
Maria Widmer, Instructional Design & Engagement Specialist, L&S Instructional Design Collaborative