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Learn how to analyze data using Python and/or R programming languages (via Zoom)

January 13, 2021

Learn essential programming skills 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:  Online via Zoom; connection information will be sent in advance.

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!

Friday, February 12, 10am-12pm
R Programming:  R Basics
Register:  https://go.wisc.edu/7a3rj7

Learning how to code can be intimidating, but will save you time and effort in the long run. This workshop will cover the basics of R programming. By the end of this session, you will be able to create variables, use pre-defined functions, understand data types and load and inspect a dataset using RStudio. This workshop is geared toward programming novices, so no previous experience is required.

 

Friday, February 19, 10am-12pm
R Programming:  R Basics (repeat)
Register:  https://go.wisc.edu/3cpy01

This workshop is a repeat of the February 12 “R Basics” workshop.

 

Friday, February 26, 10am-12pm
R Programming:  Data Wrangling
Register:  https://go.wisc.edu/7wxw0x

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 R studio (functions, operators, data types) would be helpful for you to get the most out of this session.

 

Friday, March 5, 10am-12pm
R Programming:  Visualization
Register:  https://go.wisc.edu/615hjj

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 and R studio and dplyr would be helpful for you to get the most out of this session.

 

Friday, March 12, 10am-12pm
R Programming:  Reports
Register:  https://go.wisc.edu/i01y2w

Documenting your analysis in a way that is understandable to a colleague (or yourself 3 months later) can be challenging. One way to make reports more readable, even by people who don’t code, is to alternate human readable text with machine readable code. This workshop will cover creating reproducible reports of this type using knitr. After this session, you will be able to create R markdown documents, add formatted text and executable code blocks, and render the R markdown document into a final report.

To find out more about this series, see: https://researchguides.library.wisc.edu/R

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!

Thursday, February 11, 10am-12pm
Python Programming:  Introduction
Register:  https://go.wisc.edu/5w5ox1

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!

 

Thursday, February 18, 10am-12pm
Python Programming:  Introduction (repeat)
Register:  https://go.wisc.edu/hpge4j

This workshop is a repeat of the February 11 “Python Introduction” workshop

Thursday, February 25, 10am-12pm
Python Programming:  Loops, lists, and functions
Register:  https://go.wisc.edu/c66i79

This workshop will take a deeper dive into Python, covering essential topics such as automating tasks using loops, lists, and functions.

 

Thursday, March 4,  10am-12pm
Python programming:  Spreadsheets and data manipulation
Register:  https://go.wisc.edu/1su7s5

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.

 

Thursday, March 18, 10am-12pm
Python Programming:  Data Visualization
Register:  https://go.wisc.edu/pj0488

In this workshop, we will explore different methods and tools for visualizing data using Python.

Workshop Instructors


Trisha Adamus

Trisha Adamus is a Health Sciences Librarian at UW-Madison specializing R programming and data management.

Questions? adamus@wisc.edu

 


Tobin Magle

Tobin Magle is the Research Data Lifecycle Manager in the Research Cyber infrastructure at DoIT specializing R programming and data management. She has a PhD in Microbiology and an extensive background in STEM research.

Questions? tobin.magle@wisc.edu


Casey Schacher

Casey Schacher is a Science and Engineering Librarian at UW-Madison specializing Python programming and data management.

Questions? casey.schacher@wisc.edu

 


Heather Shimon

Heather Shimon is a Science and Engineering Librarian at UW-Madison specializing research data management.

Questions? heather.shimon@wisc.edu 

 


John Caskey

John Caskey is a Senior Data Scientist for the School of Medicine and Public Health, University of Wisconsin-Madison.

 

 


Sarah Graves

Sarah Graves is a Environmental Observation and Informatics Program Coordinator for The Nelson Institute for Environmental Studies, University of Wisconsin-Madison.

 

 


Andrew Maule

Andrew Maule is a researcher for the Department of Horticulture, University of Wisconsin-Madison.

 

 


Sarah Stevens

Sarah Stevens is the Data Science Hub Facilitator for the Data Science Institute, University of Wisconsin-Madison.

 

 


Scott Wildman

Scott Wildman is a Policy and Planning Analyst for Academic Planning and Institutional Research, University of Wisconsin-Madison.

 

 

Helpers: 

Dave Bloom, Science and Engineering Librarian, University of Wisconsin-Madison

Kristjan Gudjonsson,  Help Desk Technical Lead, University of Wisconsin-Madison

Corey Halpin, Software Engineer – Internet Scout, University of Wisconsin-Madison

Jennifer Patiño, Data and Digital Scholarship Diversity Resident Librarian, University of Wisconsin-Madison

Steve Meyer, Data Strategist – Libraries, University of Wisconsin-Madison