by Julia Lowndes and Allison Horst

Welcome!

🗓️ January 27 and 28, 2020
⏰ 09:00 - 17:00
🏨 [ADD ROOM]
✍️ rstd.io/conf

Microsoft Excel is a widely used and powerful tool for working with data. As automation, reproducibility, collaboration, and frequent reporting become increasingly expected in data analysis, a good option for Excel users is to extend their workflows with R. Integrating R into data analysis with Excel can bridge the technical gap between collaborators using either software. R enables use of existing tools built for specific tasks and overcomes some limitations that arise when working with large datasets or repeated analyses. This course is for Excel users who want to add or integrate R and RStudio into their existing data analysis toolkit. Participants will get hands-on experience working with data across R and Excel, focusing on: data import and export, basic wrangling, visualization, and reporting with RMarkdown. Throughout, we will emphasize conventions and best practices for working reproducibly and collaboratively with data, including naming conventions, documentation, organization, all while “keeping the raw data raw”. Whether you are working in Excel and want to get started in R, already working in R and want tools for working more seamlessly with collaborators who use Excel, or whether you are new to data analysis entirely, this is the course for you!

Attendees will learn tools for integrating R into their existing data analysis workflow in Excel. Upon completing the workshop, participants will have learned the basics of working with data in R/RStudio, and will have experience interfacing between in Excel and R individually and as collaborators.

This workshop will be appropriate for attendees who answer yes to these questions:

Are you an Excel user who wants to expand your data analysis toolset with R? Do you want to bridge analyses between Excel and R, whether working independently or to more easily collaborate with others who use Excel or R? Are you new to data analysis, and looking for a good place to get started?

Before the training, please do the following (20 minutes). All software is free.

1. Download and install R and RStudio:
   • R: https://cloud.r-project.org/
   • RStudio: http://www.rstudio.com/download
   • Follow your operating system's normal installation process
2. Create a GitHub account:
   • GitHub: https://github.com
   • Follow optional advice on choosing your username
   • Remember your username, email and password; we will need them for the workshop!
3. Download and install Git
   • Git: https://git-scm.com/downloads
   • Follow your operating system's normal installation process. Note: you will not see an application called Git listed but if the installation process completed it was likely successful, and we will confirm together
4. Download workshop data
   • Google Drive folder: r-for-excel-data
   • Save it temporarily somewhere you will remember; we will move it together

All course material are openly available at rstd.io/conf20-r-excel.

Julia Stewart Lowndes PhD is a marine ecologist, data scientist, and Mozilla Fellow at the National Center for Ecological Analysis and Synthesis (NCEAS). As founding director of Openscapes and science program lead of the Ocean Health Index, she empowers scientists with data science and open practices. She also leads trainings as a co-founder of Eco-Data-Science, R-Ladies Santa Barbara, and as an instructor with The Carpentries. She earned her PhD at Stanford University in 2012 studying drivers and impacts of Humboldt squid in a changing climate. Web: jules32.github.io. GitHub: @jules32. Twitter: @juliesquid.

Allison Horst PhD teaches data analysis, statistics, and presentation skills at the Bren School of Environmental Science and Management (UC Santa Barbara). In addition to courses, she leads interdepartmental R/RStudio workshops for incoming graduate students, created and teaches an online R-refresher workshops for alumni, and is a co-founder of R-Ladies Santa Barbara. Allison earned the student-selected Distinguished Teaching Award at the Bren School in 2018, and was awarded the campus-wide Distinguished Teaching Award for UCSB by the Academic Senate in 2019. For her graduate research, Allison studied toxicity of engineered nanoparticles in environmental microorganisms. She is also a landscape painter, illustrator and designer. Web: allisonhorst.github.io. GitHub: @allisonhorst. Twitter: @allison_horst.

This work is licensed under a Creative Commons Attribution 4.0 International License.