Join us at rstudio::conf(2022) to sharpen your R skills. | July 25-28th in D.C.
Learn More
rstudio::conf(2022) | July 25-28th in D.C. 7/25 - 7/28 in D.C.
The premier IDE for R
RStudio anywhere using a web browser
Put Shiny applications online
Shiny, R Markdown, Tidyverse and more
Next level training for you and your team
Do, share, teach and learn data science
An easy way to access R packages
Let us host your Shiny applications
A single home for R & Python Data Science Teams
Scale, develop, and collaborate across R & Python
Easily share your insights
Control and distribute packages
RStudio
RStudio Server
Shiny Server
R Packages
RStudio Academy
RStudio Cloud
RStudio Public Package Manager
shinyapps.io
RStudio Team
RStudio Workbench
RStudio Connect
RStudio Package Manager
rstudio::conf 2018 case study
Understanding PCA using Shiny and Stack Overflow data
February 26, 2018
Principal component analysis (PCA) is a powerful approach for exploring high-dimensional data, but can be challenging for learners to comprehend. In this talk, I will walk through a practical and interactive explanation of what PCA is and how it works. As a case study I’ll explore a domain that many data analysts and data scientists are familiar with: programming languages and technologies, as understood through traffic to Stack Overflow questions. We will explore how interactive visualization using Shiny gives us insight into the complex, real-world relationships in high-dimensional datasets.
Software Engineer, RStudio, PBC
Julia Silge is a data scientist and software engineer at RStudio PBC where she works on open source modeling tools. She is an author, an international keynote speaker, and a real-world practitioner focusing on data analysis and machine learning practice. Julia loves text analysis, making beautiful charts, and communicating about technical topics with diverse audiences.