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Interactive Data Analysis with Shiny
About
Veranstaltungsort:
Online via Zoom
General Topics:
Course Level:
Format:
Software used:
Duration:
Language:
Fees:
Students: 330 €
Academics: 495 €
Commercial: 990 €
Keywords
Additional links
Dozierende: Jonas Lieth, Paul Bauer
Referenteninformationen - Jonas Lieth
Referenteninformationen - Jonas Lieth
Jonas Lieth is a research fellow in the department Survey Data Curation and joined GESIS in April 2021. He is interested in the research of context effects, public attitudes, and social geography. Methodologically, his focus lies on quantitative approaches like spatial analysis and computational text analysis.
Referenteninformationen - Paul Bauer
Referenteninformationen - Paul Bauer
Paul C. Bauer is a researcher at the LMU Munich (Institute of Statistics) and the University of Freiburg (Institute of Political Science) and works in the field of political sociology and methodology. His current projects comprise predicting elections using Google trends, using supervised and unsupervised machine learning models to analyze open-ended audio questions, and exploring the usefulness of ideal experiments for research. His work has appeared in Political Communication, Public Opinion Quarterly, Political Behavior, PLOS One, and the European Sociological Review.
Seminarinhalt
The workshop Interactive Data Analysis with Shiny introduces participants to the basics of creating interactive apps with Shiny in R. Interactive data applications are becoming increasingly popular in academia, media, and companies to visualize, manage, and analyze data. Shiny is a tool for creating such (web) applications using R code. It allows you to create interactive data apps with no knowledge of HTML, CSS, or JavaScript. The utilization of interactive applications expands the forms of use of existing data sets and enables users to freely explore the data. The course offers an introduction to reactive programming and the R Shiny package, outlines a workflow for project management, discusses ways of offline and online hosting of Shiny apps, and gives you the opportunity to start your own interactive data analysis project.
Organizational structure of the course
The best way to learn R's versatile capabilities is to try things out and apply the presented concepts. Therefore, we will have a mixture of lectures and hands-on exercises. More specifically, each topic will be introduced in a lecture by the instructors. Participants will then receive a set of exercises on each topic. The solutions of the exercises will be discussed before the start of the next lecture part.
Zielgruppe
Participants will find the course useful if:
they want to use R to build interactive web applications to analyze and visualize their data.Lernziel
By the end of the course participants will:
understand the basics of reactive programming for interactive data analysis and visualizationknow what the structure of a Shiny application looks likebe comfortable to use R Shiny to build their own interactive applicationshave learned about ways to launch and disseminate their Shiny appwill have built their first own Shiny appVoraussetzungen
Good working knowledge in R as a programming language including familiarity in the following domains: tidyverse, data type handling, data wrangling, data import, data management, modeling (e.g., linear regression), and data visualization
Software requirements
Course participants will need a computer or laptop with R (https://cran.r-project.org/), RStudio, (https://www.rstudio.com/), and the R Shiny package (https://shiny.rstudio.com) installed. The programs and the package are free and open source.
Zeitplan
Zeitplan
Tuesday, 23.07. |
10:00-11:00 | Welcome and introduction |
11:00-11:15 | Coffee break |
11:15-12:00 | Your (first) Shiny app |
12:00-13:00 | Lunch break |
13:00-14:15 | The front end: Designing the user interface |
14:15-14:30 | Coffee break |
14:30-16:00 | Tutorials for the UI |
Wednesday, 24.07. |
10:00-11:00 | Introduction to reactive programming |
11:00-11:15 | Coffee break |
11:15-12:00 | Tutorials for reactive programming |
12:00-13:00 | Lunch break |
13:00-14:15 | Advanced reactive programming |
14:15-14:30 | Coffee break |
14:30-16:00 | Tutorials for reactive programming II |
Thursday, 25.07. |
10:00-11:00 | Visualization with ggplot2 and Shiny |
11:00-11:15 | Coffee break |
11:15-12:00 | Tutorials for visualization |
12:00-13:00 | Lunch break |
13:00-14:15 | Testing and deployment |
14:15-14:30 | Coffee break |
14:30-16:00 | Tutorials for deployment |
Friday, 26.07. |
10:00-11:00 | Do's and don'ts when building your own app |
11:00-11:15 | Coffee break |
11:15-12:00 | Building your own app I |
12:00-13:00 | Lunch break |
13:00-14:15 | Building your own app II |
14:15-14:30 | Coffee break |
14:30-16:00 | Building your own app III |
Literaturempfehlungen
Literaturempfehlungen
The course does not require any prior reading.
However, our schedule is primarily based on one textbook which we generally recommend for further reading:
Wickham, Hadley (2020): Mastering Shiny: Build Interactive Apps, Reports, and Dashboards Powered by R. Accessible online at:
https://mastering-shiny.org/.
Additional recommended literature:
Fay, Colin, Rochette, Sébastien, Guyader, Vincent, and Girard, Cervan (2022): Engineering Production-Grade Shiny Apps. Accessible online at: https://engineering-shiny.org/.
Granjon, David (2022). Outstanding User Interfaces With Shiny. Accessible online at: https://unleash-shiny.rinterface.com