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Visualization analysis using R Shiny
Journal of the Korean Data & Information Science Society 2017;28:1279-90
Published online November 30, 2017
© 2017 Korean Data & Information Science Society.

Jonghwa Na1 · Eunji Hwang2

1Department of Information and Statistics, Chungbuk National University
2Korea Health Industry Development Institute
Correspondence to: Jonghwa Na
Professor, Department of Information and Statistics, Chungbuk National University, Chungbuk 28644, Korea. Email:
Received October 30, 2017; Revised November 21, 2017; Accepted November 22, 2017.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
R’s {shiny} package provides an environment for creating web applications with only R scripts. Shiny does not require knowledge of a separate web programming language and its development is very easy and straightforward. In addition, Shiny has a variety of extensibility, and its functions are expanding day by day. Therefore, the presentation of high-quality results is an excellent tool for R-based analysts. In this paper, we present actual cases of large data analysis using Shiny. First, geological anomaly zone is extracted by analyzing topographical data expressed in the form of contour lines by analysis related to spatial data. Next, we will construct a model to predict major diseases by 16 cities and provinces nationwide using weather, environment, and social media information. In this process, we want to show that Shiny is very effective for data visualization and analysis.
Keywords : Geological anomaly zone, negative binomial regression, shiny, visualization, web application