How to use R Shiny for EDA and Prediction

How to use R Shiny for EDA and Prediction

The objective of the present article is to provide a simple guide on how to develop an R Shiny application to analyze, explore, and predict variables within a dataset.

The objective of the present article is to provide a simple guide on how to develop an R Shiny application to analyze, explore, and predict variables within a dataset.

The first segment of the article covers R Shiny basics, such as the explanation fo its functionality. Further, I will develop an exploratory data analysis of bike-sharing data in the form of interactive graphs. Then, I will create a prediction model to help the user of the application predict the number of total bike registration the system by taking into consideration weather conditions and a specific day of the year.

Furthermore, I will describe the data to get in the context of the information that the dataset contains. To put a purpose to the web application, in the data understanding section, I will create several business questions that I will walk through to build the R Shiny.

Then, by using R, I will arrange the data in the correct format to build the machine learning model and the Shiny application. Finally, I will display the code and explain the steps on how to create an R Shiny application.

What is R Shiny?

R Shiny is an R package that is capable of building an interactive web page application straight from R without using any web application languages such as HTML, CSS, or JavaScript knowledge.

One essential feature of Shiny is that these applications are in a way “live” since the output of the web page changes as the user modifies the inputs, without reloading the browser.

r bike-sharing towards-data-science data-visualization r-shiny visual studio code

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