Developing Data Products

The final module in the Coursera Data Science Specialization covers the topic of developing "data products".

Data products are applications, software, presentations, etc., based on data, that facilitate our understanding of data (Brian Caffo).

The course introduced an extensive list of development tools that can be used to create data products with almost any desired look and feel. The list included Shiny, Slidify, RPresenter, GoogleVis, Open CPU, RCharts, Manipulate, Morris Chart, XCharts and Plotly.

All of the tools have R, the statistical programming language, in their underpinnings.

This presentation demonstrates the use of Shiny and Slidify and how they can help us understand code blue occurances at a hospital.

"Shiny" is a development tool that allows construction of sophisticated interactive web pages using R. No knowledge of HTML, CSS or Javascript is necessary, although Shiny apps can be customized using those languages if desired. For more information about Shiny visit http://shiny.rstudio.com

Going to the following Web page will display my Shiny application: https://myshinyacct.shinyapps.io/CodeBlue/

When it opens you will find on the left side two user input controls: a drop down list and a slider. On the right there is a bar plot that displays the number of code blue occurances by day of week for the period of time that the user selected.

The drop down list lets you select week, quarter or year. Selecting "week" will display the number of code blues by day of week for one week. "Quarter"" will display the number by day of week for an entire quarter. "Year" will display the number per day of week for an entire year.

Drag the slider to pick a particular week, quarter or year to display. Click the "play" button under the slider to cause it to slide by itself from left to right with an update happening every two seconds.