library(shiny)
## Warning: package 'shiny' was built under R version 3.2.5
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.2.5
library(plotly)
## Warning: package 'plotly' was built under R version 3.2.5
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:graphics':
## 
##     layout

1. Introduction

This is a shiny presentation using “mtcars database. There are three tab panels: the first one creates a histogram from a chosen variable; the second one combines two variables producing a two dimension graphic; the third one provides a statistical summary.

2. Shiny App

2.1 Histograms

To create an histogram I’ve used ggplot and plotly. The user can choose any variable from database. Let’s see an example with the plotly library

a<-qplot(mpg, data=mtcars)
a
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

2.2 Two variable scatterplot

In this tab panel the user can choose two variables from mtcars dataset. Automatically, there is a scatterplot of these two variables.

plot(mtcars$mpg, mtcars$disp)

2.2 Statistical summary

In this tab panel the user can select from a checkbox the variables he/she wants to incorporate to the summary.

summary(mtcars$mpg)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   10.40   15.42   19.20   20.09   22.80   33.90

3 Conclusion

The advantage of shiny application is its interactivity, and the user easily can choose different graphics and variables.