Shiny Application Layouts Exercises (Part-2)

SHINY APPLICATION LAYOUTS-PLOT PLUS COLUMNS

In the second part of our series we will build another small shiny app but use another UI.

More specifically we will present the example of a UI with a plot at the top and columns at the bottom that contain the inputs that drive the plot. For our case we are going to use the diamonds dataset to create a Diamonds Analyzer App.

This part can be useful for you in two ways.

First of all, you can see different ways to enhance the appearance and the utility of your shiny app.

Secondly you can make a revision on what you learnt in the “Building Shiny App” series as we will build basic shiny stuff in order to present it in the proper way.

Read the examples below to understand the logic of what we are going to do and then test your skills with the exercise set we prepared for you. Lets begin!

Answers to the are available here.

Shiny Installation

In order to create the app we have to install and load the package shiny.

Exercise 1

Install and load shiny.

Grid Layout

The sidebarLayout uses Shiny’s grid layout functions. Rows are created by the fluidRow function and include columns defined by the column function. Column widths should add up to 12 within a fluidRow.
The first parameter to the column function is it’s width. You can also change the position of columns to decide the location of UI elements. You can put columns to the right by adding the offset parameter to the column function. Each unit of offset increases the left-margin of a column by a whole column.

Now let’s begin to build our UI. First of all we will place the fluidpage with a title as below:

#ui.R
library(shiny) shinyUI(fluidPage( title = "Diamonds", h4("Diamonds Analyzer") ))
#server.R
library(shiny) function(input, output) {}

Exercise 2

Create the initial UI of your app and name it “Diamonds Analyzer”.

You can use the fluidrow function with the column function of width =2 inside of it like this:
#ui.R
library(shiny) shinyUI(fluidPage( title = "Diamonds", h4("Diamonds Analyzer"), fluidRow(column(2), column(2), ) ))

Exercise 3

Create a fluidrow with two columns of width = 4 inside it. NOTE: Do not expect to see something yet.

Now it is time to fill these columns with some tools that will help us determine the variables that we are going to use for our plot.
In the first 4 columns we will put a selectInput as the code below.
#ui.R
fluidRow(column(4, h4("Variable X"), selectInput('x', 'X', names(diamonds)))

Exercise 4

Put a selectInput in the first 4 columns of your UI. Name it “Variable X”. HINT:Use names to get the names of the dataset diamonds as inputs.

Now let’s move to the next four columns. We are going to put in there another selectInput and select the second of the dataset’s names as default. We are also going to see what offset does by setting it to 1 and then deactivating it again like the example below. You can use the code as it is or change the parameters given to understand the logic behind its use.
#ui.R
offset = 1, selectInput('y', 'Y', names(dataset), names(dataset)[[2]])

Exercise 5

Create a selectInput from column 5 to column 8. Choose the second of the dataset’s name as default. Name it “Variable Y”. HINT: Use names to get the names of the dataset diamonds as inputs.

Exercise 6

Set the offset parameter to 1 from columns 5 to 8.

Now let’s call our plot and put it on the top of our UI. Look at the example below.

Exercise 7

Place the plot on the top of your UI. HINT: Use plotOutput and hr. NOTE: You are not going to see the plot in your UI because you have not created the server side yet.

We are going to create a reactive expression in order to combine the selected variables into a new data frame.Look at the example:
#server.R
selectedData <- reactive({ diamonds[, c(input$x, input$y)] })

Exercise 8

Create a reactive expression in order to combine the selected variables into a new data frame. HINT: Use reactive.

Now plot your new data frame like the example:
#server.R
output$plot <- renderPlot({ plot(selectedData()) })

Exercise 9

Plot your data frame. HINT: Use renderPlot.

As mentioned before the width of our UI is equal to 12 columns. So what is goint to happen if we a add a new column of width = 4 next to the other two? You have to find out in order to understand better how it works.

Exercise 10

Create a new selectInput and try to put it next to “Variable Y”. Try to explain the result. NOTE: You do not have to connect it with your plot.