Visualizing House Data

Code

library(shiny)
library(ggplot2)
library(dplyr) # Data wrangling
library(flexdashboard) # Dashboard package
library(shinydashboard) # Dashboard package
library(plotly) # Interactive data visualisations

ds <- ggplot2::txhousing
str(ds)

ds$month <- factor(ds$month, levels = c(1:12),
                          labels = c("January","February","March","April","May","June",
                                     "July", "August", "September", "October", "November", "December"),
                          ordered = TRUE) 
ds$city <- factor(ds$city)
ds$year <- factor(ds$year)

str(ds)

cities <- unique(ds$city)
discrete_x <- colnames(ds)[2:3]
continuous_y <- colnames(ds)[4:8]

ui <- fluidPage(
    br(),
    sidebarPanel(
        selectInput(inputId = "citySelect",
            label = "Select City",
            choices = cities,
            multiple = TRUE),
      selectInput('x', label = 'Independant Variable', choices = discrete_x),
        selectInput('y', label = 'Dependant Variable', choices = continuous_y),
        selectInput('colour', label = 'Colour', c('None', colnames(ds[1:3])))
    ),
    
    mainPanel(
        plotOutput('trendPlot')
    )
)

server <- function(input, output) {
  
    output$trendPlot <- renderPlot({
      dsx <- ds[ds$city %in% input$citySelect,]
        p <- ggplot(data = dsx, aes_string(x = input$x, y = input$y)) + geom_boxplot()

        if (input$colour != 'None')
                p <- p + aes_string(colour=input$colour)

        p
    })
}

shinyApp(ui = ui, server = server, options=list(height = 600)) # Run the application
Visualizing House Data

Module 10 Skill Builder

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Code
