In rjake/shinysim: Loads reactive data frames and mock input list into environment

library(tidyverse)
library(shiny)        #renderPlot, renderTable, sliderInput
library(shinyWidgets) #radioGroupButtons
get_data <- mpg 

MPG Example

Column {.sidebar data-width=200}

Filter the data:

#You can make this sidebar global by putting it ahead of Tab 1
#below are 2 input options: a gorup of buttons, and a slider
radioGroupButtons(#for categorical variables
    inputId = "year", #this will allow the selection to be referenced as input$cyl
    label = "Select Year of Vehicle", #NULL if you don't want a header
    choiceNames = c("All", sort(unique(get_data$year))), #can use paste, etc to make nicer display
    choiceValues = c("All", sort(unique(get_data$year))), #values in the data, need to line up with above
    justified =  T, #will fill the width of the container it sits in (sidebar) 
    status = "primary")
sliderInput(
    inputId = "displ", #referenced as input$displ
    label = "Select Weight:",
    value = range(get_data$displ), #default selection, you can move the range around
    min = (min(get_data$displ)),
    max = (max(get_data$displ)),
    step = .1)
#This will build a dataframe to use throughout the dashboard. To reference this dataframe, you will need to be in some reactive element ex: renderText({nrow(use_data())}). This is essentially a function and so you will need to use parentheses at the end like this: use_data() 
use_data <- 
    reactive({
        df <- 
            get_data %>% 
            filter(between(displ, min(input$displ), max(input$displ)))

        #this if statements will filter for the selection of the radioGroupButtons
        if (input$year != "All") {
            df <- df %>% filter(year == input$year)
        }

        df
    })

Column {data-width=450}

Highway MPG by Engine Displacement

renderPlot({ #renderPlot is only required becuase we are referencing someting reactive: use_data(). Otherwise we could just use ggplot(get_data,...)
    ggplot(use_data(), aes(displ, hwy)) +
        geom_smooth(color = "grey65") +
        geom_point(aes(color = factor(cyl))) +
        ylim(0, 45) +
        labs(color = "Cylinder") +
        theme(legend.position = "bottom")
})

Column

Top 10 by hwy

#this will display a top 10 table that is filtered based on the selections above
renderTable(expr = {# use {...} section to create table
                    use_data() %>%
                    arrange(desc(hwy)) %>% 
                    slice(1:10) %>% 
                    mutate(Rank = row_number()) %>% 
                    select(Rank, year, manufacturer, model, trans, hwy, fl, class)
            }, 
            spacing = "xs",
            align = "l",
            bordered = T)

r renderText({paste("Max Highway MPG by Class in Year:", input$year)})

renderTable(
    {#you can make separate objects (similar to in a function)
        count_n <- 
            use_data() %>% 
            count(class)

        max_value <- #this could have been done above, broken into different steps to show how it works
            use_data() %>% 
            group_by(class) %>% 
            summarise(hwy = max(hwy)) %>% 
            ungroup()

        #and then add them together for the final product
        count_n %>% 
        left_join(max_value) %>% 
        arrange(desc(hwy)) %>% 
        select(hwy, class, `#` = n)
    }, 
    spacing = "xs", 
    align = "l", 
    bordered = T)

Blank Page

Column

Box 1

• Find more information about flexdashboards here: https://rmarkdown.rstudio.com/flexdashboard/using.html#overview
• The shinyWidgets gallery has some nice widgets for filtering: https://dreamrs-vic.shinyapps.io/shinyWidgets/ The gallery isn't always available. Another overview can be found here:
  https://dreamrs.github.io/shinyWidgets/index.html

Column {.tabset}

Tab 1

Tab 2

rjake/shinysim documentation built on Nov. 11, 2019, 2:29 a.m.