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

input <- list(
  displ = c(4.2, 4.6),
  year = 2008
)

library(tidyverse)
#library(shiny)        #renderPlot, renderTable, sliderInput
library(shinyWidgets) #radioGroupButtons

raw_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$cyl
  label = "Select Year of Vehicle", # NULL if you don't want a header
  choiceNames = c("All", sort(unique(raw_data$year))), # can use paste, etc to make nicer display
  choiceValues = c("All", sort(unique(raw_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$displ
  label = "Select Engine Displacement:",
  value = range(raw_data$displ), # default selection, you can move the range around
  min = (min(raw_data$displ)),
  max = (max(raw_data$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 <-
    raw_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(raw_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)
  }, 
  # additional arguments for renderTable
  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, but I broke 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.