R - How to Use Selectinput in Shiny to Change the X and Fill Variables in a Ggplot Renderplot

R - How do I use selectInput in shiny to change the x and fill variables in a ggplot renderPlot?

The reason is that the input$x and input$y are character class. So, instead of aes, use aes_string

renderPlot({
  ggplot(data, aes_string(x = input$x)) +
  geom_bar(aes_string(fill = input$y), position = position_stack(reverse = TRUE)) +
  coord_flip() + 
  theme(legend.position = "top")
})

---

A reproducible example with data(mpg)

library(shiny)
library(ggplot2)

data(mpg)

ui <- fluidPage(
  inputPanel(
    selectInput('x', 'X', choices = c("manufacturer", "model", "year", "cyl", "class"),
          selected = "class"),
    selectInput('y', 'Y', choices = c( "trans", "fl", "drv"), 
  selected = "drv")
  ),

  mainPanel(plotOutput("outplot"))

)

server <- function(input, output) {

  output$outplot <- renderPlot({
    ggplot(mpg, aes_string(x = input$x)) +
      geom_bar(aes_string(fill= input$y), position = position_stack(reverse = TRUE)) +
      coord_flip() + 
      theme(legend.position = "top")
  })

}

shinyApp(ui = ui, server = server)

-output

My first R Shiny , how to am i combine selectinput with renderplot(ggplot)?

You can make a reactive dataset

carsales_subset <- reactive({
                           carsales %>% filter(Year==input$yil, Month==input$ay)
                           })

Then pass this through the ggplot function

output$bar <- renderPlot({
    ggplot(data=carsales_subset(),aes(x = Brand, y = Quantity, group = Brand, color = Brand, fill=Brand)) +
      geom_bar(stat = "identity")

  })

How to fill in the variables into the stat_funciton() programmatically?

The issue is that input$x is a character and hence mean(input$x, na.rm = TRUE)will not work. Instead you could do mean(removeNA[[input$x]], na.rm = TRUE).

A minimal reprex using mtcars:

library(ggplot2)

removeNA <- mtcars

input <- list(
  x = "mpg"
)

mean_x <- mean(removeNA[[input$x]], na.rm = TRUE)
sd_x <- sqrt(var(removeNA[[input$x]],na.rm = TRUE))

ggplot(data = removeNA, mapping = aes_string(x = input$x)) +  
  geom_histogram(aes(y = ..density..)) +    
  stat_function(fun = dnorm, n = 40000, args = list(mean = mean_x, sd = sd_x)) +
  labs(title = input$x) 
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Passing a selectInput() value (a choice between column names) as an axis to ggplot() in Shiny

input$xaxis is a string, so you cannot use it directly inside aes().

Try using aes_string() instead.

Note that some_other_col should also be a string.

server <- function(input, output) {

  output$df_plot <- renderPlot({
    plot <- ggplot(data = df) +
      geom_point(aes_string(x = input$xaxis, y = "some_other_col"))

    return(plot)

  })

A full working example:

library(shiny)
library(ggplot2)

df <- iris
df_colnames <- colnames(df)

xaxis_input <- selectInput(
    inputId = "xaxis",
    label = "Feature of Interest",
    choices = df_colnames
)

ui <- fluidPage(
        titlePanel("DF"),
        xaxis_input,
        plotOutput(
        outputId = "df_plot",
    )
)

server <- function(input, output) {

    output$df_plot <- renderPlot({
        plot <- ggplot(data = df) +
            geom_point(aes_string(x = input$xaxis, y = "Sepal.Width"))
    
        return(plot)
    })
}

# Run the application 
shinyApp(ui = ui, server = server)

Plotting categorical and numerical varibles with a shiny r app

Because the return value from the select list input control is a character. I've attached one screenshot showing the value of num_var_1() and num_var_2().

And I would suggest you to insert browser() function to debug your code and you could run the code below to have a better understanding of your code.

not_sel <- "No selected"

about_page <- tabPanel(
  title = "Info",
  titlePanel("Info"),
  "Creado con R Shiny",
  br(),
  "Mayo 2022"
)

main_page <- tabPanel(
  title = "Analysis",
  titlePanel("Analysis"),
  sidebarLayout(
    sidebarPanel(
      title = "Inputs",
      fileInput("csv_input", "Select CSV File to Import", accept = ".csv"),
      selectInput("num_var_1", "Variable 1", choices = c(not_sel)),
      selectInput("num_var_2", "Variable 2", choices = c(not_sel)),
      br(),
      actionButton("run_button", "Run Analysis", icon = icon("play"))
    ),
    mainPanel(
      tabsetPanel(
        tabPanel(
          title = "Plot",
          plotOutput("plot_1")
        
        
          )
        
        )
      
    )
  )
)

draw_plot_1 <- function(data_input, num_var_1, num_var_2){
  
  if(num_var_1 != not_sel & num_var_2 != not_sel)
  {
    if(is.character(num_var_2) & is.numeric(num_var_1))
    {
      ggplot(data = data_input,
             aes_string(x = num_var_1, y = num_var_2)) +
        geom_boxplot()  
    }
    else if (is.character(num_var_1) & is.numeric(num_var_2))
    {
      ggplot(data = data_input,
             aes_string(x = num_var_2, y = num_var_1)) +
        geom_boxplot()  
    }
    else
    {
      ggplot(data = data_input,
             aes_string(x = num_var_2, y = num_var_1)) +
        geom_point()  
    }
    } 
}

ui <- navbarPage(
  title = "Data Analyser",
  theme = shinytheme('united'),
  main_page,
  about_page
)

server <- function(input, output){
  
  options(shiny.maxRequestSize=10*1024^2) 
  
  data_input <- reactive({
    req(input$csv_input)
    fread(input$csv_input$datapath)
  })
  
  observeEvent(data_input(),{
    choices <- c(not_sel,names(data_input()))
    updateSelectInput(inputId = "num_var_1", choices = choices)
    updateSelectInput(inputId = "num_var_2", choices = choices)
  })
  
  num_var_1 <- eventReactive(input$run_button,input$num_var_1)
  num_var_2 <- eventReactive(input$run_button,input$num_var_2)

  
  # plot
  
  plot_1 <- eventReactive(input$run_button,{
    draw_plot_1(data_input(), num_var_1(), num_var_2())
  })
  
  output$plot_1 <- renderPlot(plot_1())
  
  output$num_var_1_title <- renderText(paste("Num Var 1:",num_var_1()))
  
}

shinyApp(ui = ui, server = server)

Problem passing variable names via selectInput() in R/Shiny

input$var is a string. Therefore, do

output$plot <- renderPlot({
  g <- ggplot(d, aes_string("y", fill = input$var, colour = input$var)) + 
         geom_density(alpha=.2)
  g
})

How to connect user input with gganimate graph in R shiny?

Your code is still far from minimal and I don't have many of the packages you reference, but I think the following will illustrate the techniques that will allow you to do what you want. I've based my code on the diamonds dataset, which is part of ggplot2.

Your problem is due to the fact that Shiny input widgets (generally) return strings, whereas ggplot functions expect symbols as their argument. This is a feature of the tidyverse's use of non-standard evaluation (NSE).

As a result, the interface between Shiny and the tidyverse can be perplexing when you first come across it. One solution is to use the bang-bang operator (!!) and the sym function.

The following app displays a faceted scatter plot in which the user has complete control over the variables that

• are plotted on the x axis
• are plotted on the y-axis
• define the colours of the plotted points
• define the facet rows
• define the facet columns

library(shiny)
library(tidyverse)

ui <- fluidPage(
  selectInput("x", "X variable:", names(diamonds)),
  selectInput("y", "Y variable", names(diamonds), selected="price"),
  selectInput("colour", "Colour: ", names(diamonds), selected="color"),
  selectInput("facetRows", "Facet rows: ", names(diamonds), selected="clarity"),
  selectInput("facetCols", "Facet columns", names(diamonds), selected="cut"),
  plotOutput("plot")
)

server <- function(input, output) {
  output$plot <- renderPlot({
     diamonds %>% 
      ggplot() +
        geom_point(aes(x=!!sym(input$x), y=!!sym(input$y), colour=!!sym(input$colour)))  +
        facet_grid(rows=vars(!!sym(input$facetRows)), cols=vars(!!sym(input$facetCols)))
  })
}

shinyApp(ui = ui, server = server)

Note that the diamonds dataset is quite large and a poor choice of variables for any of the five roles I mention above can lead to lengthy delays!

I think this provides an answer to your question, but I'm not entirely sure because of the many disparate features in your code (eg saving a GIF file, use of gganimate, reference to gapminder) that do not seem relevant to the question of using UI inputs in a call to renderPlot. If I haven't given you what you want, please refine your question and code so that they reference only the elements that are critical to the fundamental issue.

This post will help you construct a minimal reproducible example.

Define column values as input for reactive shiny plot

I assume this is what you are after:

• pass the levels of diamonds$cut as input selection
• subset the diamonds dataset to the selected cut

library(shiny)
library(ggplot2)

# Define UI for application that draws a histogram
ui=shinyUI(fluidPage(

    # Application title
    titlePanel("Reactive Boxplot"),

    # Show a boxplot of the selected cut
    mainPanel(
        selectInput("column", label = h3("Column to plot"),
                    choices = c("", levels(diamonds$cut)),
                    selected = NULL,
                    width='55%',
                    multiple = FALSE),
        plotOutput("diamondshist")
    )
)
)

# Define server logic required to draw a histogram
server=shinyServer(function(input, output) {

    compute_plot <- reactive({
        if (input$column != ""){
            ggplot(subset(diamonds, cut==input$column))+
                labs(title = "From diamonds dataset")+
                geom_boxplot(aes(x = cut, y = price))+
                scale_y_reverse()
        }
    })

    output$diamondshist <- renderPlot({
        compute_plot();
    })

})

shinyApp(ui = ui, server = server)

---

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