How to Create a Reactive Base R Boxplot in Shiny? - r

Question

I have my data frame named df...
pain_severity = c(1, 5, 10, 8, 6, 4)
urinary_severity = c(3, 8, 9, 7, 6, 10)
df = data.frame(pain_severity, urinary_severity)
I let the user choose whether they want pain or urinary severity in select input...
UI:
tabPanel("1-Variable Visualization",
sidebarLayout(
sidebarPanel(
h1("Menu Selection"),
selectInput(inputId = "variable_choice",
label = "Variable",
choices = df,
selected = "pain_severity")
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("Boxplot", plotOutput("boxplot")),
)))))
SERVER:
server <- function(input, output, session) {
output$boxplot <- renderPlot({
boxplot(input$variable_choice,
data = df,
main = "", xlab="", ylab = "", horizontal = TRUE)
points(mean(input$variable_choice, na.rm = TRUE),
data = df,
1,
col = "red")
})
}
I keep getting an error that reads... ERROR: non-numeric argument to binary operator
Why does this happen? When I run the code in base R using just pain or urinary severity as my variable it works perfectly. When I ask it to adapt based on user input from variable_choice, it gives me that error message. Do I have to use ggplot when trying to run user inputs?

Answer 1

Your code has several issues:
the choices argument should only take a vector of column names, try choices = colnames(df)
the plot functions either need a formula (however I couldn't make it work without a grouping variable) or the data itself. Try:
output$boxplot <- renderPlot({
boxplot(df[input$variable_choice],
main = "", xlab=input$variable_choice, ylab = "", horizontal = TRUE)
points(mean(df[input$variable_choice], na.rm = TRUE),
1,
col = "red")
})
In this way, you use the character input$variable_choice to index your data.frame

Answer 2

Thank you. Starja is right. I have a more in depth code for choices based on user selections that I felt would bog down the original question so I simplified it by just writing df, but I should have said colnames(df), you're right. The boxplot works perfectly, but the point returns an NA value and the error says "argument is not numeric or logical: returning NA" and the point does not show up on the graph.
My solution to this was to use colMeans and define it in the server like so...
SERVER:
col_mean <- colMeans(filtered_data()[1:908], na.rm = TRUE)
points(col_mean[input$variable_choice], 1, col = "red")
I created col_mean to grab the first 908 numeric columns in my dataset and convert it to a one mean point in a new dataset. I then used that new dataset in points which gave me the correct mean display for each.