Unable to render Gauge from Flexdashboard library in Shiny app - r

Question

I am trying to create a Shiny app which
a) prompts user to upload a file which contains numeric data,
b) reads the file and assigns the data points to different variables,
c) calculates new variables from the captured variables
d) display a 'Gauge' using the calculated variables
The code successfully executes but the Gauge chart is not rendered properly. There is no error or warning message either. Instead, I am getting the following message:
"Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON."
And instead of the gauge output I am getting that tiny spec in the middle, as seen in the attached image.
The entire code is fairly long, hence providing just the relevant snippets of code.
Would really appreciate if you can help fix this.
library(shiny)
library(flexdashboard)
ui <- fluidPage(
tabPanel("Sensitivity Analysis",
sidebarLayout(
sidebarPanel(
uiOutput("Sensitivity_Analysis")
),
mainPanel(
gaugeOutput("sensitivity", width = "600px", height = "600px")
)
)
),
server <- function (input, output)
{
output$input_financials=renderUI({
fluidRow(fileInput("file1", "Choose CSV File",multiple = FALSE,accept = c("text/csv","text/comma-separated-values,text/plain",".csv")),
actionButton("process","Process"))})
data_input=reactiveValues()
observeEvent(input$process,{
file_input <- input$file1
if (is.null(file_input)) {
return(NULL)}
## File is read and all the inputs are assigned to variables
....
## Output for Gauge begins
output$sensitivity <- flexdashboard::renderGauge({
gauge_limit <- data_input$wc_value
data_input$cash_rel_dpo <- ## Formula for cash_del_dpo
data_input$cash_rel_dro <- ## Formula for cash_del_dro
data_input$cash_rel_dio <- ## Formula for cash_del_dio
data_input$wc_predicted_value <- (data_input$wc_predicted_value - data_input$cash_rel_dpo - data_input$cash_rel_dro - data_input$cash_rel_dio)
gauge(data_input$wc_predicted_value, min = 0, max = gauge_limit,
gaugeSectors(success = c(0, 10000),
warning = c(10001, 50000),
danger = c(50001, 1000000000))
)
})
shinyApp(ui = ui, server = server)
Screenshot of the output generated upon executing the code

Answer 1

There's a similar gauge in package billboarder, try this example:
library(shiny)
library(billboarder)
ui <- fluidPage(
tabPanel(
title = "Sensitivity Analysis",
sidebarLayout(
sidebarPanel(
fileInput("file1", "Choose CSV File",
multiple = FALSE,
accept = c("text/csv","text/comma-separated-values,text/plain",".csv")),
actionButton(inputId = "process", label = "Process (click here to refresh the gauge)")
),
mainPanel(
billboarderOutput("sensitivity", width = "400px", height = "400px")
)
)
)
)
server <- function (input, output) {
data_input <- reactiveValues(x = 0)
observeEvent(input$process, {
data_input$x <- sample.int(1e5, size = 1)
}, ignoreInit = TRUE)
## Output for Gauge begins
output$sensitivity <- renderBillboarder({
billboarder() %>%
bb_gaugechart(
value = data_input$x,
name = "Predicted value",
steps = c(1e4, 5e4, 1e5),
steps_color = rev(c("#FF0000","#F6C600", "#60B044"))
) %>%
bb_gauge(
min = 0, max = 1e5,
units = "",
label = list(
format = htmlwidgets::JS("function(value, ratio) {return d3.format(',')(value);}") # format value with thousand separator
),
width = 80
)
})
}
shinyApp(ui = ui, server = server)