R Shiny Error: Cannot Coerce Type 'Closure' to Vector of Type 'Double'

r shiny - cannot coerce type 'closure' to vector of type 'double'

Try this:

library(tidyverse)
library(shiny)

df2 <- tibble(years = c(2012,2013,2014,2015))

ui <- fluidPage(
    sidebarLayout(
        sidebarPanel(
        sliderInput("year_range",
                    "Select Years:",
                    min = 2012,
                    max = 2019,
                    value = c(2012, 2019),
                    ticks = FALSE)),
        mainPanel(tableOutput('table'))
    )
)

server <- function(input, output) {
    
     
    output$table <-  renderTable({
    filter(df2, years >= input$year_range[1], years <= input$year_range[2])
    })
}

shinyApp(ui = ui, server = server)

R shiny cannot coerce type 'closure' to vector of type 'double'

The issue was resolved by using a switch in selectInput:

 pkt <- reactive({
    switch(input$points,
           "Powod utraty pracy" = joblost,
           "Plec" = sex,
           "Nie-bialy" = nwhite,
           ">12 lat szkoly" = school12,
           "Robotnik fizyczny" = bluecol,
           "Mieszka w miescie" = smsa,
           "Zonaty" = married,
           "Ma dzieci" = dkids,
           "Male dzieci" = dykids,
           "Glowa rodziny" = head,
           "Otrzymuje zasilki" = ui)
  })

  txt <- renderText({paste(input$points)})

  output$Plot <- renderPlot({
    plot(as.formula(formula()),data=Benefits,
         main  = caption(), pch = as.numeric(pkt()), 
         col=as.numeric(pkt()))

Cannot coerce type 'closure' to vector of type list when creating a lag variable by id

Don't use quotes around the column name.

library(data.table)
TandCtable[, RDexp_pre1 := c(NA, RD_expenses[-.N]), by=id]

If you want lag of different offset length it is better to use shift as suggested by @Waldi instead of appending NA's.

TandCtable[, RDexp_pre1 := shift(RD_expenses, 2), by=id]

Don't understand Cannot Coerce type 'closure' Error

TidySymptoms data has no id column in it. Assuming it's a mistake and you have that already in your data you can do the following changes in the function.

• There is no need to pass df.new to the function.
• The column in TidySymptoms is called as word but you are using text in the function.

Try this code.

minus_TextNum <- function(df){

  df.new <- mutate(df, text = gsub(x = word, pattern = "[0-9]+|\\(.*\\)", replacement = "")) %>%  
    unnest_tokens(input = text, output = word) %>% 
    filter(!word %in% c(stop_words$word, "patient")) %>% 
    group_by(id) %>% 
    summarise(text = paste(word, collapse = " "))
    return(new.df)
}

minus_TextNum(TidySymptoms)

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