Object not found when building a random forest regression

Question

I am working on my first shiny app, trying to build a random forest regression to predict the arrest charge for a Crime Dataset. I got an error said object offense_category not found when running the app. I have tried many suggestions online but it's still not working.

Here is my current ui.R code:

ui <- fluidPage(theme = shinytheme("united"),
                
                #header
                headerPanel("Prediction"),
                #inputs
                sidebarPanel(
                  h2("Filter"),
                  
                  selectizeInput("offense_category", label="Offense Category", choices=c("", sort(unique(df$offense_category))),multiple=FALSE),
                  radioButtons(
                    "year",
                    "Select year",
                    choices = c("2020", "2021","2022","2023"),
                    selected = "2020"
                  ),
                  selectizeInput("neighborhood", label="Neighborhood", choices=c("", sort(unique(df$neighborhood))),multiple=FALSE),
                  actionButton("predictbutton", "Predict", class = "btn btn-primary")
                ),
                mainPanel(h2("Prediction"), 
                          tableOutput(outputId = 'chargeprediction'))
)

And my server.R code:

server <- function(input, output){
  #input data
  datainput <- reactive({
    result <- data.frame(
      Name = c("Offense Category",
               "Year",
               "Neighborhood"),
      Value = as.character(c(input$offense_category,
                           input$year,
                           input$neighborhood)),
      stringsAsFactors=FALSE)
    Estimate_charge <- 0
    result <- rbind(result, Estimate_charge)
   
    write.table(result, "result.csv", sep="", quote=FALSE, row.names=FALSE, col.names=FALSE)
    test <- read.csv(paste("result",".csv",sep=""),header=TRUE)
    
    Output <- data.frame(Prediction=predict(rf,test), round(predict(rf,test,type="prob"),1))
    print(Output)
  })
  output$chargeprediction <- renderTable({
    if (input$predictbutton > 0){
      isolate(datainput())
    }
  })
}

And here is the error in console for your reference:

If the code runs properly, it should output a table containing the predicted result, and the corresponding probability of that prediction.

Random Forest model: rf <- randomForest(charge ~ offense_category+year+neighborhood, data=trainingset, ntree=500, importance=TRUE)