Shiny app multiple regression - r

Question

library(shiny)
ui <- fluidPage(
titlePanel("Linear model DARP"),
sidebarLayout(
sidebarPanel(
sliderInput(inputId = "area",
"select the service region area:",
min= 170,
max= 8000,
value=1001),
sliderInput(inputId = "crit..peak",
label="Choose Peak demand:",
min=10,
max=150,
value=39)
),
mainPanel(
tableOutput("table")
)
)
)
server <- function(input, output) {
output$table <- renderTable({
df_ln<-read.csv("F:/Project/Programme/ML/DAR Machine Learning TR Part A/train_darp_ln.csv")
Linearmodel_DARP<-lm(veh~area+crit..peak,data = df_ln)
new_demand1<-data.frame(area=input$area)
new_demand2<-data.frame(crit..peak=input$crit..peak
fleetsize<-predict(Linearmodel_DARP,newdata=c(new_demand1,new_demand2))
round(exp(fleetsize),0)
})
}
shinyApp(ui = ui, server = server)
I am getting error object crit..peak is not found when running the app
The app should take two inputs from the user through the slider and based on the multiple regression it will give a prediction of the predict command
please help as I need to do it soon for a project
structure(list(area = c(2217.7, 6537.4, 1705.5, 5634, 1260.5,
4797.7), density = c(0.13753, 0.016826, 0.18469, 0.021477, 0.25862,
0.027305), crit..CV = c(0.63954, 0.81437, 0.49909, 0.33935, 0.39148,
0.17489), crit..peak = c(49L, 26L, 41L, 20L, 39L, 18L), TW = c(21L,
47L, 54L, 48L, 17L, 41L), L = c(569L, 576L, 391L, 390L, 458L,
392L), s = c(7L, 3L, 3L, 6L, 3L, 2L), speed = c(18L, 26L, 20L,
30L, 24L, 33L), circuity = c(1.3284, 1.1494, 1.4597, 1.2725,
1.0486, 1.0792), cap = c(9L, 9L, 5L, 8L, 5L, 7L), mrt = c(1.5452,
2.3743, 1.5962, 2.6065, 2.1278, 2.6228), veh = c(4.605170186,
3.433987204, 4.718498871, 3.951243719, 4.060443011, 3.526360525
), veh.hrs = c(6.665569062, 5.523778231, 6.496186582, 5.71857256,
5.816843267, 5.256713817), veh.km = c(9.555940819, 8.781874769,
9.491918855, 9.119769942, 8.994897097, 8.753221378)), .Names = c("area",
"density", "crit..CV", "crit..peak", "TW", "L", "s", "speed",
"circuity", "cap", "mrt", "veh", "veh.hrs", "veh.km"), row.names = c(NA,
6L), class = "data.frame")

Answer 1

Ok, so your problem is probably due to the way you try to make your new data frame. You made two separate 1 dimensional data frames and then concatenated them, which generated a list of dataframes. To make a data frame with two or more variables, define them in your data frame definition or use cbind to join the data frames together:
new_demand <- data.frame(area = input$area,
crit..peak = input$crit..peak)
fleetsize <- predict(Linearmodel_DARP, newdata = new_demand)
This should solve your problem. In the future, when you get errors like error object ... is not found, the first thing to do is check that the objects you're generating are what you think they are. The class function would have told you that c(new_demand1, new_demand2) is a list not a data.frame

Answer 2

The error could be because of read.csv as it's missing header = T.
Let's try this chunk of code
server <- function(input, output) {
output$table <- renderTable({
df_ln <- read.csv("F:/Project/Programme/ML/DAR Machine Learning TR Part A/train_darp_ln.csv", header = T)
Linearmodel_DARP <- lm(veh~area+chrit..peak, data = df_ln)
new_demand1 <- data.frame(area=input$area)
new_demand2 <- data.frame(crit..peak=input$crit..peak)
fleetsize <- predict(Linearmodel_DARP, newdata=c(new_demand1, new_demand2))
round(exp(fleetsize), 0)
})
}