Slider with years for barplot - r

Question

I am trying to get a slider within my barplot page to make the data interactive per year.
#library
library(dplyr)
library(shiny)
library(shinythemes)
library(ggplot2)
#Source
dataset <- read.csv("Wagegap.csv")
SFWage <- dataset %>%
group_by(gender,JobTitle, Year) %>%
summarise(averageBasePay = mean(BasePay, na.rm=TRUE)) %>%
select(gender, JobTitle, averageBasePay, Year)
clean <- SFWage %>% filter(gender != "")
#UI
ui <- fluidPage(
theme = shinytheme("united"),
navbarPage("San Fransisco Wages",
tabPanel("Barplot",
mainPanel(
plotOutput("barplot")
)) ,
tabPanel("Table",
mainPanel(
dataTableOutput("table")
))
)
)
#server
server <- function(input, output){
output$barplot <- renderPlot({
ggplot(clean, aes(x = JobTitle, y = averageBasePay ))+
geom_bar(stat="Identity", width = 0.3, fill="orange")+
labs(x= "Jobs", y = "Wage", title = "Wage per job")
})
output$table <- renderDataTable({
clean
})
}
#Run App
shinyApp(ui = ui, server = server)
I don't fully understand it yet how to put this input in.
I have tried sliding it into the navbarpage but I can't figure out how it works.
I also tried making year reactive but with no success.

Answer 1

It's not the year that has to be reactive; it's the whole data frame. Therefore, in your ui, you can do:
[...]
tabPanel("Barplot",
mainPanel(
sliderInput("year", label = "Which year should be displayed?", min = 1900, max = 2020, step = 5, value = 2000) # new
plotOutput("barplot")
)) ,
[...]
I put it there for convenience; the layout is yours. I tried do change as little as possible.
The server would then have:
server <- function(input, output){
# NEW ########################################
clean <- reactive({
SFWage <- dataset %>%
group_by(gender,JobTitle, Year) %>%
summarise(averageBasePay = mean(as.numeric(BasePay), na.rm=TRUE)) %>% # Notice the as.numeric()
select(gender, JobTitle, averageBasePay, Year)
SFWage %>% filter(gender != "" & Year == input$year)
})
# OLD ########################################
output$barplot <- renderPlot({
ggplot(clean(), aes(x = JobTitle, y = averageBasePay ))+ # Parenthesis
geom_bar(stat="Identity", width = 0.3, fill="orange")+
labs(x= "Jobs", y = "Wage", title = "Wage per job")
})
output$table <- renderDataTable({
clean() # Parenthesis
})
}
Don't forget to add the parenthesis, as I did here.
This should work, but I might have mistyped something or got it completely wrong. Since I don't have your data, I can't test it.
EDIT: Due to your comment, I added the as.numeric() term, as you can see above. However, if your data is not only not numeric but also with ,, you can do:
[...]
summarise(averageBasePay = mean(as.numeric(gsub(",", ".", BasePay)), na.rm=TRUE)) %>% # Notice the as.numeric() and the gsub()
[...]