Shiny Dashboard with plot - shiny

Question

I am learning some shiny in order to do a dashboard. I have an idea. I want to create a dashboard that select from an selectinput a variable, group by such variable and plot a barplot or histogram of the total of that variable.
I have generated a sample dataset to generate what I need, however I can´t get what I need.
The UI code is the next one:
library(shiny)
shinyUI(fluidPage(
titlePanel("Demo dashboard"),
sidebarLayout(
sidebarPanel(
selectInput("variable",
"group by",
choices = c("City","Country")
)
),
mainPanel(
plotOutput("distPlot")
)
)
))
The server code is the next one, Here I aggregate by the variable that is the input and plot the total
library(shiny)
library(dplyr)
shinyServer(function(input, output) {
output$distPlot <- renderPlot({
sample<-tbl_df(data.frame(c("City1","City2","City3","City1","City2","City3","City2","City3"),
c("A","B","C","D","D","A","A","B"),
c(12,14,15,12,12,14,8,10)))
colnames(sample)<-c("City","Country","Amount")
df1<-sample%>%group_by(input$variable)%>%
summarise(total=sum(Amount))
sample%>%group_by(input$variable)%>%summarise(total=sum(Amount))
x<- df1$total
hist(x)
})
})
A screen capture of my result is the next:
however this is not the expected result. I can´t get the histogram required

Answer 1

The problem is your usage of dplyr:
Your original code doesn't evaluate input$variable to group by city, rather tries to group by a non-existing column called `input$variable`:
sample %>%
group_by(input$variable) %>%
summarise(total=sum(Amount))
Result:
# # A tibble: 1 x 2
# `input$variable` total
# <chr> <dbl>
# 1 City 97
You can check this yourself easily by adding either a print statement after the statement (e.g.: print(df1)) or adding a browser() before the statement.
This behaviour is because dplyr uses non-standard-evaluation by default. You can read up more about that here.
To use standard (programmable) evaluation you need to unquote input$variable so that the value is passed to dplyr. In the current version you can do that using a combination of !! and sym.
Example:
sample %>%
group_by(!!sym(input$variable)) %>%
summarise(total=sum(Amount))
Result:
# # A tibble: 3 x 2
# City total
# <fct> <dbl>
# 1 City1 24
# 2 City2 34
# 3 City3 39
Histogram:
Edit: Some more explanation: group_by doesn’t evaluate its input, but rather it quotes it: That's why you're getting `input$variable` as a column name.
On the other hand: the sym function turns the actual value of input$variable into a symbol, then !! can be used to remove the quoting:
What works in dplyr is if you don't have quotes around the input, so: group_by(City)
Let's see what happens step by step:
sym(input$variable) returns "City". group_by("City") would still not work because the input has quoting around it!
That's why we need to use !!: !! sym(input$variable) returns City without quotes. So the expression evaluates to group_by(City), and thus will work as expected.