Trying to create Shiny time-series graph of gapminder using ggplot - r

Question

I am new to Shiny and, as an exercise, I am trying to assess global trends over time using the Gapminder data set. My aim is to produce a basic app that allows me to plot life expectancy (lifeExp), population (pop) and GDP per capita (gdpPercap) over time (year) separately. However, when I enter the following code all I get is a ggplot with a straight line. What am I missing?
Thanks in advance!
library(shiny)
library(gapminder)
library(dplyr)
library(ggplot2)
ui <- fluidPage(
selectInput(inputId = "variables",
label = "Select Variable",
choices = names(gapminder[, 4:6])),
plotOutput("plot")
)
server <- function(input, output){
output$plot <- renderPlot({
data <- gapminder %>% group_by(year) %>%
summarise(lifeExp = mean(lifeExp, na.rm = T),
pop = mean(pop, na.rm = T),
gdpPercap = mean(gdpPercap, na.rm = T))
ggplot(data, aes(x = year, y = input$variables)) + geom_line()
})
}
shinyApp(ui = ui, server = server)

Answer 1

With modern versions of ggplot2 rlang, we may modify the aes call to aes(x = year, y = .data[[input$variables]])) and do:
library(shiny)
library(gapminder)
library(dplyr)
library(ggplot2)
ui <- fluidPage(
selectInput(inputId = "variables",
label = "Select Variable",
choices = names(gapminder[, 4:6])),
plotOutput("plot")
)
server <- function(input, output){
output$plot <- renderPlot({
data <- gapminder %>% group_by(year) %>%
summarise(lifeExp = mean(lifeExp, na.rm = TRUE),
pop = mean(pop, na.rm = TRUE),
gdpPercap = mean(gdpPercap, na.rm = TRUE))
ggplot(data, aes(x = year, y = .data[[input$variables]])) +
geom_line()
})
}
shinyApp(ui = ui, server = server)
Reference: https://ggplot2.tidyverse.org/dev/articles/ggplot2-in-packages.html#using-aes-and-vars-in-a-package-function