Incorporating Shiny app sliders into ggplot graphs - r

Question

I am trying to filter the dataframe that I use for my graph based on the input values from two sliders. I have sliders that select a range for temperature and wind speed in a given NFL game. (Each row of the dataframe is a quarterback's performance in a game along with game weather and QB measurables, so at least two rows per game.) How do I take the output from the sliders and filter the dataframe based on that? For example, how do I filter df$temperature based on the slider with id "z"?
library(shiny)
library(dplyr)
library(ggplot2)
library(tidyr)
df = read.csv("Combined_QB_Game_Data.csv")
df[df == "--"] = NA
df$Passes.Completed = as.double(df$Passes.Completed)
df$Passes.Attempted = as.double(df$Passes.Attempted)
df$Completion.Percentage = as.double(df$Completion.Percentage)
df$Passing.Yards = as.double(df$Passing.Yards)
df$Passing.Yards.Per.Attempt = as.double(df$Passing.Yards.Per.Attempt)
df$TD.Passes = as.double(df$TD.Passes)
df$Sacks = as.double(df$Sacks)
ui = fluidPage(
titlePanel("QB Performance"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "x",
label = "Options:",
choices = c("Ht", "Wt",
"Forty", "Vertical", "BenchReps",
"BroadJump", "Cone", "Shuttle", "Round", "Pick"),
selected = "Ht"),
selectInput(inputId = "y",
label = "Options2:",
choices = c("Passer.Rating","Passes.Completed","Passes.Attempted","Completion.Percentage","Passing.Yards","Passing.Yards.Per.Attempt","TD.Passes","Ints","Sacks"),
selected = "Passer.Rating"),
sliderInput("z", "Tempurature",
min = 0, max = 100, value = c(25, 75)),
sliderInput("a", "Wind",
min = 0, max = 30, value = c(5, 25))
),
mainPanel(
plotOutput(outputId = "scatterplot")
)
)
)
server = function(input, output) {
output$scatterplot = renderPlot({
p = ggplot(data = df) +
aes_string(x = input$x, y = input$y) +
geom_point()+
geom_smooth(method = "lm")
plot(p)
})
}
shinyApp(ui, server)

Answer 1

One possibility is to treat the data in a reactive conductor:
ggdata <- reactive({
bounds <- input$z
df %>% filter(temperature > bounds[1], temperature < bounds[2])
})
and then use it in the renderPlot:
output$scatterplot = renderPlot({
ggplot(data = ggdata()) +
aes_string(x = input$x, y = input$y) +
geom_point() +
geom_smooth(method = "lm")
})