How to show linear regression on brushed points in shiny app - r

Question

Edited: I removed to the call to get a dataset from data.world and instead fed in the mtcars dataset which produces the same error of contrasts can only be applied to factors of 2 or more
I am learning shiny and wanted to create a plot that gives the linear regression line for both a) the whole plot and b) linear regression line for brushed points on the plot. I would even settle for just showing the summary stats for the regression of the brushed points.
The code below
plots the user inputs for x and y
allows the user to brush points
creates a reactive datasubset of brushed points
shows summary of the regression for all points
shows data table of the reactive datasubset of brushed points when a brush is applied
breaks down when asked to perform a regression on those brushed points for reasons I do not understand...
code:
library(shiny)
library(ggplot2)
library(data.world)
library(dplyr)
library(tidyverse)
library(DT)
#show data from data.world
gcdata_ds <- "https://data.world/llawsonwork/gcdata"
#gcdatafile <- data.world::query(
#qry_sql("SELECT * FROM gcdataclean"),
#dataset =gcdata_ds
#)
#datafile <- gcdatafile
#so that you will not need data.world
datafile <-mtcars
# Define UI for application that draws a histogram
ui <- fluidPage(
#Application Layout
sidebarLayout(
#Inputs
sidebarPanel(
#select variable for y-axis
selectInput(inputId = "ya",
label = "Y-axis",
choices = colnames(datafile),
selected = "life_expec"
),
#Select Variable for x axis
selectInput(inputId = "xa",
label = "X-axis",
choices = colnames(datafile),
selected = "life_expec"
)
),
#output
mainPanel(
plotOutput(outputId = "guilfordplot", brush = "plot_brush"),
htmlOutput(outputId = "summary"), # summary of lin regress all points
dataTableOutput(outputId = "brushedtracts"), # data table to make sure brushed points are updating correctly
textOutput(outputId = "brushedreg") # NOT Working summary of lin reg brushed points
)
)
)
#define server function
server <- function(input, output){
#this was useful in creating the regression model as X was always column 1 and Y was always column in this dataframe
datasubset <- reactive({
req(input$xa)
req(input$ya)
data.frame(X = datafile[input$xa], Y = datafile[input$ya])
})
#create datasubset of the brushed points
brushedsubset <- reactive({
req(input$xa)
req(input$ya)
req(input$plot_brush)
brushedPoints(datafile, brush = input$plot_brush) %>%
select(input$xa, input$ya)
})
#Create plot
output$guilfordplot <- renderPlot({
ggplot(data = datafile, aes_string(x = input$xa, y = input$ya)) +
geom_point() + geom_smooth(method = "lm")
})
#create summary file
output$summary <- renderUI({
model = lm(datasubset()[,2] ~ datasubset()[,1], data = datasubset())
r2 = format(summary(model)$r.squared, digits = 3)
txt = paste("The equation of the line is :\nY = ",
round(coefficients(model)[1],0), " + ",
round(coefficients(model)[2], 5), "X")
# str_3 <- format(coef(m)[1], digits = 3)
str_1 <- txt
str_2 <- paste("The R^2 value is equal to ", r2)
HTML(paste(str_1, str_2, sep = '<br/>'))
})
# create data table
output$brushedtracts <- DT::renderDataTable({
select(brushedsubset(), input$xa, input$ya)
})
# create brushed summary stats
output$brushedreg <- renderText({
modelbrush = lm(brushedsubset()[,2] ~ brushedsubset()[,1], data = brushedsubset())
br2 = format(summary(modelbrush)$r.squared, digits = 3)
btxt = paste("The equation of the line is :\nY = ",
round(coefficients(modelbrush)[1],0), " + ",
round(coefficients(modelbrush)[2], 5), "X")
paste(btxt, ' and the rsquared is: ', br2 )
})
}
# Run the application
shinyApp(ui = ui, server = server)
So the code above works for the summary regression of all points for a given x and y input.
But this code does not work for giving me the linear regression of the brushed points and I cannot figure out why because it is the nearly identical for the code for the linear regression of all points.
Any help would be appreciated and it there is a tidyer way of doing the linear regression and summary stats please let me know.