Rshiny plotting output of a loop within a function

Question

I am having trouble getting my function to plot the required chart/s in Rshiny. This same function works perfectly fine in Rmarkdown with a ggplot output. Within Rshiny if I utilise the iris dataset, I can get the function to work. However I am having trouble getting the function to work with column names being input using the selectInput function in Rshiny. I have tried to change aes to aes_string in ggplot, but I still get the same error of "Only strings can be converted to symbols".

Below is some reproducible code together with my function:

library(shiny)
library(tidyverse)
library(scales)
library(ggpubr)
scatter_fun<-function(data,xval,yval){

xval <- ensym(xval)
yval <- ensym(yval)
plot_list = list()
corr=list()
for (i in 0:3) 
{ data2<-data%>%mutate(x1=lag(!!xval,i),y1=!!yval)
p<-ggplot(data2, aes(x1, y1))+
geom_point(size=3, color="#6724C6")+
theme(axis.line.x.bottom = element_line("black"),
panel.grid.major = element_blank(), 
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line.y.left = element_line("black"),
panel.grid.major.x = element_blank(),
#axis.text.x = element_blank(),
legend.title = element_blank())+ylab(quo_name(yval))+
xlab(quo_name(xval))+
scale_y_continuous(labels = scales::comma)+
scale_x_continuous(labels = scales::comma)+
expand_limits(y = 0)+
geom_smooth(se=FALSE,method='lm', colour="gray48")+ggtitle(paste0("Lag",i))+
annotate(geom = 'text', label=paste0("R=",round(cor(data2[,"x1"],
data2[,"y1"],
use = "complete.obs",method="spearman" ),2)), x = -Inf, y = Inf, hjust = 0, vjust = 1)
plot_list[[i+1]] =p
q=round(cor(data2[,"x1"],
data2[,"y1"],
use = "complete.obs",method="spearman" ),2)
corr[[i+1]]=q
corr<<-corr
}
return(plot_list)}


dataset<-iris



ui <- fluidPage(
titlePanel("Example"),
fluidRow(
column(7,
       selectInput("variable1", "Variable 1:",
                   choices=names(dataset[1:4]))),
column(7,
      selectInput("variable2", "Variable 2:",
                  choices=names(dataset[1:4])))),
mainPanel(
plotOutput("distPlot")
))


server <- function(input, output) {

output$distPlot <- renderPlot({

#m<-scatter_fun(iris, Petal.Length, Petal.Width)
m<-scatter_fun(dataset, input$variable1, input$variable2)
print(ggarrange(plotlist=m, ncol=2,nrow=3, common.legend = T))
})
}


shinyApp(ui = ui, server = server)

Answer 1

Try this

library(shiny)
library(tidyverse)
library(scales)
library(ggpubr)
scatter_fun<-function(data,xval,yval){

  # xval <- ensym(xval)
  # yval <- ensym(yval)
  
  plot_list = list()
  corr=list()
  for (i in 0:3) 
  { data2<-data %>% mutate(x1=lag(.data[[xval]],i),y1=.data[[yval]])
  p<-ggplot(data2, aes(x1, y1))+
    geom_point(size=3, color="#6724C6")+
    theme(axis.line.x.bottom = element_line("black"),
          panel.grid.major = element_blank(), 
          panel.grid.minor = element_blank(),
          panel.background = element_blank(),
          axis.line.y.left = element_line("black"),
          panel.grid.major.x = element_blank(),
          #axis.text.x = element_blank(),
          legend.title = element_blank())+ylab(yval) +
    xlab(xval)+
    scale_y_continuous(labels = scales::comma)+
    scale_x_continuous(labels = scales::comma)+
    expand_limits(y = 0)+
    geom_smooth(se=FALSE,method='lm', colour="gray48")+ggtitle(paste0("Lag",i))+
    annotate(geom = 'text', label=paste0("R=",round(cor(data2[,"x1"],
                                                        data2[,"y1"],
                                                        use = "complete.obs",method="spearman" ),2)), x = -Inf, y = Inf, hjust = 0, vjust = 1)
  plot_list[[i+1]] =p
  q=round(cor(data2[,"x1"],
              data2[,"y1"],
              use = "complete.obs",method="spearman" ),2)
  corr[[i+1]]=q
  corr<<-corr
  }
  return(plot_list)}


dataset<-iris

ui <- fluidPage(
  titlePanel("Example"),
  fluidRow(
    column(7,
           selectInput("variable1", "Variable 1:",
                       choices=names(dataset[1:4]))),
    column(7,
           selectInput("variable2", "Variable 2:",
                       choices=names(dataset[1:4])))),
  mainPanel(
    plotOutput("distPlot")
  ))


server <- function(input, output) {
  
  output$distPlot <- renderPlot({
    #m<-scatter_fun(iris, Petal.Length, Petal.Width)
    m<-scatter_fun(dataset, input$variable1, input$variable2)
    print(ggarrange(plotlist=m, ncol=2,nrow=3, common.legend = T))
  })
}

shinyApp(ui = ui, server = server)