Inserting RStudio ggplot graphs into RShiny dashboard

Question

I'm trying to see if I can insert 2 ggplot charts made in RStudio into a basic dashboard in RShiny. The desired output is a basic dashboard with 2 graphs on it, one below the other. Ideally I would have one code that produces the dashboard with the 2 graphs. The code ideally will run without user interaction so that it can automatically update.

What about saving each ggplot output (as a .pdf?) and then inserting the image into the dashboard?

I've looked at : Shiny building 2 graphs one below the other

There's apparently a way to combine graphs in ggplot but my output needs to be a dashboard: Side-by-side plots with ggplot2 First the basic dashboard code:

##DASHBOARD CODE


library(shinydashboard)

dashboardPage(
  dashboardHeader(),
  dashboardSidebar(),
  dashboardBody()
)
##basic dashboard layout


library(shiny)
library(shinydashboard)

ui <- dashboardPage(
  dashboardHeader(),
  dashboardSidebar(),
  dashboardBody()
)

server <- function(input, output) { }

shinyApp(ui, server)
##viewing blank dashboard



library(shinydashboard)

ui <- dashboardPage(
  dashboardHeader(title = "Plasma Therapy"),
  dashboardSidebar(),
  dashboardBody(
    # Boxes need to be put in a row (or column)
    fluidRow(
      box(plotOutput("plot1", height = 250)),
      
      box(
        title = "Controls",
        sliderInput("slider", "Number of observations:", 1, 100, 50)
      )
    )
  )
)

server <- function(input, output) {
  set.seed(122)
  histdata <- rnorm(500)
  
  output$plot1 <- renderPlot({
    data <- ggplot(data=o2outcomes, aes(x=transfusion_date, y=ID, group=1)) +
      geom_line()+
      ylim(0, 100)+labs(y= "Number of Patients Transfused", x = "Transfusion Date")+ggtitle("Number of Patients Transfused Over Time") 
    ##create line graph 
    
  })
}

shinyApp(ui, server)

##formatting dashboard

setwd("/Users/k/Desktop/"COVID")
##set the working directory

library(readr)
library(dplyr)
library(ggplot2)
library(scales)
library(shiny)
library(grid)
library(tidyverse)
library(stringr)
library (lubridate)
library (tinytex)
install.packages("anytime")
install.packages("devtools")
library(devtools)
#load the packages needed


o2outcomes <- read.csv(
  file="patients_transfused.csv",
  stringsAsFactors = FALSE)

o2outcomes <- o2outcomes[!apply(is.na(o2outcomes) | o2outcomes == "", 1, all),]
##remove blank and NA data

view (o2outcomes)

(names(o2outcomes)[10] <- "transfusion_date")
##rename column 8 for transferring from 'character' to 'date'


o2outcomes <- transform(o2outcomes,
                        td = anytime::anytime(gsub("/20 ","/2020 ",transfusion_date))
)

o2outcomes$transfusion_date <- parse_date_time(o2outcomes$transfusion_date,
                                               orders = "%m/%d/%y %H%M")
##convert data from character into date


o2outcomes <- o2outcomes[order(o2outcomes$transfusion_date),]
##sort by date


o2outcomes <- o2outcomes[order(o2outcomes$transfusion_date), ]
o2outcomes$ID <- seq_len(nrow(o2outcomes))
##create ID to track cumulative cases

ggplot(data=o2outcomes, aes(x=transfusion_date, y=ID, group=1)) +
  geom_line()+
  ylim(0, 100)+labs(y= "Number of Patients Transfused", x = "Transfusion Date")+ggtitle("Number of Patients Transfused Over Time") 
##create line graph 

setwd("/Users/k/Desktop/COVID")
##set the working directory


library(dplyr)
library(ggplot2)
library(tidyr)
##these are the packages you would need to generate figure. This code loads the packages. 

cols<-c("AmbientAir"="lightblue","LowFlow"="blue","HighFlow"="orange","NIPPV"="purple","MechanicalVentilation"="red","ECMO"="black")
##this is setting the colors

Figure<-read.csv("Figure.csv",header=TRUE)
Figure_Event<-read.csv("Figure_Event.csv",header=TRUE)
##this loads your files

Figure_Event %>% filter(Event=="Discharged" | Event=="Death") %>% filter(Patient<26)-> Figure_Event
##this filters the Figure_Event file to relevent rows

Figure %>% drop_na(Requirement) %>% ggplot() + geom_line(aes(x=Day,y=Patient,group=Patient,col=Requirement),lwd=2.5) + scale_color_manual(values=cols) + scale_y_continuous(trans="reverse",breaks=seq(1,50,1))+scale_x_continuous(breaks=seq(-14,24,1))+theme(panel.grid.major = element_blank(),panel.grid.minor = element_blank(),panel.background = element_blank()) + geom_vline(xintercept=0) + geom_point(data=Figure_Event, aes(x=Day,y=Patient,shape=Event),size=4) + scale_shape_manual(values=c(15,22)) + scale_color_discrete(breaks=c("AmbientAir","LowFlow","HighFlow", "NIPPV","MechanicalVentilation","ECMO"))
##this makes the figure with the ggplot package and reorders the legend

Thanks