I am relatively new to Shiny, and currently struggling at putting together a simple Shiny app that does the following job:
Have a table with 10 rows and 2 columns (x and y). The table is blank at initiation, and is completely user editable through using library(DT). All the data points are through user inputs. Let's restrict x and y to be only positive numbers.
Have a graph on the right side (or at bottom). Once user finishes inputting 20 values in the table (10 x values & 10 y values), click on an actionbutton, and the graph will ** draw a scatterplot ** using those 10 sets of value points, and fit a line through those points.
If the user wants to make any edits to the table, he/she edits the table directly, and click on the actionbutton again to re-draw a new scatterplot, and re-fit a line.
I am struggling at how to make the user inputs in the table into the inputs of that scatterplot and eventually fit a line through. This task is unlike my previous work, where I only have to build an interactive shiny app using data from an existing dataset (e.g. read a csv).
Here's an app I created quickly that I believe fits your requirements, this article was helpful in the editing piece.
library(shiny)
library(DT)
library(tidyverse)
ui <- fluidPage(
# Application title
titlePanel("Editable Dataframe and Plot"),
# Sidebar
sidebarLayout(
sidebarPanel(
DTOutput("my_datatable"),
actionButton("go",label = "Plot Data")
),
# Show plot
mainPanel(
plotOutput("my_plot")
)
)
)
server <- function(input, output) {
#initialize a blank dataframe
v <- reactiveValues(data = {
data.frame(x = numeric(0),y = numeric(0)) %>%
add_row(x = rep(0,10),y = rep(0,10))
})
#output the datatable based on the dataframe (and make it editable)
output$my_datatable <- renderDT({
DT::datatable(v$data, editable = TRUE)
})
#when there is any edit to a cell, write that edit to the initial dataframe
#check to make sure it's positive, if not convert
observeEvent(input$my_datatable_cell_edit, {
#get values
info = input$my_datatable_cell_edit
i = as.numeric(info$row)
j = as.numeric(info$col)
k = as.numeric(info$value)
if(k < 0){ #convert to positive if negative
k <- k * -1
}
#write values to reactive
v$data[i,j] <- k
})
#render plot
output$my_plot <- renderPlot({
req(input$go) #require the input button to be non-0 (ie: don't load the plot when the app first loads)
isolate(v$data) %>% #don't react to any changes in the data
ggplot(aes(x,y)) +
geom_point() +
geom_smooth(method = "lm")
})
}
# Run the application
shinyApp(ui = ui, server = server)
Thanks so much! This is EXACTLY what I am looking for.
Your code does exactly what I am looking for, and your detailed comments help me understand the flow of reactivity in certain parts of the server. The article you linked is very helpful as well.