Trying to edit a reactive database so that updates to the database are reflected in the output. Have tried numerous variants, but none are working, general idea is shown - where I would like to have the figure update with changes to the database.
library(tidyverse)
library(shiny)
library(DT)
# Define UI for application that draws a histogram
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
sliderInput("ages", "Max age:", 10, 100, 15),
sliderInput("nsamp",
"Sample size:",
min = 10,
max = 1000,
value = 100)),
mainPanel(dt_output('Sample sizes and weighting', 'x1'),
plotOutput("fig"))
)
)
server <- function(input, output) {
x = reactive({
df = data.frame(age = 1:input$ages,
samples = input$nsamp,
weighting = 1)
})
output$x1 = renderDT(x(),
selection = 'none',
editable = TRUE,
server = TRUE,
rownames = FALSE)
output$fig = renderPlot({
ggplot(x(), aes(age, samples))
geom_line()
geom_point()
})
}
shinyApp(ui = ui, server = server)
CodePudding user response:
We can use input$x1_cell_edit
and reactiveValues
to modify the data that is passed to the plot.
Note the use of isolate
inside renderDT
, that is to prevent the table from re-rendering when db$database
is modified.
library(tidyverse)
library(shiny)
library(DT)
# Define UI for application that draws a histogram
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
sliderInput("ages", "Max age:", 10, 100, 15),
sliderInput("nsamp",
"Sample size:",
min = 10,
max = 1000,
value = 100
)
),
mainPanel(
dataTableOutput("x1"),
plotOutput("fig")
)
)
)
server <- function(input, output) {
# all the data will be stored in this two objects
db <- reactiveValues(database = NULL)
# to store the modified values
edited_vals <- reactiveVal(tibble(row = numeric(), col = numeric(), value = numeric()))
# create a new table each time the sliders are changed
observeEvent(c(input$ages, input$nsamp), {
df <- data.frame(
age = 1:input$ages,
samples = input$nsamp,
weighting = 1
)
db$database <- df
})
observeEvent(input$x1_cell_edit, {
db$database[as.numeric(input$x1_cell_edit$row), as.numeric(input$x1_cell_edit$col 1)] <- as.numeric(input$x1_cell_edit$value)
})
output$x1 <- renderDT(
{
input$ages
input$nsamp
datatable(
isolate(db$database),
selection = "none",
editable = TRUE,
rownames = FALSE,
options = list(stateSave = TRUE)
)
},
server = TRUE
)
output$fig <- renderPlot({
ggplot(db$database, aes(as.numeric(age), as.numeric(samples)))
geom_point()
geom_line()
})
}
shinyApp(ui = ui, server = server)