My goal is to retrieve data from a googlesheet and map it on a leaflet map.
Everything is working fine, only if the code to retrieve data from googlesheet is placed in the global.R and it is only valid for that session of the running shiny app. However, if meanwhile the sheet is updated, these updates are not reflected in the running session. So I need to wire up a ui.R button to fetch new data each time the button is fired and pass the data onto the relevant codes in server.R . (I hope this is clear).
In my current setup, the data gets downloaded from googlesheet (via global.R) and passed on to the environment and used for that running app session.
Here is my working shiny app setup:
ui.R
...
leafletOutput("map"),
actionButton("button", "Get New Data")
...
#added the below lines to update the question:
selectInput("Country",
"Country:",
c("All",
unique(as.character(draw$Country))))
server.R
shinyServer(function(input, output, session) {
#...
output$map <- renderLeaflet({
#... some options here
})
draw <- mydata
drawvalue <- reactive({
if (input$year == year1){return(mydata)} else {
filtered <- filter(mydata, Type == input$type1)
return(filtered)
}
})
observe({
#... some other variable definitions
colorBy <- input$color ##added to update the question
sizeBy <- input$size ##added to update the question
draw <- drawvalue()
colorData <- draw[[colorBy]] ##added to update the question
#... code related to the leaflet
})
#...
}
global.R
mydata <- gs_read(gs_key("0123456abcdabcd123123123"))
After some reading and exploring, I am told that I have to use reactive and observeEvent. But my faulty setup results in error, saying that 'object "mydata" not found'.
I tried in the server.R: (I know the code below is all faulty)
observeEvent(input$button,{
mydata <- gs_read(gs_key("0123456abcdabcd123123123"))
})
mydata <- eventReactive(input$button,{
mydata()
})
update:
in my ui.R, I also refer to "draw", this also bugs. How should I change this one? I updated the lines in the ui.R above in the question. this line is part of the ui.R line which call the DT package to show some tables.
by the way, this app is based on the superzip shiny app.
NB: I will give 100 points bounty for the accepted answer.
In general observe and observeEvent do not return any value and they are used for side effects. So this part of the code below doesn't return any value and even if you used <<- to override the variable mydata shiny wouldn't know that its value has changed.
observeEvent(input$button,{
mydata <- gs_read(gs_key("0123456abcdabcd123123123"))
})
So if you want shiny to know when the data is updated you should read it within reactive environment. So, instead of reading the data via global.R I would advice to do following within server.R:
mydata <- eventReactive(input$button, {
gs_read(gs_key("0123456abcdabcd123123123"))
})
After clicking the button shiny would read (new) data which could be then accessed with mydata() and passed to the render* functions and other reactive parts of the code. For example:
drawvalue <- reactive({
if (input$year == year1){return(mydata() )} else { # added ()
filtered <- filter(mydata(), Type == input$type1) # added () to mydata
return(filtered)
}
})
You had to change this part of code
draw <- drawvalue()
to
draw <- reactive({ drawvalue() })
and then access it with draw()
UPDATE:
If you want make choices of the widget selectInput from UI.R dependent on draw you can do following:
1) Add the parameter session to the server function for updateSelectInput
shinyServer(function(input, output, session) {...} # added session
2) Set choices of the widget in UI.R to ""
selectInput("Country", "Country:", choices = "")
3) Update the choices on the server side with:
observe({
req(draw()) # require that draw is available
updateSelectInput(session, "Country", "Country:",
c("All", unique(as.character(draw()$Country)))) # added ()
})
Related
I am trying to access the data frame created in one render function into another render function.
There are two server outputs, lvi and Category, in lvi I have created Data1 data frame and Category I have created Data2 dataframe. I want to select Data2 where Data1 ID is matching.
I am following the below steps to achieve my objective but I get error "Object Data1 not found".
My UI is
ui <- fluidPage(
# App title ----
titlePanel("Phase1"),
fluidPage(
column(4,
# Input: Select a file ----
fileInput("file1", "Import file1")
)
),
fluidPage(
column(4,
# Input: Select a file ----
fileInput("file2", "Import File2")
)
),
# Main panel for displaying outputs ----
mainPanel(
# Output: Data file ----
dataTableOutput("lvi"),
dataTableOutput("category")
)
)
My server code is
server <- function(input, output) {
output$lvi <- renderDataTable({
req(input$file1)
Data1 <- as.data.frame(read_excel(input$file1$datapath, sheet = "Sheet1"))
})
output$category <- renderDataTable({
req(input$file2)
Data2 <- as.data.frame(read_excel(input$file2$datapath, sheet = "Sheet1"))
Data2 <- Data2[,c(2,8)]
Data2 <- Data2[Data1$ID == "ID001",]
})
}
shinyApp(ui, server)
Once a reactive block is done executing, all elements within it go away, like a function. The only thing that survives is what is "returned" from that block, which is typically either the last expression in the block (or, when in a real function, something in return(...)). If you think of reactive (and observe) blocks as "functions", you may realize that the only thing that something outside of the function knows of what goes on inside the function is if the function explicitly returns it somehow.
With that in mind, the way you get to a frame inside one render/reactive block is to not calculate it inside that reactive block: instead, create that frame in its own data-reactive block and use it in both the render and the other render.
Try this (untested):
server <- function(input, output) {
Data1_rx <- eventReactive(input$file1, {
req(input$file1, file.exists(input$file1$datapath))
as.dataframe(read_excel(input$file1$datapath, sheet = "Sheet1"))
})
output$lvi <- renderDataTable({ req(Data1_rx()) })
output$category <- renderDataTable({
req(input$file2, file.exists(input$file2$datapath),
Data1_rx(), "ID" %in% names(Data1_rx()))
Data2 <- as.data.frame(read_excel(input$file2$datapath, sheet = "Sheet1"))
Data2 <- Data2[,c(2,8)]
Data2 <- Data2[Data1_rx()$ID == "ID001",]
})
}
shinyApp(ui, server)
But since we're already going down the road of "better design" and "best practices", let's break data2 out and the data2-filtered frame as well ... you may not be using it separately now, but it's often better to separate "loading/generate frames" from "rendering into something beautiful". That way, if you need to know something about the data you loaded, you don't have to (a) reload it elsewhere, inefficient; or (b) try to rip into the internals of the shiny DataTable object and get it manually. (Both are really bad ideas.)
So a slightly better solution might start with:
server <- function(input, output) {
Data1_rx <- eventReactive(input$file1, {
req(input$file1, file.exists(input$file1$datapath))
as.dataframe(read_excel(input$file1$datapath, sheet = "Sheet1"))
})
Data2_rx <- eventReactive(input$file2, {
req(input$file2, file.exists(input$file2$datapath))
dat <- as.dataframe(read_excel(input$file2$datapath, sheet = "Sheet1"))
dat[,c(2,8)]
})
Data12_rx <- reactive({
req(Data1_rx(), Data2_rx())
Data2_rx()[ Data1_rx()$ID == "ID001", ]
})
output$lvi <- renderDataTable({ req(Data1_rx()); })
output$category <- renderDataTable({ req(Data12_rx()); })
}
shinyApp(ui, server)
While this code is a little longer, it also groups "data loading/munging" together, and "render data into something beautiful" together. And if you need to look at early data or filtered data, it's all right there.
(Side note: one performance hit you might see from this is that you now have more copies of data floating around. As long you are not dealing with "large" data, this isn't a huge deal.)
I am having a problem with accessing data in different parts of my server() function. The basic structure is something like this:
server <- shinyServer(function(input, output) {
# get the data from a file obtained from a textInput in the ui
data <- reactive({
req(input$file)
file <- input$file$datapath
# process the file and return a new dataframe
})
output$head <- renderTable({
mydf <- data()
head(mydf)
})
output$tail <- renderTable({
mydf <- data()
tail(mydf)
})
})
I would like to avoid having to call data() twice but I haven't found a way to do that.
Edit following the comment by #KentJohnson
What I am trying to achieve is for the user to select a file to open, using textInput, and after the file is opened, the app should do some processing and populate the two tables in the ui. After this, the user then chooses some other actions which also require the same data.
I wanted to avoid having to call data() twice but I haven't found a way to do that. I was assuming that each call would mean reading from the file each time. The file is very large so that is my motivation.
As #KentJohnson points out, reactive already achieves your goal. The expression that makes up data...
req(input$file)
file <- input$file$datapath
# process the file and return a new dataframe
...only runs when input$file$datapath changes. It does not rerun each time data() is called.
Putting your two tables into an observe environment makes it possible to call data() only twice, but I don't know if it will fit with what you want to do. Notice that here, I didn't put a textInput or things like that because my point was to show the observe environment. I'll let you adapt it to your situation (since you didn't put the ui part in your post):
library(shiny)
ui <- basicPage(
fileInput("file",
"Import a CSV file",
accept = ".csv"),
tableOutput("head"),
tableOutput("tail")
)
server <- shinyServer(function(input, output) {
# get the data from a file obtained from a textInput in the ui
data <- reactive({
req(input$file)
inFile <- input$file
read.csv(inFile$datapath, header = F, sep = ";")
# process the file and return a new dataframe
})
observe({
mydf <- data()
if (is.null(mydf)){
output$head <- renderTable({})
output$tail <- renderTable({})
}
else {
output$head <- renderTable({
head(mydf)
})
output$tail <- renderTable({
tail(mydf)
})
}
})
})
shinyApp(ui, server)
Edit: I misunderstood the OP's question, see #SmokeyShakers' answer for a more appropriate answer.
I am working on a shiny app where users can upload their own data and get some plots and statistics back. However, I also want to include an example dataset that gets used instead if the user presses a specific button. Importantly, the plots should be reactive so that users get updated plots whenever they click on the "use example data instead" button or upload a new file. I tried to recreate my current approach of overwriting the data object as best as I could here, but simply defining the data object twice doesn't overwrite the data in the way I hoped it would. Any suggestions are appreciated.
library(shiny)
# UI
ui <- fluidPage(
# Application title
titlePanel("Reproducible Example"),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
fileInput("Upload", "Upload your own Data"),
actionButton("Example", "Use Example Data instead")
),
# Show a plot of the generated distribution
mainPanel(
plotOutput("hist")
)
)
)
# Server Logic
server <- function(input, output) {
data <- eventReactive(input$Upload,{input$Upload})
data <- eventReactive(input$Example, {faithful$eruptions})
output$hist <- renderPlot({hist(data())})
}
# Run the application
shinyApp(ui = ui, server = server)
You can use a reactiveVal like this:
server <- function(input, output) {
my_data <- reactiveVal()
observeEvent(input$Upload, {
tmp <- read.csv(input$Upload$datapath)
## do whatever is needed to parse the data
my_data(tmp)
})
observeEvent(input$Example, {
my_data(faithful)
})
output$hist <- renderPlot({
dat <- as.data.frame(req(my_data()))
dat <- dat[, sapply(dat, is.numeric), drop = FALSE]
validate(need(NCOL(dat) > 1, "No numeric columns found in provided data"))
hist(dat[,1])
})
}
Depending on upload or button click, you store your data in my_data which is a reactive value. Whenever this value changes, the renderPlot function fires and uses the correct data.
You can use a reactive value to access whether the user has chosen to use an example dataset or use their own dataset. The user can choose to switch between the active dataset using an input from your UI.
Here's the official explanation on reactive values from RStudio: link
This would go in your ui.R:
radioButtons("sample_or_real",
label = h4("User data or sample data?"),
choices = list(
"Sample Data" = "sample",
"Upload from user data" = "user",
),
selected = "user"
)
This would go in your server.R:
data_active <- reactive({
# if user switches to internal data, switch in-app data
observeEvent(input$sample_or_real_button, {
if(input$sample_or_real == "sample"){
data_internal <- sample_data_object
} else {
data_internal <- uploaded_data_object
}
})
Note, that when using a reactive value in your server.R file, it must have parentheses () at the end of the object name. So, you call the data_internal object as data_internal().
I am using the rhandsontable package in a Shiny app which should have the following functionality:
the data used in the calculation can be randomly generated, invoked by an actionButton (and when the app starts)
the data can be manually edited by the user via the handsontable object
after manual editing it should be possible to re-generate random data, invoking a new calculation
The following app does exactly that what I want, but I could not figure it out how to get rid of the global variable did_recalc. It is a minimal example, where the data consists of two numeric values which are summed up.
library(shiny)
library(rhandsontable)
did_recalc <- FALSE
ui <- fluidPage(
rHandsontableOutput('table'),
textOutput('result'),
actionButton("recalc", "generate new random vals and calculate")
)
server <- function(input,output,session)({
dataset_generator <- eventReactive(input$recalc, {
df <- as.data.frame(runif(2))
output$table <- renderRHandsontable({rhandsontable(df)})
did_recalc <<- TRUE
df
}, ignoreNULL = FALSE)
output$result <- renderText({
df <- dataset_generator()
if (!is.null(input$table) && !did_recalc)
df <- hot_to_r(input$table)
did_recalc <<- FALSE
sum(df)
})
})
shinyApp(ui = ui, server = server)
If I remove the !did_recalc condition within output$result <- ... then editing the table still invokes a (correct) calculation. But if "recalc" is pressed (after some manual editing was done), then the "recalc" button just generates new random values, but without recalculating the sum.
It seems to me, that input$table can just be changed by manual edits of the table object and does not care about new values given via renderRHandsontable. Hence I need this hack with the global variable, which allows me to track if the user just re-generated the data (causing that input$table is "outdated")
Has anybody an idea how to get the functionality of this example without the global variable?
You could store the data in a reactiveValues and have two observers updating it; one if the button is clicked, one if the table is edited by hand.
In your output$table and output$result, you then just need to use the data that is in the reactiveValues. Here's an example (same ui.R as you posted):
server <- function(input,output,session)({
values <- reactiveValues(data=as.data.frame(runif(2)))
observe({
input$recalc
values$data <- as.data.frame(runif(2))
})
observe({
if(!is.null(input$table))
values$data <- hot_to_r(input$table)
})
output$table <- renderRHandsontable({
rhandsontable(values$data)
})
output$result <- renderText({
sum(values$data)
})
})
I am currently writing a shiny app which imports a dataset and displays a manipulated version. To work on the shiny methods I am currently working on a simplified version which displays the imported dataset. I currently assign the imported dataset to a reactive value, and then use the render table as follows:-
shinyServer(function(input, output) {
DATA<-reactive({
input$filein
})
output$Dataset <- renderTable({
DATA()
})
})
The interface then produces a table with the following columns:-
name, size, type, datapath.
What I had in mind was to call the datapath variable, and use read.csv to call it within the renderTable function. I tried using:-
DATA()$datapath
However that doesn't seem to produce any result. Are there any other ways to extract this data within Shiny? I contemplated using vector indices as you would using regular R code however I am unsure as to whether or not that'll work within Shiny.
Here is an example for files in the current working directory. The example file I used was a minimal csv file (see bottom). Please note however that this is indeed limited to files in your working directory. If you want other files to be loaded you will need to have a further component to specify the path (possibly in the selectInput).
library(shiny)
library(tools)
runApp(
list(
ui = pageWithSidebar(
headerPanel("File Info Test"),
sidebarPanel(
p("Demo Page."),
selectInput("filein", "Choose File", choices=c("test.csv"))
),
mainPanel(
tableOutput("myTableInfo"),
tableOutput("myTable")
)
),
server = function(input, output){
mydata <- reactive({
read.csv(input$filein)
})
file_info <- reactive({
validate(
need(!is.null(input$filein), "please select file"
)
)
name <- input$filein
size <- file.info(input$filein)[['size']]
type <- file_ext(input$filein)
datapath <- file_path_as_absolute(input$filein)
cbind(name, size, type, datapath)
})
output$myTableInfo <- renderTable({
file_info()
})
output$myTable <- renderTable({
mydata()
})
}
)
)
test.csv
X1,X2,X3
1,2,3
4,5,6