I'm working on an app which takes up a CSV via reactiveFileReader and applies some functions. I would like to modify the contents of the data before applying these functions.
I understand that reactive objects cannot be modified directly, but I can't even seem to be able to make a new object with the desired modifications (in this case, new column names in the dataframe).
This is where I am at in the server code:
data <- reactiveFileReader(1000, session, "path", read.csv)
data_new <- reactive({ colnames(data) <- c("Col 1"," Col 2","Col 3") })
output$data <- renderDataTable(data_new())
Unfortunately this yields the error "Error: attempt to set 'colnames' on an object with less than two dimensions".
Any suggestions on how to properly modify and store the data?
Many thanks!
Try this
ui <- fluidPage(
uiOutput("data1"),
uiOutput("data")
)
server <- function(input, output, session) {
data <- reactiveFileReader(1000, session, "file2.csv", read.csv)
data_new <- reactive({
df <- data()
colnames(df) <- c("Col 1"," Col 2","Col 3")
df
})
output$data <- renderTable(data_new())
output$data1 <- renderTable(head(data()))
}
shinyApp(ui, server)
Related
I am making a Shiny App and I would like to rename the first variable from dataframe, to make after a corrplot.
In normal R the code is:
library(lares)
names(Dataset)[1] <- "DR"
corr_var(Dataset, DR, top=20)
And in Shiny I have something:
dataReg2 = reactive({
inFile <- input$fileReg
if (is.null(inFile))
return(NULL)
else
data1 = read_excel(inFile$datapath)
return(data1)
})
plot=reactive({
names(dataReg2())[[1]]='DR'
corr_var(dataReg2(), DR , top = 20 )
})
But it doesn't work, the error is invalid (NULL) left side of assignment...
Thank you in advance.
You cannot change the column names of reactive object. Copy the data in another variable and you can change the column name of that variable. See this simple example using mtcars.
library(shiny)
ui <- fluidPage(
tableOutput('tab')
)
server <- function(input, output) {
data <- reactive(mtcars)
output$tab <- renderTable({
new_table <- data()
names(new_table)[1] <- 'new'
head(new_table)
})
}
shinyApp(ui, server)
I'm trying to merge two uploaded data frames, output it as a table, then being able to download it and reset the inputs, but only get the error: "Error 'by' must match numbers of columns".
I have trouble understanding reactiveValues I guess, since I can't simply call them as data frames in the app...
library(shiny)
library(shinyjs)
library(readxl)
library(DT)
ui <- fluidPage(
useShinyjs(),
fileInput('inFile1', 'Choose file'),
fileInput('inFile2', 'Choose file'),
actionButton('reset', 'Reset'),
tableOutput('overlap')
)
server <- function(input, output, session) {
rv <- reactiveValues()
observe({
req(input$inFile1)
rv$data1 <- readxl::read_xls(input$inFile1$datapath)
})
observe({
req(input$inFile2)
rv$data2 <- readxl::read_xls(input$inFile2$datapath)
})
observeEvent(input$reset, {
rv$data1 <- NULL
rv$data2 <- NULL
reset('inFile1')
reset('inFile2')
})
dataframe<-reactive({
if (!is.null(rv$data1) | !is.null(rv$data2))
return(NULL)
df <- merge(as.data.frame(rv$data1),as.data.frame(rv$data2),by.x = 1,by.y = 1)
colnames(df) <- c("GeneID",paste0(colnames(rv$data1)[2:ncol(rv$data1)],"_file_1"),
paste0(colnames(rv$data2)[2:ncol(rv$data2)],"_file_2"))
df
})
overlap1 <- reactive({
if(!is.null(dataframe()))
dataframe()
})
output$overlap <- renderDataTable({
datatable(overlap1())
})
}
shinyApp(ui, server)
At a first glance your reactive expressions look fine to me. And given that error message the error is caused by merge(). Taking a closer look there, what strikes me are those is.null checks at the top of the dataframe<-reactive(. The condition (!is.null(rv$data1) | !is.null(rv$data2)) means that you are trying to merge two objects that are NULL because only then the code wont't stop with return(NULL). If one or both rv-values are "Truthy" the code won't run and all the reactive is going to return is NULL.
I used isTruthy() below. I think it helps in two ways:
isTruthy() checks if the values contain anything "usable". That way, you do not have to care about how rv is initialised. It could be NA or integer(0) or anything else that is meaningless. isTruthy handles all these cases. Merging now only takes place when there are two values with "meaningful" data (note that this does not necessarily mean that the data can be coerced to data.frame).
It avoids a complicated double negative in the if-statement.
dataframe <- reactive({
if (isTruthy(rv$data1) && isTruthy(rv$data2)) {
df <- merge(rv$data1, rv$data2, by.x = 1,by.y = 1)
colnames(df) <- c("GeneID", paste0(colnames(rv$data1)[2:ncol(rv$data1)], "_file_1"),
paste0(colnames(rv$data2)[2:ncol(rv$data2)], "_file_2"))
} else df <- NULL
df
})
Final tweak: I removed as.data.frame in the merge statement because the first thing merge is trying to do is coerce the arguments to a data frame.
I want to save user'S data in the db.
Every user's data should be submitted per row without any error. The data is in a function with if else condition. Every if else's output is to be saved against it's user. How can I do it?
I tried creating a dataframe for it but still the data wasn't saved in it.
Here is reprex of my code.
library(shiny)
library(tidyverse)
ui <- fluidPage(
textInput("my_in","type a value for an entry"),
actionButton("newline_but","press for a new entry"),
tableOutput("showmytable")
)
server <- function(input, output, session) {
mydf <- reactiveVal(tibble(msg=NA_character_))
output$showmytable <- renderTable({
mydf()
})
observeEvent(input$my_in,{
local_df <- req(mydf())
curr_row <- nrow(local_df)
local_df[curr_row,1] <- input$my_in
mydf(local_df)
})
observeEvent(input$newline_but,{
local_df <- req(mydf())
mydf(add_row(local_df))
})
observeEvent(mydf(),
{
#export to a global but would be better to maybe write to a database
assign(x="exported_df",
value=mydf(),
envir = .GlobalEnv)
})
}
shinyApp(ui,server)```
I have been going through most of the Q&As related to dataframe manipulation within Shiny and I still don't understand how to do something which, in my mind, should be very simple. I don't have experience writing Shiny apps and I'm still struggling with concepts like reactive events.
I have a dataframe A, loaded into R. I want to be able to see a specific value in a specific column in the dataframe in the UI and then edit it. After I edit the dataframe, I want to close the Shiny app and then see the edited dataframe in the Environment tab of RStudio. How do I go about doing this?
I think this might be a workable example.
Assume df is your data frame (I used iris to test, commented out below). Create a reactiveVal to hold your data, and use for editing with datatable. After editing, you can store the data back into your global environment dataframe df with <<-. An alternative is to do this when exiting the shiny app (such as through the onStop or session$onSessionEnded method).
library(shiny)
library(DT)
#df <- iris
ui <- fluidPage(
DT::dataTableOutput('data'),
)
server <- function(input, output) {
rv <- reactiveVal(df)
output$data <- DT::renderDataTable ({
DT::datatable(rv(), editable = TRUE)
})
observeEvent(input$data_cell_edit, {
info <- input$data_cell_edit
newdf <- rv()
newdf[info$row, info$col] <- info$value
rv(newdf)
df <<- rv()
})
}
shinyApp(ui = ui, server = server)
Alternative with replacing global df on exiting (requires session):
server <- function(input, output, session) {
rv <- reactiveVal(df)
output$data <- DT::renderDataTable ({
DT::datatable(rv(), editable = TRUE)
})
observeEvent(input$data_cell_edit, {
info <- input$data_cell_edit
newdf <- rv()
newdf[info$row, info$col] <- info$value
rv(newdf)
})
session$onSessionEnded(function() {
df <<- isolate(rv())
})
}
If you don't want to use reactive values, I suppose you could try the following. This can update your data.frame in the global environment as edits are made. Note that server = FALSE is added to handle changes in pages:
server <- function(input, output) {
output$data <- DT::renderDT (df, editable = TRUE, server = FALSE)
observeEvent(input$data_cell_edit, {
info <- input$data_cell_edit
df[info$row, info$col] <<- info$value
})
}
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.)