I am creating a Shiny app and I have started using the Waiter package.
When I load the app, before doing anything, we cannot see anything (at it is expected). When I generate the plot, the loading bar appears but when it finishes, it doesn't disappear. It stays a white box that it still can be seen.
Loading....
It has finished.
Does anyone know how to remove it?
Thanks in advance!
Code:
library(shiny)
library(magrittr)
library(DT)
library(ggplot2)
library(waiter)
new_choices <- setNames(names(mtcars), names(mtcars))
ui <- fluidPage(
# Application title
titlePanel("My shiny app"),
sidebarLayout(
sidebarPanel(
tabsetPanel(
tabPanel("Selection",
selectInput("x_axis", "Choose x axis",
choices = new_choices),
selectInput("y_axis", "Choose y axis",
choices = new_choices),
hr(),
),
tabPanel("Titles",
hr(),
textInput(inputId = "title", "You can write the title:", value = "This is the title"),
textInput(inputId = "xlab", "You can re-name the x-axis:", value = "x-axis...."),
textInput(inputId = "ylab", "You can re-name the y-axis:", value = "y-axis ...."),
),
tabPanel("Calculations",
hr(),
checkboxInput("log2", "Do the log2 transformation", value = F),
checkboxInput("sqrt", "Calculate the square root", value = F),
)
),
useWaitress(),
actionButton(inputId = "drawplot", label = "Show the plot")
),
# Show a plot of the generated distribution
mainPanel(
plotOutput("plot"),
)
)
)
server <- function(input, output, session) {
waitress <- Waitress$new(theme = "overlay-percent", min = 0, max = 10)
data <- reactive({
mtcars
})
filtered_data <- reactive({
data <- data()
if(input$log2 == TRUE){
data <- log2(data+1)
}
if(input$sqrt == TRUE){
data <- sqrt(data)
}
return(data)
})
v <- reactiveValues()
observeEvent(input$drawplot, {
# use notification
waitress$notify()
for(i in 1:10){
waitress$inc(1) # increase by 10%
Sys.sleep(.3)
}
v$plot <- ggplot() +
geom_point(data = filtered_data(),
aes_string(x = input$x_axis, y = input$y_axis)) +
xlab(input$xlab) +
ylab(input$ylab) +
ggtitle(input$title)
waitress$close() # hide when done
})
output$plot <- renderPlot({
if (is.null(v$plot)) return()
v$plot
})
}
shinyApp(ui, server)
Feels like a bug to me. You may file an issue to the waiter github repository and ask them to fix it. Meanwhile, a workaround we can do is to manually show and hide the bar by ourselves.
library(shiny)
library(magrittr)
library(DT)
library(ggplot2)
library(waiter)
library(shinyjs)
new_choices <- setNames(names(mtcars), names(mtcars))
ui <- fluidPage(
# Application title
titlePanel("My shiny app"),
sidebarLayout(
sidebarPanel(
tabsetPanel(
tabPanel("Selection",
selectInput("x_axis", "Choose x axis",
choices = new_choices),
selectInput("y_axis", "Choose y axis",
choices = new_choices),
hr(),
),
tabPanel("Titles",
hr(),
textInput(inputId = "title", "You can write the title:", value = "This is the title"),
textInput(inputId = "xlab", "You can re-name the x-axis:", value = "x-axis...."),
textInput(inputId = "ylab", "You can re-name the y-axis:", value = "y-axis ...."),
),
tabPanel("Calculations",
hr(),
checkboxInput("log2", "Do the log2 transformation", value = F),
checkboxInput("sqrt", "Calculate the square root", value = F),
)
),
useWaitress(),
useShinyjs(),
actionButton(inputId = "drawplot", label = "Show the plot")
),
# Show a plot of the generated distribution
mainPanel(
plotOutput("plot")
)
)
)
server <- function(input, output, session) {
waitress <- Waitress$new(theme = "overlay-percent", min = 0, max = 10)
data <- reactive({
mtcars
})
filtered_data <- reactive({
data <- data()
if(input$log2 == TRUE){
data <- log2(data+1)
}
if(input$sqrt == TRUE){
data <- sqrt(data)
}
return(data)
})
v <- reactiveValues()
observeEvent(input$drawplot, {
# use notification
show(selector = '.waitress-notification.notifications')
waitress$notify()
for(i in 1:10){
waitress$inc(1) # increase by 10%
Sys.sleep(.3)
}
v$plot <- ggplot() +
geom_point(data = filtered_data(),
aes_string(x = input$x_axis, y = input$y_axis)) +
xlab(input$xlab) +
ylab(input$ylab) +
ggtitle(input$title)
waitress$close()
hide(selector = '.waitress-notification.notifications')
})
output$plot <- renderPlot({
if (is.null(v$plot)) return()
v$plot
})
}
shinyApp(ui, server)
Related
I have plotted scatterplot for each country, and I am trying to add a correlation coefficient under the scatterplot, but I keep getting errors saying "Selections can't have missing values." even after using na.rm
Can someone help me with this??
I appreciate any help you can provide.
data link EuropeIndia
#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(plotly)
library(DT)
library(tidyverse)
library(car)
library(ggpubr)
covid <- read.csv("EuropeIndia.csv")
title <- tags$a(href='https://ourworldindata.org/covid-vaccinations?country=OWID_WRL',
'COVID 19 Vaccinations')
# Define UI for application
ui <- fluidPage(
headerPanel(title = title),
# Application title
titlePanel("COVID vaccinations: Deaths Vs All variables"),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
selectInput("location", "1. Select a country",
choices = covid$location, selectize = TRUE, multiple = FALSE),
br(),
helpText("2. Select variables for scatterplot"),
selectInput(inputId = "y", label = "Y-axis:",
choices = c("total_deaths", "new_deaths"),
selected = "Deaths",),
br(),
selectInput(inputId = "x", label = "X-axis:",
choices = names(subset(covid,select = -c(total_deaths,new_deaths,
iso_code, continent,date,location), na.rm =TRUE)),
selectize = TRUE,
selected = "Comparator variables")
),
mainPanel(
textOutput("location"),
#plotOutput("Scatterplot"),
tabsetPanel(
type = "tabs",
tabPanel("Scatterplot", plotlyOutput("scatterplot"),
verbatimTextOutput("correlation"),
verbatimTextOutput("interpretation")),
tabPanel("Summary of COVID data", verbatimTextOutput("summary")),
tabPanel("Dataset", DTOutput("dataset")))
)
)
)
# Define server logic
server <- function(input, output) {
output$location <- renderPrint({locationfilter <- subset(covid, covid$location == input$location)})
output$summary <- renderPrint({summary(covid)})
output$dataset <- renderDT(
covid, options = list(
pageLength = 50,
initComplete = JS('function(setting, json) { alert("done"); }')
)
)
output$scatterplot <- renderPlotly({
ggplotly(
ggplot(subset(covid, covid$location == input$location),
aes(y = .data[[input$y]], x = .data[[input$x]],col = factor(stringency_index)))+
geom_smooth()+geom_point()+labs(col ="Stringency Index")
)
})
output$correlation <- renderText({
x= subset(covid, covid$location == input$location) %>% dplyr::select(as.numeric(!!!input$x, na.rm =TRUE))
y= subset(covid, covid$location == input$location) %>% dplyr::select(as.numeric(!!!input$y, na.rm = TRUE))
var(x,y, na.rm = T, use)
cor(x,y, method = 'pearson', na.rm =T)
})
}
# Run the application
shinyApp(ui = ui, server = server)
First of all you should select just one Country from the selection list.
For error checking I propose you the next code.
library(shiny)
library(plotly)
library(DT)
library(tidyverse)
library(car)
library(ggpubr)
covid <- read.csv("EuropeIndia.csv")
title <- tags$a(href='https://ourworldindata.org/covid-vaccinations?country=OWID_WRL',
'COVID 19 Vaccinations')
# Define UI for application
ui <- fluidPage(
headerPanel(title = title),
# Application title
titlePanel("COVID vaccinations: Deaths Vs All variables"),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
selectInput("location", "1. Select a country",
choices = covid$location[1], selectize = TRUE, multiple = FALSE),
br(),
helpText("2. Select variables for scatterplot"),
selectInput(inputId = "y", label = "Y-axis:",
choices = c("total_deaths", "new_deaths"),
selected = "Deaths",),
br(),
selectInput(inputId = "x", label = "X-axis:",
choices = names(subset(covid,select = -c(total_deaths,new_deaths,
iso_code, continent,date,location), na.rm =TRUE)),
selectize = TRUE,
selected = "Comparator variables")
),
mainPanel(
textOutput("location"),
#plotOutput("Scatterplot"),
tabsetPanel(
type = "tabs",
tabPanel("Scatterplot", plotlyOutput("scatterplot"),
verbatimTextOutput("correlation"),
verbatimTextOutput("interpretation")),
tabPanel("Summary of COVID data", verbatimTextOutput("summary")),
tabPanel("Dataset", DTOutput("dataset")))
)
)
)
# Define server logic
server <- function(input, output) {
output$location <- renderPrint({locationfilter <- subset(covid, covid$location == input$location)})
output$summary <- renderPrint({summary(covid)})
output$dataset <- renderDT(
covid, options = list(
pageLength = 50,
initComplete = JS('function(setting, json) { alert("done"); }')
)
)
output$scatterplot <- renderPlotly({
ggplotly(
ggplot(subset(covid, covid$location == input$location),
aes(y = .data[[input$y]], x = .data[[input$x]],col = factor(stringency_index)))+
geom_smooth()+geom_point()+labs(col ="Stringency Index")
)
})
output$correlation <- renderText({
x <- covid[covid$location == input$location, input$x]
y <- covid[covid$location == input$location, input$y]
xy = data.frame(x,y)
xy = xy[complete.cases(xy),]
var(xy)
cor(xy,method = 'pearson')
})
}
# Run the application
shinyApp(ui = ui, server = server)
I am trying to plot using ggplot in R shiny. I want to upload data and any variable can be used for plotting. I am trying to keep aes() dynamically. I tried a few examples example 1, but dint work for me. Here is my code:
library(shiny)
library(shinydashboard)
library(readxl)
library(DT)
library(dplyr)
library(ggplot2)
# Define UI for application that draws a histogram
ui <- fluidPage(
titlePanel("Uploading Files"),
sidebarLayout(
sidebarPanel(
fileInput('file1', 'Upload data File',
accept=c('text/csv','.xlsx',
'text/comma-separated-values,text/plain',
'.csv'))),
mainPanel(
DT::dataTableOutput('contents')
)
),
tabPanel("First Type",
pageWithSidebar(
headerPanel('Visualization of Dengue Cases'),
sidebarPanel(
selectInput('xcol', 'X Variable', ""),
selectInput('ycol', 'Y Variable', "", selected = "")
),
mainPanel(
plotOutput('MyPlot')
)
)
)
)
# Define server logic required to draw a histogram
server <- function(input, output,session) {
data <- reactive({
req(input$file1)
inFile <- input$file1
df <- read_excel(paste(inFile$datapath, sep=""), 1)
updateSelectInput(session, inputId = 'xcol', label = 'X Variable',
choices = names(df), selected = names(df))
updateSelectInput(session, inputId = 'ycol', label = 'Y Variable',
choices = names(df), selected = names(df)[2])
return(df)
})
output$contents <- DT::renderDataTable({
data()
},options = list(pageLength = 10, width="100%", scrollX = TRUE))
output$MyPlot <- renderPlot({
select_quo <- quo(input$MyPlot_select)
data %>%
mutate(user_input = !!select_quo) %>%
ggplot(aes(fill=user_input, y=user_input, x= user_input)) +
geom_bar( stat="identity")
})
}
# Run the application
shinyApp(ui = ui, server = server)
Can use any data set, such as Diamond dataset.
Also kindly help in allowing all types of formats (.csv, .txt,.xls) of data. As of now, only .xls is acceptable.
There are several issues with your code.
You use data instead of data() in the renderPlot
There is no input input$MyPlot_select.
Using quo and !! will not give the desired result. Instead you could simply use the .data pronoun if your column names are strings.
Add req at the beginning of renderPlot.
This said your renderPlot should look like so:
output$MyPlot <- renderPlot({
req(input$xcol, input$ycol)
x <- input$xcol
y <- input$ycol
fill <- input$xcol
ggplot(data(), aes(x = .data[[x]], y = .data[[y]], fill=.data[[fill]])) +
geom_col()
})
For the second part of your question. To make your app work for different types of input files you could get the file extension using e.g. tools::file_ext and use the result in switch statement.
Full reproducible code:
library(shiny)
library(shinydashboard)
library(readxl)
library(DT)
library(dplyr)
library(ggplot2)
ui <- fluidPage(
titlePanel("Uploading Files"),
sidebarLayout(
sidebarPanel(
fileInput("file1", "Upload data File",
accept = c(
"text/csv", ".xlsx",
"text/comma-separated-values,text/plain",
".csv"
)
)
),
mainPanel(
DT::dataTableOutput("contents")
)
),
tabPanel(
"First Type",
pageWithSidebar(
headerPanel("Visualization of Dengue Cases"),
sidebarPanel(
selectInput("xcol", "X Variable", ""),
selectInput("ycol", "Y Variable", "", selected = "")
),
mainPanel(
plotOutput("MyPlot")
)
)
)
)
# Define server logic required to draw a histogram
server <- function(input, output, session) {
data <- reactive({
req(input$file1)
inFile <- input$file1
type <- tools::file_ext(inFile$name)
filename <- inFile$datapath
df <- switch(type,
"xlsx" = read_excel(filename),
"csv" = read_csv(filename),
"tsv" = read_tsv(filename))
updateSelectInput(session,
inputId = "xcol", label = "X Variable",
choices = names(df), selected = names(df)
)
updateSelectInput(session,
inputId = "ycol", label = "Y Variable",
choices = names(df), selected = names(df)[2]
)
return(df)
})
output$contents <- DT::renderDataTable({
data()
}, options = list(pageLength = 10, width = "100%", scrollX = TRUE))
output$MyPlot <- renderPlot({
req(input$xcol, input$ycol)
x <- input$xcol
y <- input$ycol
fill <- input$xcol
ggplot(data(), aes(x = .data[[x]], y = .data[[y]], fill=.data[[fill]])) +
geom_col()
})
}
# Run the application
shinyApp(ui = ui, server = server)
I am creating a shiny app with some tabs and I am using the shinycssloaders package in order to show a spinner AFTER pressing the actionButton. I saw this post because I was having the same problem... I followed the solution that it was given to the post, but as I my app is different (it has tabPanels, it doesn't work properly, the spinner still apears).
For example, if you click on "Show the plot" in the first tab (selection) and then you want to want to do the log2 transformation o calculate the square root (3rd tab, calculations), before clicking the actionButton the spinner appears and the plot updates. It happens the same when you want to change the titles (2nd tab).
Does anyone know how to fix it?
Thanks very much in advance
The code:
library(shiny)
library(magrittr)
library(DT)
library(ggplot2)
library(shinycssloaders)
new_choices <- setNames(names(mtcars), names(mtcars))
ui <- fluidPage(
# Application title
titlePanel("My shiny app"),
sidebarLayout(
sidebarPanel(
tabsetPanel(
tabPanel("Selection",
selectInput("x_axis", "Choose x axis",
choices = new_choices),
selectInput("y_axis", "Choose y axis",
choices = new_choices),
hr(),
),
tabPanel("Titles",
hr(),
textInput(inputId = "title", "You can write the title:", value = "This is the title"),
textInput(inputId = "xlab", "You can re-name the x-axis:", value = "x-axis...."),
textInput(inputId = "ylab", "You can re-name the y-axis:", value = "y-axis ...."),
),
tabPanel("Calculations",
hr(),
checkboxInput("log2", "Do the log2 transformation", value = F),
checkboxInput("sqrt", "Calculate the square root", value = F),
)
),
actionButton(inputId = "drawplot", label = "Show the plot")
),
# Show a plot of the generated distribution
mainPanel(
# plotOutput("plot")
uiOutput("spinner"),
)
)
)
server <- function(input, output, session) {
data <- reactive({
mtcars
})
filtered_data <- reactive({
data <- data()
if(input$log2 == TRUE){
data <- log2(data+1)
}
if(input$sqrt == TRUE){
data <- sqrt(data)
}
return(data)
})
observeEvent(input$drawplot, {
output$spinner <- renderUI({
withSpinner(plotOutput("plot"), color="black")
})
output$plot <- renderPlot({
Sys.sleep(3)
ggplot() +
geom_point(data = filtered_data(),
aes_string(x = input$x_axis, y = input$y_axis)) +
xlab(input$xlab) +
ylab(input$ylab) +
ggtitle(input$title)
})
})
}
shinyApp(ui, server)
Is it OK like this? I'm not sure to understand all your requirements. To avoid the spinner at the start-up, I use a conditionalPanel. In the server code, I did some changes. It is not recommended to define some output inside an observer.
library(shiny)
library(magrittr)
library(ggplot2)
library(shinycssloaders)
new_choices <- setNames(names(mtcars), names(mtcars))
ui <- fluidPage(
# Application title
titlePanel("My shiny app"),
sidebarLayout(
sidebarPanel(
tabsetPanel(
tabPanel(
"Selection",
selectInput("x_axis", "Choose x axis",
choices = new_choices),
selectInput("y_axis", "Choose y axis",
choices = new_choices),
hr(),
),
tabPanel(
"Titles",
hr(),
textInput(inputId = "title", "You can write the title:", value = "This is the title"),
textInput(inputId = "xlab", "You can re-name the x-axis:", value = "x-axis...."),
textInput(inputId = "ylab", "You can re-name the y-axis:", value = "y-axis ...."),
),
tabPanel(
"Calculations",
hr(),
checkboxInput("log2", "Do the log2 transformation", value = F),
checkboxInput("sqrt", "Calculate the square root", value = F),
)
),
actionButton(inputId = "drawplot", label = "Show the plot")
),
# Show a plot of the generated distribution
mainPanel(
conditionalPanel(
condition = "input.drawplot > 0",
style = "display: none;",
withSpinner(plotOutput("plot"))
)
)
)
)
server <- function(input, output, session) {
data <- reactive({
mtcars
})
filtered_data <- reactive({
data <- data()
if(input$log2 == TRUE){
data <- log2(data+1)
}
if(input$sqrt == TRUE){
data <- sqrt(data)
}
return(data)
})
gg <- reactive({
ggplot() +
geom_point(data = filtered_data(),
aes_string(x = input$x_axis, y = input$y_axis)) +
xlab(input$xlab) +
ylab(input$ylab) +
ggtitle(input$title)
}) %>%
bindEvent(input$drawplot)
output$plot <- renderPlot({
Sys.sleep(3)
gg()
})
}
shinyApp(ui, server)
You need to isolate the expressions that you don't want to trigger the rendering event inside renderPlot
library(shiny)
library(magrittr)
library(DT)
library(ggplot2)
library(shinycssloaders)
new_choices <- setNames(names(mtcars), names(mtcars))
ui <- fluidPage(
# Application title
titlePanel("My shiny app"),
sidebarLayout(
sidebarPanel(
tabsetPanel(
tabPanel("Selection",
selectInput("x_axis", "Choose x axis",
choices = new_choices),
selectInput("y_axis", "Choose y axis",
choices = new_choices),
hr(),
),
tabPanel("Titles",
hr(),
textInput(inputId = "title", "You can write the title:", value = "This is the title"),
textInput(inputId = "xlab", "You can re-name the x-axis:", value = "x-axis...."),
textInput(inputId = "ylab", "You can re-name the y-axis:", value = "y-axis ...."),
),
tabPanel("Calculations",
hr(),
checkboxInput("log2", "Do the log2 transformation", value = F),
checkboxInput("sqrt", "Calculate the square root", value = F),
)
),
actionButton(inputId = "drawplot", label = "Show the plot")
),
# Show a plot of the generated distribution
mainPanel(
# plotOutput("plot")
uiOutput("spinner"),
)
)
)
server <- function(input, output, session) {
data <- reactive({
mtcars
})
filtered_data <- reactive({
data <- data()
if(input$log2 == TRUE){
data <- log2(data+1)
}
if(input$sqrt == TRUE){
data <- sqrt(data)
}
return(data)
})
observeEvent(input$drawplot, {
output$spinner <- renderUI({
withSpinner(plotOutput("plot"), color="black")
})
output$plot <- renderPlot({
Sys.sleep(3)
ggplot() +
geom_point(data = isolate(filtered_data()),
aes_string(x = isolate(input$x_axis), y = isolate(input$y_axis))) +
xlab(isolate(input$xlab)) +
ylab(isolate(input$ylab)) +
ggtitle(isolate(input$title))
})
})
}
shinyApp(ui, server)
Read more about shiny reactivity and isolation: https://shiny.rstudio.com/articles/isolation.html
I am having trouble with some code that I've written.
Here is a sample of the dataset: https://docs.google.com/spreadsheets/d/1C_P5xxzYr7HOkaZFfFiDhanqDSuSIrd2UkiC-6_G2q0/edit?usp=sharing
Objective:
I have a dataset that contains a column of Purchase_Month, candy and freq of the number of times that type of candy was purchased in that given month.
I have an rPlot which I was to change based on the chosen Candy bar in the SelectInput. And output a line chart based on the number of times that candy was purchased that month.
I have my current code below, but it tells me that candyCount is not found.
## ui.R ##
library(shinydashboard)
library(rCharts)
dashboardPage(
dashboardHeader(title = "Dashboard"),
dashboardSidebar(
width = 150,
sidebarMenu(
menuItem("Dashboard", tabName = "dashboard", icon = icon("bar-chart"))
)
),
dashboardBody(
sidebarPanel(
htmlOutput("candy")
),
mainPanel(
showOutput("plot2", "polycharts")
))
)
##server.R##
library(rCharts)
library(ggplot2)
library(ggvis)
server <- function(input, output, session) {
output$candy <- renderUI({
available2 <- dataset[(dataset$candy == input$candy), "candy"]
selectInput(
inputId = "candy",
label = "Choose a candy: ",
choices = sort(as.character(unique(available2))),
selected = unique(available2[1])
)
})
observeEvent(input$candy, {
candyChoice<- toString(input$customer_issue)
print(candyChoice)
candyCount<- dataset[dataset$candy == candyChoice, ]
})
})
output$plot2 <- renderChart2({
p2 <- rPlot(freq~purchase_month, data = candyCount, type = 'line')
p2$guides(y = list(min = 0, title = ""))
p2$guides(y = list(title = sprintf("%s Claims",input$candy)))
p2$addParams(height = 300, dom = 'chart2')
return(p2)
})
}
Updated Data: Why wouldn't this work?
candyCount<- reactive({
dataset[dataset$candy == input$candy, ]
})
output$plot2 <- renderChart2({
p2 <- rPlot(freq~purchase, data = candyCount(), type = 'line')
p2$guides(y = list(min = 0, title = ""))
p2$guides(y = list(title = ""))
p2$addParams(height = 300, dom = 'chart2')
return(p2)
})
output$candy <- renderUI({
available2 <- dataset[(dataset$candy == input$candy), "candy"]
selectInput(
inputId = "candy",
label = "Choose a candy: ",
choices = sort(as.character(unique(available2))),
selected = unique(available2[1])
)
})
In the above you are trying to subset by an input, which is inside your output. The selectInput needs to be inside UI.R.
A working basic example you may find useful.
library(shiny)
df <- read.csv("/path/to/my.csv")
ui <- shinyUI(pageWithSidebar(
headerPanel('Candy Data'),
sidebarPanel(
selectInput('candy', 'Candy', unique(as.character(df[,2])), selected = "Twix")
),
mainPanel(
plotOutput('plot1')
)
))
server <- shinyServer(function(input, output, session) {
selectedData <- reactive({
df[which(df[,2] == input$candy),3]
})
output$plot1 <- renderPlot({
barplot(selectedData())
})
})
shinyApp(ui, server)
In the above example the ui renders a selectInput which has the ID candy. The value, i.e the candy selected is now assigned to input$candy scope. In server we have a reactive function watching for any input change. When the user selects a new candy this function, df[which(df[,2] == input$candy),3] is saying "subset my data frame, df, by the new input$candy". This is now assigned to the selectedData(). Finally we render then boxplot.
EDIT
server.R
require(rCharts)
options(RCHART_WIDTH = 500)
df <- read.csv("path/to/my.csv")
shinyServer(function(input, output, session) {
selectedData <- reactive({
df[which(df[,2] == input$candy),]
})
output$plot1 <- renderChart({
p <- rPlot(freq~purchase_month, data = selectedData(), type = "line")
p$addParams(dom = 'plot1')
return(p)
})
})
ui.R
require(rCharts)
options(RCHART_LIB = 'polycharts')
shinyUI(pageWithSidebar(
headerPanel('Candy Data'),
sidebarPanel(
selectInput('candy', 'Candy', unique(as.character(df[,2])), selected = "Twix")
),
mainPanel(
showOutput('plot1', 'polycharts')
)
))
save files in directory and then runApp.
At available2 you're filtering the data about a selected candy with dataset$candy == input$candy. But you use the same available2 to determine which are the choices at selectInput. I'm guessing you wanted: available2 <- dataset[, "candy"].
I have been working with the Shiny package, there is one function, which the user is able to select from a list of choices, based on the choice, the plot will update. however, right now the app does not update when the selection changes.
server.R
----------
library(shiny)
library(quantmod)
library(TTR)
shinyServer(function(input, output, session) {
selectedsymbol <- reactive({
symbol <- input$selectstock
})
output$stockplotoverview <- renderPlot({
symbolinput <- selectedsymbol()
getSymbols(symbolinput)
chartSeries(get(symbolinput))
addMACD()
addBBands()
})
output$candlechart <- renderPlot({
symbolinput <- input$selectstock
getSymbols(symbolinput)
candleChart(get(symbolinput),multi.col=TRUE,theme="white")
})
output$barchart <- renderPlot({
symbolinput <- input$selectstock
getSymbols(symbolinput)
barChart(get(symbolinput))
})
})
ui.R
library(shiny)
shinyUI(fluidPage(
# Application title
titlePanel("Hello Shiny!"),
# Sidebar component
sidebarLayout(
sidebarPanel(
selectInput("selectstockset", label = h3("Select the stock set"), choices = list("My Stock set" = 1,
"Good Stock Set" = 2,
"Customize" = 3), selected = 1),
selectInput("selectalgo", label = h3("Select the algorithm"), choices = list("Worst Increment" = 1,
"PAMR" = 2,
"SMA" = 3), selected = 1),
dateRangeInput("daterange", label = h3("Date Range")),
submitButton("Simulate")
),
# Show a plot of the generated distribution
mainPanel(
tabsetPanel(
tabPanel("Stock Set",
helpText("Select a stock to examine.
Information will be collected from yahoo finance."),
textInput("stocksetname", label = h4("Stock Set Name"),
value = "Enter text...") ,
# uiOutput("selectstock"),
selectInput("selectstock", label = h4("Select the stock"), choices = list("AAPL" = "AAPL",
"SBUX" = "SBUX",
"GS" = "GS")),
tabsetPanel(
tabPanel("Overview",
plotOutput("stockplotoverview")
),
tabPanel("Candle Chart",
plotOutput("candlechart")
),
tabPanel("Bar Chart",
plotOutput("barchart"))
),
hr(),
fluidRow(
column(3,
actionButton("addtostockset","Add to stock set"),
tags$style(type='text/css', "#addtostockset { align: right;}")
),
column(3,
actionButton("confirm","Confirm stock set"),
tags$style(type='text/css', "#confirm { align: right; }")
)
)),
tabPanel("Simulation Window"),
tabPanel("Statistical Result")
)
)
)))
Nothing is returned by your reactive conductor:
selectedsymbol <- reactive({
symbol <- input$selectstock
})
Use
selectedsymbol <- reactive({
symbol <- input$selectstock
return(symbol)
})