Shiny app with reactive data call from server - r

I'm trying to make a plot with reactive data from the server. Unfortunately I can't get the plot to work. I'm getting an error like: "Error:EXPR must be a length 1 vector". I tried different styles of plots and different libraries: Quantmod, ggplot, so on. Any suggestions?
Server:
library(shiny)
Dat<-read.csv("A:\\home\\Documents\\Franchise_Failureby_Brand2011.csv", sep=';')
names(Dat)[1]<-paste("Brand")
names(Dat)[2]<-paste("Failure")
names(Dat)[3]<-paste("Disbursement")
names(Dat)[4]<-paste("Disb$X$1000")
names(Dat)[5]<-paste("Chgoff")
Dat1<-Dat[is.na(Dat)==FALSE,]
Dat<-Dat1[1:578,]
# Define server logic required to draw a histogram
shinyServer(function(input, output) {
DatSv <- reactive({
Value <- switch(input$Value,
"Failure"= Dat$Failure[1:10],
"Disbursement"=Dat$Disbursement[1:10],
"Disb$X$1000"=Dat$`Disb$X$1000`[1:10],
"Chgoff"=Dat$Chgoff[1:10])
Brand<-Dat$Brand[1:10]
Brand(input$Value)
})
# Generate plot
output$plot1 <- renderPlot({
library("quantmod")
hist(DatSv(),
main=paste('r', Value, '(', Brand, ')', sep=''))
})
# Generate summary of data
output$summary<-renderPrint({
summary(Dat)
})
})
UI:
library(shiny)
shinyUI(fluidPage(
titlePanel("Plot Franchise Failure"),
sidebarLayout(
sidebarPanel(
radioButtons("n", "Chose output Y Axis:",
c("Failure" ,
"Disbursement",
"Disb$X$1000" ,
"Chgoff" )),
checkboxInput("show_xlab", "Show/Hide X Axis Label", value=TRUE),
checkboxInput("show_ylab", "Show/Hide Y Axis Label", value=TRUE),
checkboxInput("show_title", "Show/Hide Title")
),
mainPanel(
tabsetPanel(
type = "tabs",
tabPanel("Plot", plotOutput("plot1")),
tabPanel("Summary", verbatimTextOutput("summary"))
)
)
)
)
)

Hi the problem comes from connecting the inputs in the UI with the server. In the UI you have given the inputid = "n" for the radioButtons. That means we can get the Value of the Radiobuttons with input$n and not input$Value. The later is always NULL since there is no input with inputid = "Value". I had some other small problems with your code but here is a working version of the server code. I didn't modify the UI
library(shiny)
Dat<-read.csv("A:\\home\\Documents\\Franchise_Failureby_Brand2011.csv", sep=';')
names(Dat)[1]<-paste("Brand")
names(Dat)[2]<-paste("Failure")
names(Dat)[3]<-paste("Disbursement")
names(Dat)[4]<-paste("Disb$X$1000")
names(Dat)[5]<-paste("Chgoff")
Dat1<-Dat[is.na(Dat)==FALSE,]
Dat<-Dat1[1:578,]
# Define server logic required to draw a histogram
shinyServer(function(input, output) {
DatSv <- reactive({
switch(input$n,
"Failure"= gsub("%","",as.character( Dat$Failure)),
"Disbursement"=Dat$Disbursement,
"Disb$X$1000"=gsub("\\$","",as.character( Dat$`Disb$X$1000`)),
"Chgoff"=gsub("%","",as.character(Dat$Chgoff)))
})
# Generate plot
output$plot1 <- renderPlot({
library("quantmod")
hist(as.numeric(DatSv()),
main=paste('Histogram of ',input$n, sep=''),
xlab = input$n)
})
# Generate summary of data
output$summary<-renderPrint({
summary(Dat)
})
})

Related

Is it possible to have one function to download various ggplot plots?

My shiny app generates a number of useful graphs. I would like to allow the user to download the graphs in various formats.
I have done this before for a single graph using How to save plots that are made in a shiny app as a guide. However, I am ending up creating more repeated code for each additional plot. I am not a programmer, but it really seems like I should be able to write one function to do this since I am just passing parameters to downloadHandler and ggsave, but I can't figure it out.
The MRE below represents a page with, say, ten different graphs. Is there a way to write a single function that receives the plot ID from a button (like a tag or something?) and the format from the selectInput to pass those parameters to downloadHandler and ggsave to save each of those graphs in the selected format? The function at the bottom shows my thinking, but I don't know where to go from here or if that is even the right direction.
Thanks!
library(shiny)
library(ggplot2)
# Define UI for application that draws a histogram
ui <- fluidPage(
# Application title
titlePanel("Old Faithful Geyser Data"),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
sliderInput("bins",
"Number of bins:",
min = 1,
max = 50,
value = 30)
),
# Show plots and download buttons
mainPanel(
plotOutput("distPlot"),
fluidRow(
column(3,
downloadButton("dl_plot1")
),
column(3,
selectInput("plot1_format",label = "Format",choices = c("SVG","PDF","JPEG","PNG"),width = "75px")
)
),
plotOutput("scat_plot"),
column(3,
downloadButton("dl_plot2")
),
column(3,
selectInput("plot2_format",label = "Format",choices = c("SVG","PDF","JPEG","PNG"),width = "75px")
)
)
)
)
# Define server logic required to draw a histogram and scatterplot
server <- function(input, output) {
output$distPlot <- renderPlot({
x <- faithful$waiting
binwidth<-(max(x)-min(x))/input$bins
p<-ggplot(faithful,aes(waiting))+
geom_histogram(binwidth = binwidth)
p
})
output$scat_plot<-renderPlot({
p<-ggplot(faithful,aes(x=waiting,y=eruptions))+
geom_point()
p
})
downloadPlot <- function(plot_name,file_name,file_format){#concept code
downloadHandler(
filename=function() { paste0(file_name,".",file_format)},
content=function(file){
ggsave(file,plot=plot_name,device=file_format)
}
)
}
}
# Run the application
shinyApp(ui = ui, server = server)
To achieve your desired result without duplicating code you could (or have to) use a Shiny module. Basically a module is a pair of an UI function and a server function. For more on modules I would suggest to have a look at e.g. Mastering shiny, ch. 19.
In the code below I use a module to take care of the download part. The job of downloadButtonUI and downloadSelectUI is to add a download button and a selectInput for the file format. The downloadServer does the hard work and saves the plot in the desired format.
Note: Besides the download module I moved the code for the plots to reactives so that the plots could be passed to the downloadHandler or the download module.
EDIT: Added a fix. We have to pass the reactive (e.g. dist_plot without parentheses) to the download server and use plot() inside the downloadServer instead to export the updated plots.
library(shiny)
library(ggplot2)
# Download Module
downloaButtondUI <- function(id) {
downloadButton(NS(id, "dl_plot"))
}
downloadSelectUI <- function(id) {
selectInput(NS(id, "format"), label = "Format", choices = c("SVG", "PDF", "JPEG", "PNG"), width = "75px")
}
downloadServer <- function(id, plot) {
moduleServer(id, function(input, output, session) {
output$dl_plot <- downloadHandler(
filename = function() {
file_format <- tolower(input$format)
paste0(id, ".", file_format)
},
content = function(file) {
ggsave(file, plot = plot())
}
)
})
}
# Define UI for application that draws a histogram
ui <- fluidPage(
# Application title
titlePanel("Old Faithful Geyser Data"),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
sliderInput("bins",
"Number of bins:",
min = 1,
max = 50,
value = 30
)
),
# Show plots and download buttons
mainPanel(
plotOutput("distPlot"),
fluidRow(
column(3, downloaButtondUI("distPlot")),
column(3, downloadSelectUI("distPlot"))
),
plotOutput("scat_plot"),
fluidRow(
column(3, downloaButtondUI("scatPlot")),
column(3, downloadSelectUI("scatPlot"))
),
)
)
)
server <- function(input, output) {
dist_plot <- reactive({
p <- ggplot(faithful, aes(waiting)) +
geom_histogram(bins = input$bins)
p
})
scat_plot <- reactive({
p <- ggplot(faithful, aes(x = waiting, y = eruptions)) +
geom_point()
p
})
output$distPlot <- renderPlot({
dist_plot()
})
output$scat_plot <- renderPlot({
scat_plot()
})
downloadServer("distPlot", dist_plot)
downloadServer("scatPlot", scat_plot)
}
shinyApp(ui = ui, server = server)
#>
#> Listening on http://127.0.0.1:4092

Recomputing renderplot based on renderui user input in RShiny

I'm a bit of an RShiny and R novice. I'm trying to program an RShiny application. It would initially graphs a scatterplot matrix using the first three variables of the dataset by default. The user could then choose their own variable selections from a complete list of variables. Once variables are chosen, the user would click and action button and the graph would be recomputed using the newly selected variables.
I'm using selectinput rather than checkboxinput to accommodate datasets with many variables. I'm using the iris dataset. The code below produces the initial graph and allows the user to select the variables. I just can't figure out how to make it recompute the matrix plot. How do I do this? Thanks!
library(shiny)
runApp(list(
ui = fluidPage(
cols = colnames(iris),
headerPanel('Grow Clusters'),
tabsetPanel(
tabPanel("Plot",
sidebarPanel(
# uiOutput("varselect"),
selectInput("choose_vars", "Select variables to plot",
choices=colnames(iris), selected=iris[1:3], multiple=T),
actionButton("submitButton", "Produce Matrix Plot!")
),
mainPanel(
plotOutput('pairsplot')
)
),
tabPanel("Summary")
,
tabPanel("Table")
)
),
server = function(input, output) {
selectedData <- reactive({
cols = colnames(iris)
selectInput("choose_vars", "Select variables to plot",
choices=cols, selected=cols[1:3], multiple=T)
})
output$pairsplot <- renderPlot({
pairs(iris[1:3], pch = 21)
})
output$varselect <- renderUI({
iris[input$choose_vars]
plotOutput("pairsplot")
})
}
)
)
I think what you are looking for is quo function as in the Chris Beely blog: https://chrisbeeley.net/?p=1116
If you want users to pass arguments and then turn that character vector into objects r can read you need to use quo(input$choose_vars) and then in the plot you need to add !! before that passing variable. Notice you need to load dplyr.
library(shiny)
library(dplyr)
runApp(list(
ui = fluidPage(
cols = colnames(iris),
headerPanel('Grow Clusters'),
tabsetPanel(
tabPanel("Plot",
sidebarPanel(
# uiOutput("varselect"),
selectInput("choose_vars", "Select variables to plot",
choices=colnames(iris), selected=iris[1:3], multiple=T),
actionButton("submitButton", "Produce Matrix Plot!")
),
mainPanel(
plotOutput('pairsplot')
)
),
tabPanel("Summary")
,
tabPanel("Table")
)
),
server = function(input, output) {
selectedData <- reactive({
cols <- colnames(iris)
selectInput("choose_vars", "Select variables to plot",
choices=cols, selected=cols[1:3], multiple=T)
})
output$pairsplot <- renderPlot({
if(is.null(input$choose_vars) || length(input$choose_vars)<2){
pairs(iris[1:3], pch = 21)
} else {
var <- quo(input$choose_vars)
pairs(iris %>% select(!!var), pch = 21)
}
})
output$varselect <- renderUI({
iris[input$choose_vars]
plotOutput("pairsplot")
})
}
)
)

Display error message when api call comes back empty in Shiny?

I have an interactive visualization that connects to a city government's police data API.
When certain combinations of inputs are selected, my API call comes back empty and I get a nasty red error message (as my plot inputs are unavailable).
Can someone tell me how to display a more informative error message along the lines of, "there are no incidents matching your selection, please try again"? I would like this error message to appear as a showNotification and my ggplot not to render.
Below is an extremely stripped down version of what I am doing. Note how when a combination like "AVONDALE" and "CHEMICAL IRRITANT" is selected, the chart renders, whereas when a combination like "ENGLISH WOODS" and "TASER-BEANBAG-PEPPERBALL-40MM FOAM" is selected, an error message is returned. This error message is what I would like to address with a showNotification alert.
Note that this uses the Socrata API, so the package RSocrata must be installed and loaded.
install.packages("RSocrata")
library(shiny)
library(reshape2)
library(dplyr)
library(plotly)
library(shinythemes)
library(tibble)
library(RSocrata)
# Define UI for application that draws a histogram
ui <- fluidPage(
navbarPage("Example",
theme = shinytheme("united"),
tabPanel("Plot",
sidebarLayout(
sidebarPanel(
# neighborhood selector
selectizeInput("neighbSelect",
"Neighborhoods:",
choices = c("AVONDALE", "CLIFTON", "ENGLISH WOODS"),
multiple = FALSE)),
# incident description selector
selectizeInput("incSelect",
"Incident Type:",
choices = c("CHEMICAL IRRITANT", "TASER-BEANBAG-PEPPERBALL-40MM FOAM"),
multiple = FALSE))
),
# Output plot
mainPanel(
plotlyOutput("plot")
)
)
)
# Define server logic
server <- function(input, output) {
forceInput <- reactive({
forceInput <- read.socrata(paste0("https://data.cincinnati-oh.gov/resource/e2va-wsic.json?$where=sna_neighborhood= '", input$neighbSelect, "' AND incident_description= '", input$incSelect, "'"))
})
# Render plot
output$plot <- renderPlotly({
ggplot(data = forceInput(), aes(x = sna_neighborhood)) +
geom_histogram(stat = "count")
})
}
# Run the application
shinyApp(ui = ui, server = server)
Thank you so much for any help anyone can offer!
Im going to give an example with the shinyalert library to have the popup. Here I added the sample choice TEST to indicate no data:
#install.packages("RSocrata")
library(shiny)
library(reshape2)
library(dplyr)
library(plotly)
library(shinythemes)
library(tibble)
library(RSocrata)
library(shinyalert)
# Define UI for application that draws a histogram
ui <- fluidPage(
useShinyalert(),
navbarPage("Example",
theme = shinytheme("united"),
tabPanel("Plot",
sidebarLayout(
sidebarPanel(
# neighborhood selector
selectizeInput("neighbSelect",
"Neighborhoods:",
choices = c("AVONDALE", "CLIFTON", "ENGLISH WOODS","TEST"),
multiple = FALSE)),
# incident description selector
selectizeInput("incSelect",
"Incident Type:",
choices = c("CHEMICAL IRRITANT", "TASER-BEANBAG-PEPPERBALL-40MM FOAM"),
multiple = FALSE))
),
# Output plot
mainPanel(
plotlyOutput("plot")
)
)
)
# Define server logic
server <- function(input, output,session) {
forceInput <- reactive({
forceInput <- read.socrata(paste0("https://data.cincinnati-oh.gov/resource/e2va-wsic.json?$where=sna_neighborhood= '", input$neighbSelect, "' AND incident_description= '", input$incSelect, "'"))
if(nrow(forceInput)==0){
shinyalert("Oops!", "No data returned", type = "error")
forceInput <- NULL
}
forceInput
})
# Render plot
output$plot <- renderPlotly({
req(forceInput())
ggplot(data = forceInput(), aes(x = sna_neighborhood)) +
geom_histogram(stat = "count")
})
}
# Run the application
shinyApp(ui = ui, server = server)

R (RShiny) equivalent of layer_data function for other types of plots

I am building an RShiny-app where I am creating a plot based on a data table which I can edit and another data table which I cannot. I eventually want to save all data points on the plot in a data table which I can display and export.
I have seen many ways to do this using ggplot (ie layer_data, ggplot_build), but no efficient ways when just using plot and lines. My plots will be getting quite complicated so it would be really helpful to find an easy way to do this rather than hardcoding everything in.
A very simple example of my code is below (Note: plots will be getting much more complicated than this. They will be line graphs, but I will just need the y values at each x value marked with a number on the x axis):
x <- data.frame('col_1' = c(1,2,3,4,5), 'col_2' = c(4,5,6,7,8))
y <- data.frame('col_1' = c(5,4,3,6,7), 'col_2' = c(1,2,3,4,5))
#import necessary libraries
library(shiny)
library(DT)
library(shinythemes)
library(rhandsontable)
#ui
ui <- fluidPage(theme = shinytheme("flatly"),
titlePanel("Test"),
sidebarLayout(
sidebarPanel(
#display data
rHandsontableOutput('contents'),
#update plot button
actionButton("go", "Plot Update"),
width=4
),
mainPanel(
tabsetPanel(
#plot
tabPanel("Plot", plotOutput("plot_1")) )
))
)
#server
server <- function(input, output, session) {
#data table
output$table_b <- renderTable(x)
indat <- reactiveValues(data=y)
observe({
if(!is.null(input$contents))
indat$data <- hot_to_r(input$contents)
})
output$contents <- renderRHandsontable({
rhandsontable(indat$data)
})
#save updated data
test <- eventReactive(input$go, {
live_data = hot_to_r(input$contents)
return(live_data)
})
#plot
output$plot_1 <- renderPlot({
plot(x[,1],x[,2],col='red',type = 'l')
lines(test()[,1],x[,2], col='black', type='l')
# need a way to grab data from plot a create a table
})
}
shinyApp(ui, server)

R shiny: Display data set in shiny app

I am trying to print dataset values in shiny web app. But I am only able to print data set name using below code. How can I print dataset values?
library(MASS)
library(shinythemes)
library(shiny)
library(ggplot2)
mass.tmp <- data(package = "MASS")[3]
mass.datasets <- as.vector(mass.tmp$results[,3])
ui <- fluidPage(
theme = shinytheme("superhero"),
titlePanel("Linear Regression Modelling"),
sidebarLayout(
sidebarPanel(
selectInput("dsname", "Dataset:",choices = c(mass.datasets))
,
uiOutput("x_axis")
# ,
# textOutput("txt"),
# tableOutput("tab")
),
mainPanel(
tags$br(),
tags$br()
)
)
)
server <- function(input, output) {
num_ds <- function(ds)
{
nums <- sapply(ds,is.numeric)
num_ds <- ds[,nums]
return(num_ds)
}
ds_ext <- reactive({ num_ds(input$dsname) })
output$x_axis <- renderUI({
col_opts <- get(ds_ext())
selectInput("x_axis2", "Independent Variable:", choices = names(col_opts))
})
}
shinyApp(ui = ui, server = server)
Actually I am trying to solve error in above code "Incorrect number of dimensions". I have written function which would return data frame with only numeric variables so that I can analyze. But getting error in line I guess where I am creating object x_axis. pls help.

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