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rstudio
Error expected an object with class 'shiny.tag'
Below is my code for the server part which returns error as shown in the screenshot.
library(shinydashboard)
library(dplyr)
library(shiny)
library(ggplot2)
server <- shinyServer(function(input,output,session){
# read file
values <- reactive({read.csv(input$file$datapath,na.strings=c(" ",""," "," ")) })
# observeEvent for input$file
observeEvent(input$file, {
# render tables at file upload
output$data.frame <- renderTable(values())
# update selectInput#Question
updateSelectInput(
session,
inputId = "Question",
choices=names(values()),
selected=names(values()[,1])
)
})
# observeEvent for input$Go
observeEvent(input$Go, {
# temp <- values([-input$Delete, ] # commented for now
# values <- temp # commented for now
# commented for now
library(tm)
demo=Corpus(VectorSource(values()[,input$Question]))
demo=tm_map(demo,content_transformer(tolower))
demo=tm_map(demo,removePunctuation)
df<- data.frame(text=unlist(sapply(demo,`[`)),stringsAsFactors=F)
df$text=ifelse(df$text=="poor"|df$text=="fair","BAD",ifelse(df$text=="excellent"|df$text=="good","GOOD",NA))
output$pos <- renderValueBox({
# evaluate data: count, summarize, etc.
positive<- df%>%
filter(text=="GOOD") %>%count()
# make value box
valueBox(positive,"Positive Response")
})
output$neg <- renderValueBox({
# evaluate data: count, summarize, etc.
negative<- df%>%
filter(text=="BAD") %>%count()
# make value box
valueBox(negative,"Negative Response")
})
output$nrow <- renderValueBox({
#Number of records
records<- nrow(df)
# make value box
valueBox(records,"Total number of responses")
})
output$bar <- renderPlot({
#Bar chart
ggplot(data=df,aes(text,fill=text))+geom_bar(aes(y = (..count..)/sum(..count..)))+geom_text(aes(y = ((..count..)/sum(..count..)), label = scales::percent((..count..)/sum(..count..))), stat = "count", vjust = -0.25)+xlab("Selected Feedback")+ylab("Response Proportion")
})
output$JigID<-renderTable({
#Students who have given bad feedback
values()[which(df[,"text"]=="BAD"),"sis_id"]
})
})
observeEvent(input$file,{
updateSelectInput(
session,
inputId = "feeds",
choices=names(values()),
selected=names(values()[,1])
)})
observeEvent(input$Go, {
#Text analytics
library(tm)
feeds.corpus<-Corpus(VectorSource(values()[,input$feeds]))
#Data Transformations -Cleaning
feeds.corpus<-tm_map(feeds.corpus,tolower) #Converting to lower case
feeds.corpus<-tm_map(feeds.corpus,stripWhitespace) #Removing extra white space
feeds.corpus<-tm_map(feeds.corpus,removePunctuation) #Removing punctuations
feeds.corpus<-tm_map(feeds.corpus,removeNumbers) #Removing numbers
my_stopwords<-c(stopwords('english')) #Can add more words apart from standard list
feeds.corpus<-tm_map(feeds.corpus,removeWords,my_stopwords)
pos=c("good","very","best","satisfied","happy","excellent","nice","awesome","really","appreciate","easy","easier","precise","understand")
neg=c("missed","lost","late","don't","not","tougher","difficult","bad","doesn't","difficulty","concern","uptick")
#Famous Jeffreybreen Algorithm to "Tag" sentiments to sentences
score.sentiment = function(sentences, pos.words, neg.words, .progress='none')
{
require(plyr)
require(stringr)
#we got a vector of sentences. plyr will handle a list
#or a vector as an "l" for us
#we want a simple array of scores back, so we use
#"l" + "a" + "ply" = "laply":
scores = laply(sentences, function(sentence, pos.words, neg.words) {
#clean up sentences with R's regex-driven global substitute, gsub():
sentence = gsub('[[:punct:]]', '', sentence) #removes punctuations
sentence = gsub('[[:cntrl:]]', '', sentence) #removes control characters
sentence = gsub('\\d+', '', sentence) #removes digits
#and convert to lower case:
sentence = tolower(sentence)
#split sentences into words. str_split is in the stringr package
word.list = str_split(sentence, '\\s+')
#sometimes a list() is one level of hierarchy too much
words = unlist(word.list)
#compare our words to the dictionaries of positive & negative terms
pos.matches = match(words, pos.words)
neg.matches = match(words, neg.words)
#match() returns the position of the matched term or NA
#we just want a TRUE/FALSE:
pos.matches = !is.na(pos.matches)
neg.matches = !is.na(neg.matches)
#and conveniently enough, TRUE/FALSE will be treated as 1/0 by sum():
score = sum(pos.matches) - sum(neg.matches)
return(score)
}, pos.words, neg.words, .progress=.progress )
scores.df = data.frame(score=scores, text=sentences)
return(scores.df)
}
feeds.score<-score.sentiment(values()[,input$feeds], pos, neg, .progress="text")
feeds.score$text<-as.character(feeds.score$text)
feeds.score$sentiment<-ifelse(feeds.score$score>0,"positive",
ifelse(feeds.score$score<0,"negative","neutral"))
#Classified feeds
output$class_pos=renderValueBox({
feeds.score%>%filter(sentiment=="positive")%>%count()
})
output$class_neg=renderValueBox({
feeds.score%>%filter(sentiment=="negative")%>%count()
})
output$class_neu=renderValueBox({
feeds.score%>%filter(sentiment=="neutral")%>%count()
})
})
})
Please help.
It is more than likely your UI file, not your server file.
Check the inputs your providing into the UI functions and make sure they're correctly declared. See example below where by not including title= to the dashboardHeader function returns the same error you're experiencing.
library(shiny)
library(shinydashboard)
ui <- dashboardPage(
dashboardHeader("Invalid Title"),
# dashboardHeader(title="Valid Title"),
dashboardSidebar(),
dashboardBody()
)
server <- function(input, output) { }
shinyApp(ui, server)
> runApp('apppp.R')
[1] "Invalid Title"
Error in FUN(X[[i]], ...) : Expected an object with class 'shiny.tag'.
This code has certainly some issues:
output$class_neu=renderValueBox({
feeds.score%>%filter(sentiment=="neutral")%>%count()
})
However I'm also getting this error basically when I don't have data :
output$foo<- renderValueBox({
if(react() %>% nrow() < 1){
return()
}
valueBox(react()$Perf[1] %>% percent(accuracy = 0.1),
color = "yellow")
})
In this case NULL is returned and the error appears. Not sure how to best handle that.
I see this also when I have a trailing comma sometimes -- removing the comma usually fixes it
