MenuItem rendered as subItem - r

Question

I have a problem with MenuItem in sidebarMenu. When I add a third MenuItem (RFM) it seems that in ui it renders as a subitem and when i click on that item there's nothing being displayed even if in the server.R there's the corresponding function. Here's a screenshot of the sidebarMenu
ui.R
dashboardPage(
dashboardHeader(title= "Acquisti Clienti CC"),
dashboardSidebar(
h4("Explorer"),
textInput("cluster","Digita un Codice cliente CC:","H01621"),
selectizeInput('categ',label="Seleziona una Categoria Merceologica",
choices=unique(user_clustering$DESC_CAT_MERC),
selected=c("NOTEBOOK","PC","TABLET/PDA"),
options = NULL,
multiple=TRUE),
#uiOutput("checkcluster"),
sidebarMenu(id="menu",
tags$style(".fa-stats {color:#f2f4f4}"),
tags$style(".fa-th-list {color:#f2f4f4}"),
menuItem("Dashboard", tabName = "dashboard",icon = icon("stats",lib = "glyphicon")),
menuItem("Data", tabName = "Data",icon = icon("th-list",lib = "glyphicon")),
menuItem("RFM",tabname="RFM",icon = icon("dashboard",lib = "glyphicon")) ## That's the item I ve just added
)
),
dashboardBody(
tabItems(
tabItem("dashboard",
fluidRow(
#valueBoxOutput("Spesa_Grafico",width=3),
valueBoxOutput("Spesa_Totale"),
#valueBoxOutput("Spesa_Cluster",width=3),
valueBoxOutput("Clienti_Totali")
),
fluidRow(
box(title="Cluster 1",plotlyOutput('plot1'),
fluidRow(column(4,offset=3,DT::dataTableOutput("plot1_data",width = 10)))),
#DT::dataTableOutput("plot1_data",width = 8),
box(title="Cluster 2",plotlyOutput('plot2'),
fluidRow(column(4,offset=3,DT::dataTableOutput("plot2_data",width = 10)))),
#DT::dataTableOutput("plot2_data",width = 8),
box(title="Cluster 3",plotlyOutput('plot3'),
fluidRow(column(4,offset=3,DT::dataTableOutput("plot3_data",width = 10)))),
#DT::dataTableOutput("plot3_data",width = 8),
box(title="Cluster 4",plotlyOutput('plot4'),
fluidRow(column(4,offset=3,DT::dataTableOutput("plot4_data",width = 10))))
#DT::dataTableOutput("plot4_data",width = 8)
)
)
,
tabItem("Data",
DT::dataTableOutput("Data"),
downloadButton("downloadCsv", "Download as CSV")
),
tabItem("RFM",
fluidRow(
box(title="RFM",plotOutput('plot_rfm')))
)
)
)
)
server.R
function(input, output, session) {
# Combine the selected variables into a new data frame
# Radar Chart data
selectedData <- reactive({
categ<-input[["categ"]]
data_plot<- user_clustering_raw %>%filter(DESC_CAT_MERC %in% categ)%>%
group_by(CLUSTER,DESC_CAT_MERC)%>%
dplyr::summarise(VAL_INV=sum(VAL_INV))%>%ungroup()%>%
group_by(CLUSTER)%>%mutate(VAL_INV=VAL_INV/sum(VAL_INV))
return (data_plot)
})
# RFM chart (2nd page....)
selectedData_plot2<-reactive({
clust<-user_clustering_raw[user_clustering_raw$CO_CUST==input$cluster,]$CLUSTER[0]
rfm <- RFM_rec %>%
inner_join(user_clustering_raw%>%select(CO_CUST,CLUSTER)%>%distinct(),by="CO_CUST")%>%
filter(CLUSTER %in% clust)
return (rfm)
})
# Data for summary alongside graph
summary_1<-reactive({
categ<-input[["categ"]]
summary_1<-user_clustering_raw%>%
filter(DESC_CAT_MERC%in% categ)
return (summary_1)
})
# Value box
output$Spesa_Totale <- renderValueBox({
valueBox(
value = prettyNum(round(sum(user_clustering$VAL_INV),0),big.mark=",",decimal.mark = "."),
subtitle = "Spesa Totale",
icon = icon("euro"),width=6
)
})
output$Clienti_Totali <- renderValueBox({
valueBox(
length(unique(user_clustering_raw%>%pull(CO_CUST))),
"Numero Clienti Totali",
icon = icon("users"),width=6
)
})
summary_2<-reactive({
outlier<-data.frame(CO_CUST=attributes(big_outliers),FLAG_OUTLIER=1)
colnames(outlier)<-c("CO_CUST","FLAG_OUTLIER")
data_summary_2<- user_clustering_raw%>%left_join(outlier,by="CO_CUST")%>%
replace_na(list(FLAG_OUTLIER=0))
colnames(data_summary_2)<-c("Codice Cliente", "Categoria Merc.",
"Spesa (EUR)","Cluster","Outlier")
data_summary_2
})
# 1 CLUSTER
output$plot1 <- renderPlotly({
categ<-input[["categ"]]
d1<-selectedData()
d1_clust<-d1%>%filter(DESC_CAT_MERC %in% categ)
d1_clust<-d1_clust%>%filter(CLUSTER==1)
plot_ly(
type = 'scatterpolar',
r = d1_clust$VAL_INV,
theta = d1_clust$DESC_CAT_MERC,
fill = 'toself'
) %>%
layout(
polar = list(
radialaxis = list(
visible = T,
range = c(0,1)
)
),
showlegend = F
)
})
output$plot1_data <- DT::renderDataTable({
plot1_data<-summary_1()
plot1_data<-plot1_data%>%filter(CLUSTER==1)%>%
group_by(DESC_CAT_MERC)%>%
summarise(VAL_INV=sum(VAL_INV),NUMERICA_CLIENTI=n_distinct(CO_CUST))%>%
ungroup()%>%
mutate(VAL_INV_PERC=round(VAL_INV/sum(VAL_INV),3)*100)
plot1_data <- plot1_data[c("DESC_CAT_MERC", "VAL_INV", "VAL_INV_PERC","NUMERICA_CLIENTI")]
colnames(plot1_data)<-c("Cat.Merceologica","Fatturato (EUR)","Fatturato %","Numero Clienti")
DT::datatable(plot1_data,rownames = FALSE,options = list(dom = 't',
columnDefs = list(list(className = 'dt-center', targets = "_all"))))%>%formatCurrency(2:2, '')
})
# 2 CLUSTER
output$plot2 <- renderPlotly({
categ<-input[["categ"]]
d1<-selectedData()
d2_clust<-d1%>%filter(DESC_CAT_MERC %in% categ)
d2_clust<-d2_clust%>%filter(CLUSTER==2)
plot_ly(
type = 'scatterpolar',
r = d2_clust$VAL_INV,
theta = d2_clust$DESC_CAT_MERC,
fill = 'toself',mode="markers"
) %>%
layout(
polar = list(
radialaxis = list(
visible = T,
range = c(0,1)
)
),
showlegend = F
)
})
output$plot2_data <- DT::renderDataTable({
plot2_data<-summary_1()
plot2_data<-plot2_data%>%filter(CLUSTER==2)%>%
group_by(DESC_CAT_MERC)%>%
summarise(VAL_INV=sum(VAL_INV),NUMERICA_CLIENTI=n_distinct(CO_CUST))%>%ungroup()%>%
mutate(VAL_INV_PERC=round(VAL_INV/sum(VAL_INV),3)*100)
plot2_data <- plot2_data[c("DESC_CAT_MERC", "VAL_INV", "VAL_INV_PERC","NUMERICA_CLIENTI")]
colnames(plot2_data)<-c("Cat.Merceologica","Fatturato (EUR)","Fatturato %","Numero Clienti")
DT::datatable(plot2_data,rownames = FALSE,
options = list(dom = 't',
columnDefs = list(list(className = 'dt-center', targets = "_all"))))%>%formatCurrency(2:2, '')
})
# 3 CLUSTER
output$plot3 <- renderPlotly({
categ<-input[["categ"]]
d1<-selectedData()
d3_clust<-d1%>%filter(DESC_CAT_MERC %in% categ)
d3_clust<-d3_clust%>%filter(CLUSTER==3)
plot_ly(
type = 'scatterpolar',
r = d3_clust$VAL_INV,
theta = d3_clust$DESC_CAT_MERC,
fill = 'toself'
) %>%
layout(
polar = list(
radialaxis = list(
visible = T,
range = c(0,1)
)
),
showlegend = F
)
})
output$plot3_data <- DT::renderDataTable({
plot3_data<-summary_1()
plot3_data<-plot3_data%>%filter(CLUSTER==3)%>%
group_by(DESC_CAT_MERC)%>%
summarise(VAL_INV=sum(VAL_INV),
NUMERICA_CLIENTI=n_distinct(CO_CUST))%>%ungroup()%>%
mutate(VAL_INV_PERC=round(VAL_INV/sum(VAL_INV),3)*100)
plot3_data <- plot3_data[c("DESC_CAT_MERC", "VAL_INV", "VAL_INV_PERC","NUMERICA_CLIENTI")]
colnames(plot3_data)<-c("Cat.Merceologica","Fatturato (EUR)","Fatturato %","Numero Clienti")
DT::datatable(plot3_data,rownames = FALSE,options = list(dom = 't',
columnDefs = list(list(className = 'dt-center', targets = "_all"))))%>%
formatCurrency(2:2, '')
})
# 4 CLUSTER
output$plot4 <- renderPlotly({
categ<-input[["categ"]]
d1<-selectedData()
d4_clust<-d1%>%filter(DESC_CAT_MERC %in% categ)
d4_clust<-d4_clust%>%filter(CLUSTER==3)
plot_ly(
type = 'scatterpolar',
r = d4_clust$VAL_INV,
theta = d4_clust$DESC_CAT_MERC,
fill = 'toself'
) %>%
layout(
polar = list(
radialaxis = list(
visible = T,
range = c(0,1)
)
),
showlegend = F
)
})
output$plot4_data <- DT::renderDataTable({
plot4_data<-summary_1()
plot4_data<-plot4_data%>%filter(CLUSTER==4)%>%
group_by(DESC_CAT_MERC)%>%
summarise(VAL_INV=sum(VAL_INV),
NUMERICA_CLIENTI=n_distinct(CO_CUST))%>%
ungroup()%>%mutate(VAL_INV_PERC=round(VAL_INV/sum(VAL_INV),3)*100)
plot4_data <- plot4_data[c("DESC_CAT_MERC", "VAL_INV", "VAL_INV_PERC","NUMERICA_CLIENTI")]
colnames(plot4_data)<-c("Cat.Merceologica","Fatturato (EUR)","Fatturato %","Numero Clienti")
DT::datatable(plot4_data,rownames = FALSE,options = list(dom = 't',
columnDefs = list(list(className = 'dt-center', targets = "_all"))))%>%
formatCurrency(2:2, '')
})
# rfm
output$plot_rfm <- renderPlot({
d<-selectedData_plot2()
adding_point<- d[d$CO_CUST==input$cluster,]
p1 <- ggplot(d,aes(x=FREQ))+
geom_histogram(fill="darkblue",col="white")+
ggtitle("Frequenza Acquisti")+labs(x="Frequenza Acquisti",y="Conteggio")+
geom_point(x=adding_point$FREQ,y=0,col="red",size=4)+
theme(axis.text.x = element_text(angle=45,hjust=1,size=12),
axis.title.x = element_blank(),plot.title = element_text(size=14,face="bold"))
breaks <- pretty(range(d$MONET), n = nclass.FD(d$MONET), min.n = 1)
bwidth <- breaks[2]-breaks[1]
p2 <- ggplot(d,aes(x=round(MONET,0)))+
geom_histogram(fill="darkblue",col="white")+
ggtitle("Valore Monetario Acquisti (EUR)")+labs(x="Valore Monetario",y="Conteggio")+
scale_x_continuous(labels=dollar_format(prefix="€"))+
geom_point(x=adding_point$MONET,y=0,col="red",size=4)+
theme(axis.text.x = element_text(angle=45,hjust=1,size=12),
axis.title.x = element_blank(),plot.title = element_text(size=14,face="bold"))
p3 <- ggplot(d,aes(x=LAST_PURCHASE))+
geom_histogram(fill="darkblue",col="white")+
ggtitle("Ultimo Acquisto (Giorni)")+labs(x="Ultimo Acquisto",y="Conteggio")+
geom_point(x=adding_point$LAST_PURCHASE,y=0,col="red",size=4)+
theme(axis.text.x = element_text(angle=45,hjust=1,size=12),
axis.title.x = element_blank(),plot.title = element_text(size=14,face="bold"))
grid.arrange(p1, p2,p3, nrow = 1)
})
# Data being displayed 2 tabitem
output$Data <- DT::renderDataTable({
DT::datatable(summary_2(),rownames = FALSE)%>% formatStyle(
'Outlier',
target = 'row',
color = styleEqual(c(1, 0), c('red', 'black')))%>%formatCurrency(3:3, '')
})
# Check CO_CLIENTE per errori input utente
output$checkcluster <- renderUI({
if (sum(input$cluster%in% user_clustering_raw$CO_CUST)==0)
print ("Errore! Codice Cliente non presente...")})
}
I hope it's clear enough, please don't downgrade

Answer 1

You missed a capital letter:
menuItem("RFM",tabname="RFM",icon = icon("dashboard",lib = "glyphicon")) ## That's the item I ve just added
tabname should be tabName.
Also, tabItem("RFM", should be tabItem("rfm", since it is linked to the id in the tabName parameter.
So, a stripped down working version is given below - minimizing the code is how I found the issue. Hope this helps!
library(shiny)
library(shinydashboard)
library(plotly)
ui <- dashboardPage(
dashboardHeader(title= "Acquisti Clienti CC"),
dashboardSidebar(
sidebarMenu(id="menu",
menuItem(text = "Dashboard", tabName = "dashboard",icon = icon("stats",lib = "glyphicon")),
menuItem(text = "Data", tabName = "Data",icon = icon("th-list",lib = "glyphicon")),
menuItem(text = "RFM", tabName="rfm",icon = icon("th-list",lib = "glyphicon"))
)
),
dashboardBody(
tabItems(
tabItem("dashboard",
p('dashboard')
)
,
tabItem("Data",
p('data')
),
tabItem("rfm",
p('rfm')
)
)
)
)
server <- function(input,output){}
shinyApp(ui,server)