Friends could help me with my shiny code below. It is executable code for manipulation. I am managing to generate the scatter plot normally, it varies according to my SliderInput. In my case, I am generating clusters. If sliderinput is selected as 5, the scatterplot will generate 5 clusters and so on. Everything is fine here. I also did a selectInput below the sliderinput to show the map for a specific cluster. However, I was unable to generate the scatterplot for a specific cluster, that is, if it selected 2 in my selectInput, I would like it to show only the map for cluster 2. Could you help me with this?
library(shiny)
library(ggplot2)
library(rdist)
library(geosphere)
library(kableExtra)
library(readxl)
library(tidyverse)
library(DT)
library(shinythemes)
#database
df<-structure(list(Properties = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35), Latitude = c(-23.8, -23.8, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9,
+ -23.9, -23.9, -23.9, -23.9, -23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9), Longitude = c(-49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.7,
+ -49.7, -49.7, -49.7, -49.7, -49.6, -49.6, -49.6, -49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6), Waste = c(526, 350, 526, 469, 285, 175, 175, 350, 350, 175, 350, 175, 175, 364,
+ 175, 175, 350, 45.5, 54.6,350,350,350,350,350,350,350,350,350,350,350,350,350,350,350,350)), class = "data.frame", row.names = c(NA, -35L))
function.cl<-function(df,k,Filter1,Filter2){
#cluster
coordinates<-df[c("Latitude","Longitude")]
d<-as.dist(distm(coordinates[,2:1]))
fit.average<-hclust(d,method="average")
#Number of clusters
clusters<-cutree(fit.average, k)
nclusters<-matrix(table(clusters))
df$cluster <- clusters
#Localization
center_mass<-matrix(nrow=k,ncol=2)
for(i in 1:k){
center_mass[i,]<-c(weighted.mean(subset(df,cluster==i)$Latitude,subset(df,cluster==i)$Waste),
weighted.mean(subset(df,cluster==i)$Longitude,subset(df,cluster==i)$Waste))}
coordinates$cluster<-clusters
center_mass<-cbind(center_mass,matrix(c(1:k),ncol=1))
#Coverage
coverage<-matrix(nrow=k,ncol=1)
for(i in 1:k){
aux_dist<-distm(rbind(subset(coordinates,cluster==i),center_mass[i,])[,2:1])
coverage[i,]<-max(aux_dist[nclusters[i,1]+1,])}
coverage<-cbind(coverage,matrix(c(1:k),ncol=1))
colnames(coverage)<-c("Coverage_meters","cluster")
#Sum of Waste from clusters
sum_waste<-matrix(nrow=k,ncol=1)
for(i in 1:k){
sum_waste[i,]<-sum(subset(df,cluster==i)["Waste"])
}
sum_waste<-cbind(sum_waste,matrix(c(1:k),ncol=1))
colnames(sum_waste)<-c("Potential_Waste_m3","cluster")
#Output table
data_table <- Reduce(merge, list(df, coverage, sum_waste))
data_table <- data_table[order(data_table$cluster, as.numeric(data_table$Properties)),]
data_table_1 <- aggregate(. ~ cluster + Coverage_meters + Potential_Waste_m3, data_table[,c(1,7,6,2)], toString)
#Scatter Plot
suppressPackageStartupMessages(library(ggplot2))
df1<-as.data.frame(center_mass)
colnames(df1) <-c("Latitude", "Longitude", "cluster")
g<-ggplot(data=df, aes(x=Longitude, y=Latitude, color=factor(clusters))) + geom_point(aes(x=Longitude, y=Latitude), size = 4)
Centro_View<- g + geom_text(data=df, mapping=aes(x=eval(Longitude), y=eval(Latitude), label=Waste), size=3, hjust=-0.1)+ geom_point(data=df1, mapping=aes(Longitude, Latitude), color= "green", size=4) + geom_text(data=df1, mapping = aes(x=Longitude, y=Latitude, label = 1:k), color = "black", size = 4)
plotGD<-print(Centro_View + ggtitle("Scatter Plot") + theme(plot.title = element_text(hjust = 0.5)))
return(list(
"Data" = data_table_1,
"Plot" = plotGD,
"Plot1" = plotGD
))
}
ui <- bootstrapPage(
navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
"Cl",
tabPanel("Solution",
#fileInput("data", h3("Import excel")),
sidebarLayout(
sidebarPanel(
radioButtons("filter1", h3("Select properties"),
choices = list("All properties" = 1,
"Exclude properties" = 2),
selected = 1),
radioButtons("filter2", h3("Select properties"),
choices = list("All properties" = 1,
"Exclude properties" = 2),
selected = 1),
tags$hr(),
tags$b(h3("Satisfied?")),
tags$b(h5("(a) Choose other filters")),
tags$b(h5("(b) Choose clusters")),
sliderInput("Slider", h5(""),
min = 2, max = 8, value = 5),
tags$hr(),
actionButton("reset", "Reset")
),
mainPanel(
tabsetPanel(
tabPanel("Solution", plotOutput("ScatterPlot"))))
))),
tabPanel("",
sidebarLayout(
sidebarPanel(
selectInput("select", label = h4("Select just one cluster to show"),""),
),
mainPanel(
tabsetPanel(
tabPanel("Map", plotOutput("ScatterPlot1"))))
)))
server <- function(input, output, session) {
Modelcl<-reactive(function.cl(df,input$Slider,1,1))
output$ScatterPlot <- renderPlot({
Modelcl()[[1]]
})
output$ScatterPlot1 <- renderPlot({
Modelcl()[[2]]
})
observeEvent(c(df,input$Slider),{
abc <- req(Modelcl()$Data)
updateSelectInput(session,'select',
choices=sort(unique(abc$cluster)))
})
}
shinyApp(ui = ui, server = server)
Thank you very much!