aagarw30

library(shiny)
shinyServer(function(input,output)({
  # x contains all the observations of the x variable selected by the user. X is a reactive function
  x <- reactive({
    iris[,as.numeric(input$var1)]
  })
  # x contains all the observations of the y variable selected by the user. Y is a reactive function
  y <- reactive({
    iris[,as.numeric(input$var2)]
    

aagarw30

library(shiny)
library(leaflet)
shinyServer(function(input, output, session){
  output$mymap <- renderLeaflet({
    # Classifying the type of earthquake based on magnitude
    quakes$type = ifelse((quakes$mag >= 4 & quakes$mag <= 4.9), "Light [4-4.9]",
                         ifelse((quakes$mag >= 5 & quakes$mag <= 5.9), "Moderate [5-5.9]",
                                ifelse((quakes$mag >= 6 & quakes$mag <= 6.9), "Strong [6-6.9]", 
                                       ifelse((quakes$mag >= 7 & quakes$mag <= 7.9), "Major [7-7.9]", "Great"      
                                       ))))

aagarw30

library(shiny)
library(data.table)
# use the below options code if you wish to increase the file input limit, 
# in this example file input limit is increased from 5MB to 9MB
 options(shiny.maxRequestSize = 700*1024^2)

shinyServer(function(input,output){
  
  # This reactive function will take the inputs from UI.R and use them for read.table() to read the data from the file. It returns the dataset in the form of a dataframe.
  # file$datapath -> gives the path of the file

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library(shiny)
library(googleVis)
shinyServer(function(input, output, session){
  



  output$bubble <- renderGvis({
    

aagarw30

library(shiny)
library(ggplot2)
shinyServer(function(input,output)({
  # x contains all the observations of the x variable selected by the user. X is a reactive function
  x <- reactive({
    iris[,as.numeric(input$var1)]
  })
  # x contains all the observations of the y variable selected by the user. Y is a reactive function
  y <- reactive({
    iris[,as.numeric(input$var2)]

aagarw30

library(shiny)
shinyServer(function(input, output, session){

  observe(
    {input$Year
    # Update based on the year change event
    updateSelectInput(session, "Month", "Month", choices = data$Month[data$Year==input$Year])
 }
    )
  

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library(shiny)

shinyServer(function(input, output,session){
  
  
})

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library(shiny)

shinyServer(function(input, output) {
  
# Split the elements input from the user
  v <- reactive({
    as.numeric(unlist(strsplit(input$vec1,",")))
  })
  
  # Print a message just before printing the vector values

aagarw30

Title: Multiple Action Button Demo - An attempt to button event based navigation/actions. Powered by R, Shiny and Rstudio.
License: GPL-3
Author: Abhinav Agrawal
DisplayMode: Showcase
Tags: action button, R, R Shiny
Type: Shiny

aagarw30

Title: Multiple Action Button Demo - Example # 2
Description: An attempt to button event based navigation/actions. Powered by R, Shiny and Rstudio.
License: GPL-3
Author: Abhinav Agrawal
DisplayMode: Showcase
Tags: action button, R, R Shiny
Type: Shiny