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# Demo example for reactiveVal with observeEvent()
# Create dependency on a button to reflect user input changes to the rendered output 
library(shiny) # for Shiny components
library(dplyr) # for piping

my = mtcars %>% 
  mutate(cyl = as.factor(cyl))

ui <- fluidPage(
  h4("Demo of using reactiveVal() along with observeEvent() in R Shiny to subset data and display on click of action Button"),

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# Demo example for eventReactive()
# Create dependency on a button to reflect user input changes to the rendered output 
# subset data on click of button and display the resultant data

# Load the required libraries
library(shiny) # for Shiny components
library(dplyr) # for piping and data manipulation

# For demo using the mtcars dataset
# convert the cylinder variable to factor type

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# Demonstration of ggcorrplot package 
# Package created by Alboukadel Kassambara
# Reference link - https://cran.r-project.org/web/packages/ggcorrplot/ggcorrplot.pdf


# Load the required libraries
# install.packages("ggcorrplot")
library(ggcorrplot)

# mtcars dataset from base R used here for demonstration

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# Load required packages
library(shiny)
library(ggplot2)
library(dplyr)

# Adding State column to the original dataset for easy data manipulation at a later stage
states = row.names(USArrests)
crimedata = USArrests %>% 
  mutate("State" = as.factor(states)) # convert State to a factor variable

aagarw30

library(shiny)

ui <- fluidPage(
  radioButtons(inputId = "plot_type" , label = "Select the plot", choices = c("scatter", "bar", "hist" )),
  plotOutput("myplot")
  
)

server <- function(input, output, session) {
  

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## Load required packages

library(plotly)
library(ggplot2)
library(shiny)

## Defining a key column in mtcars which will be used for event handling in event_data()
mtcars$key <- row.names(mtcars)

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## How to disable the plotly tool bar from right top corner
## We will be using the pressure dataset for sake of demo

## Single file shiny app

## install the packages if not already
## Load the required libraries


library(shiny) # for shiny functions

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library(shiny)
# 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 = 9*1024^2)
# options(shiny.trace=T)

shinyServer(function(input,output) {
  
## input$file is a data frame and contains the details around the name, size and temp location of the files uploaded
# this reactive output display the content of the input$file dataframe
  output$filedf <- renderTable({

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# Load required packages
library(shiny)
library(ggplot2)

# UI Code begins here
ui <- fluidPage(
  sidebarLayout(
    sidebarPanel(
      ## Add inputs widgets later
    ),

aagarw30

library(shiny)
library(leaflet)
library(dplyr)
# Create a small dataframe
visits = data.frame(City=c("Bangalore", "Delhi", "Chennai", "Bangalore"), 
                    lat=c(12.972442, 28.644800, 13.067439, 12.972442), 
                    lon=c(77.580643, 77.216721, 80.237617, 77.580643), 
                    Year=c("2007", "2008", "2009", "2010")) 

visits$Year = as.Date(visits$Year, format="%Y")