sureshgorakala/include.html

## include.html
<!DOCTYPE html>
<html>

<head>

</head>

<body>
  <h1>HTML UI</h1>
  <table>
    <tr><td>
      <img src="D:/Suresh R&D/SentiApp/www/s1.jpg" alt="happy Simily">
    </td></tr>
    <tr><td>
      <img src="D:/Suresh R&D/SentiApp/www/s1.jpg" alt="normal Simily">
    </td></tr>
    <tr><td>
      <img src="D:/Suresh R&D/SentiApp/www/s1.jpg" alt="sad Simily">
    </td></tr>
  </table>

  <p>
    <label>Distribution type:</label><br />
    <select name="dist">
      <option value="norm">Normal</option>
      <option value="unif">Uniform</option>
      <option value="lnorm">Log-normal</option>
      <option value="exp">Exponential</option>
    </select>
  </p>

  <p>
    <label>Number of observations:</label><br />
    <input type="number" name="n" value="500" min="1" max="1000" />
  </p>

  <pre id="summary" class="shiny-text-output"></pre>

  <div id="plot" class="shiny-plot-output"
       style="width: 100%; height: 400px"></div>

  <div id="table" class="shiny-html-output"></div>
</body>

</html>

## server.R
library(shiny)

# Define server logic for random distribution application
shinyServer(function(input, output) {

  # Reactive expression to generate the requested distribution. This is
  # called whenever the inputs change. The output renderers defined
  # below then all used the value computed from this expression
  data <- reactive({
    dist <- switch(input$dist,
                   norm = rnorm,
                   unif = runif,
                   lnorm = rlnorm,
                   exp = rexp,
                   rnorm)

    dist(input$n)
  })

  # Generate a plot of the data. Also uses the inputs to build the
  # plot label. Note that the dependencies on both the inputs and
  # the data reactive expression are both tracked, and all expressions
  # are called in the sequence implied by the dependency graph
  output$plot <- renderPlot({
    dist <- input$dist
    n <- input$n

    hist(data(),
         main=paste('r', dist, '(', n, ')', sep=''))
  })

  # Generate a summary of the data
  output$summary <- renderPrint({
    summary(data())
  })

  # Generate an HTML table view of the data
  output$table <- renderTable({
    data.frame(x=data())
  })
})

## ui.R
library(markdown)

shinyUI(fluidPage(

  titlePanel("#Emirates Sentiment Analysis"),

  fluidRow(
    column(4,
      includeHTML("include.html")
    )
  )
))
	<!DOCTYPE html>
	<html>

	<head>

	</head>

	<body>
	<h1>HTML UI</h1>
	<table>
	<tr><td>
	<img src="D:/Suresh R&D/SentiApp/www/s1.jpg" alt="happy Simily">
	</td></tr>
	<tr><td>
	<img src="D:/Suresh R&D/SentiApp/www/s1.jpg" alt="normal Simily">
	</td></tr>
	<tr><td>
	<img src="D:/Suresh R&D/SentiApp/www/s1.jpg" alt="sad Simily">
	</td></tr>
	</table>

	<p>
	<label>Distribution type:</label><br />
	<select name="dist">
	<option value="norm">Normal</option>
	<option value="unif">Uniform</option>
	<option value="lnorm">Log-normal</option>
	<option value="exp">Exponential</option>
	</select>
	</p>

	<p>
	<label>Number of observations:</label><br />
	<input type="number" name="n" value="500" min="1" max="1000" />
	</p>

	<pre id="summary" class="shiny-text-output"></pre>

	<div id="plot" class="shiny-plot-output"
	style="width: 100%; height: 400px"></div>

	<div id="table" class="shiny-html-output"></div>
	</body>

	</html>
	library(shiny)

	# Define server logic for random distribution application
	shinyServer(function(input, output) {

	# Reactive expression to generate the requested distribution. This is
	# called whenever the inputs change. The output renderers defined
	# below then all used the value computed from this expression
	data <- reactive({
	dist <- switch(input$dist,
	norm = rnorm,
	unif = runif,
	lnorm = rlnorm,
	exp = rexp,
	rnorm)

	dist(input$n)
	})

	# Generate a plot of the data. Also uses the inputs to build the
	# plot label. Note that the dependencies on both the inputs and
	# the data reactive expression are both tracked, and all expressions
	# are called in the sequence implied by the dependency graph
	output$plot <- renderPlot({
	dist <- input$dist
	n <- input$n

	hist(data(),
	main=paste('r', dist, '(', n, ')', sep=''))
	})

	# Generate a summary of the data
	output$summary <- renderPrint({
	summary(data())
	})

	# Generate an HTML table view of the data
	output$table <- renderTable({
	data.frame(x=data())
	})
	})
	library(markdown)

	shinyUI(fluidPage(

	titlePanel("#Emirates Sentiment Analysis"),

	fluidRow(
	column(4,
	includeHTML("include.html")
	)
	)
	))