adding sample apps

module3/Sample Apps/ggplot-reactive.R

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+library(ggplot2)
+library(dplyr)
+library(shiny)
+
+df <- read.csv('https://raw.githubusercontent.com/charleyferrari/CUNY_DATA608/master/lecture3/Sample%20Code/hpi.csv')
+df$DATE <- as.POSIXct(strptime(df$DATE, format = '%m/%d/%y'))
+
+ui <- fluidPage(
+  headerPanel('Housing Price Explorer'),
+  sidebarPanel(
+    selectInput('seas', 'Seasonality', unique(df$Seasonality), selected='SA'),
+    selectInput('metro', 'Metro Area', unique(df$Metro), selected='Atlanta'),
+    selectInput('tier', 'Housing Tier', unique(df$Tier), selected='High')
+  ),
+  mainPanel(
+    plotOutput('plot1'),
+    verbatimTextOutput('stats')
+  )
+)
+
+server <- shinyServer(function(input, output, session) {
+
+  selectedData <- reactive({
+    dfSlice <- df %>%
+      filter(Seasonality == input$seas, Metro == input$metro)
+  })
+
+  output$plot1 <- renderPlot({
+
+    dfSlice <- df %>%
+      filter(Seasonality == input$seas, Metro == input$metro)
+
+    ggplot(selectedData(), aes(x = DATE, y = HPI, color = Tier)) +
+      geom_line()
+  })
+
+  output$stats <- renderPrint({
+    dfSliceTier <- selectedData() %>%
+      filter(Tier == input$tier)
+
+    summary(dfSliceTier$HPI)
+  })
+
+})
+
+shinyApp(ui = ui, server = server)

module3/Sample Apps/ggplot-simple.R

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+library(ggplot2)
+library(dplyr)
+library(plotly)
+library(shiny)
+
+df <- read.csv('https://raw.githubusercontent.com/charleyferrari/CUNY_DATA608/master/lecture3/Sample%20Code/hpi.csv')
+df$DATE <- as.POSIXct(strptime(df$DATE, format = '%m/%d/%y'))
+
+ui <- fluidPage(
+  headerPanel('Housing Price Explorer'),
+  sidebarPanel(
+    selectInput('seas', 'Seasonality', unique(df$Seasonality), selected='SA'),
+    selectInput('metro', 'Metro Area', unique(df$Metro), selected='Atlanta'),
+    selectInput('tier', 'Housing Tier', unique(df$Tier), selected='High')
+  ),
+  mainPanel(
+    plotOutput('plot1'),
+    verbatimTextOutput('stats')
+  )
+)
+
+server <- function(input, output, session) {
+
+  output$plot1 <- renderPlot({
+
+    dfSlice <- df %>%
+      filter(Seasonality == input$seas, Metro == input$metro)
+
+    ggplot(dfSlice, aes(x = DATE, y = HPI, color = Tier)) +
+      geom_line()
+  })
+
+  output$stats <- renderPrint({
+    dfSlice <- df %>%
+      filter(Seasonality == input$seas, Metro == input$metro, Tier == input$tier)
+
+    summary(dfSlice$HPI)
+  })
+
+}
+
+shinyApp(ui = ui, server = server)

module3/Sample Apps/plotly-simple.R

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+library(ggplot2)
+library(dplyr)
+library(plotly)
+library(shiny)
+
+df <- read.csv('https://raw.githubusercontent.com/charleyferrari/CUNY_DATA608/master/lecture3/Sample%20Code/hpi.csv')
+df$DATE <- as.POSIXct(strptime(df$DATE, format = '%m/%d/%y'))
+
+ui <- fluidPage(
+  headerPanel('Housing Price Explorer'),
+  sidebarPanel(
+    selectInput('seas', 'Seasonality', unique(df$Seasonality), selected='SA'),
+    selectInput('metro', 'Metro Area', unique(df$Metro), selected='Atlanta'),
+    selectInput('tier', 'Housing Tier', unique(df$Tier), selected='High')
+  ),
+  mainPanel(
+    plotlyOutput('plot1'),
+    verbatimTextOutput('stats')
+  )
+)
+
+server <- function(input, output, session) {
+
+  selectedData <- reactive({
+    dfSlice <- df %>%
+      filter(Seasonality == input$seas, Metro == input$metro)
+  })
+
+  output$plot1 <- renderPlotly({
+
+    dfSlice <- df %>%
+      filter(Seasonality == input$seas, Metro == input$metro)
+
+    plot_ly(selectedData(), x = ~DATE, y = ~HPI, color = ~Tier, type='scatter',
+            mode = 'lines')
+  })
+
+  output$stats <- renderPrint({
+    dfSliceTier <- selectedData() %>%
+      filter(Tier == input$tier)
+
+    summary(dfSliceTier$HPI)
+  })
+
+}
+
+shinyApp(ui = ui, server = server)