worked on exercise

exercise-3/ui.R

@@ -3,6 +3,8 @@ shinyUI(fluidPage(
   mainPanel(
     # Add a selectInput (with a proper id) that allows you to select a variable to map
 
+    selectInput('mapvar', label = 'Variable to Map', choices = list("Population" = 'population', 'Electoral Votes' = 'votes', 'Votes / Population' = 'ratio')),
+
     # Use plotlyOutput to show your map
     plotlyOutput('map')
   )

exercise-4/server.R

@@ -2,7 +2,7 @@
 library(dplyr)
 
 # Read in data
-setwd('~/Documents/info-201/m14-shiny/exercise-4/')
+setwd('~/Documents/info-201/m18-shiny/exercise-3')
 source('./scripts/buildMap.R')
 source('./scripts/buildScatter.R')
 df <- read.csv('./data/electoral_college.csv', stringsAsFactors = FALSE)
@@ -23,5 +23,8 @@ shinyServer(function(input, output) {
   }) 
 
   # Create a `scatter` property on your `output` object. That property shoudl be a `renderPlotly` object that returns a scatterplot (`BuildScatter`)
+  output$scatter <- renderPlotly( {
+    return(BuildScatter(joined.data, input$search))
+  })
 
 })

exercise-4/ui.R

@@ -1,4 +1,5 @@
 # ui.R
+# install.packages("shiny")
 library(shiny)
 library(plotly)
 shinyUI(navbarPage('Electoral College',
@@ -25,10 +26,10 @@ shinyUI(navbarPage('Electoral College',
                    # Create a tabPanel to show your scatter plot
 
                             # Add a titlePanel to your tab
-
+                    tabPanel('Scatter',
 
                             # Create a sidebar layout for this tab (page)
-
+                            titlePanel('Population Vs. Vote Power')
 
                               # Create a sidebarPanel for your controls
 
@@ -37,5 +38,6 @@ shinyUI(navbarPage('Electoral College',
 
 
                               # Create a main panel, in which you should display your plotly Scatter plot
-
+
+                    )        
 ))

exercise-5/server.R

@@ -2,18 +2,22 @@
 
 #Require the following: shiny, HSUAR, dyplr, and ggplot2
 
+library(shiny)
+library(HSAUR)
+library(dplyr)
+library(ggplot2)
 
 #Load the dataset 'womensrole' from the HSUAR package (same way you would load a built in dataset)
 
-
+data <- womensrole
 
 #Here you will define the data that is shown based on your inputs defined in the UI
 #and turn it into an output plot
 #Hint: reference the input values using 'input$inputID'
 shinyServer(function(input, output) {
 
   #plotNameHere will become what you named your plot in the UI
-  output$plotNamehere <- renderPlot({
+  output$plot.of.role <- renderPlot({
 
     #Here use your different input values to define what data is used to render your plot
     #The x axis will be the level of education
@@ -22,17 +26,33 @@ shinyServer(function(input, output) {
 
 
     #Filter the dataset based on whether the input is Men, Women, or Both
-
+
+    if(input$sex == "Male") {
+      plot.data <- data %>% filter(sex == "Male")
+    }
+    if(input$sex == "Female") {
+      plot.data <- data %>% filter(sex == "Female")
+    }
+    if(input$sex == "Both") {
+      plot.data <- data
+    }
 
 
     #Define a y axis value based on the input Agree or Disagree
-
+
+    if(input$thoughts == "Agree") {
+      thoughts <- plot.data$agree
+    }
+    if(input$thoughts == "Disagree") {
+      thoughts <- plot.data$disagree
+    }
 
     #Using the values you just defined, construct a scatterplot using ggplot2
     #x will be defined by education, y by agree/disagree
     #Bonus: Factor the color field by sex 
     #(this will allow you to visually see the difference between Men and Women when Both are selected)
-
+
+    ggplot(data = plot.data, aes(x = education, y = thoughts, color = factor(sex))) + geom_point()
 
   })
 

exercise-5/ui.R

@@ -7,7 +7,7 @@ library(shiny)
 shinyUI(fluidPage(
 
   # Add a descriptive application title
-  titlePanel("Add Title Here"),
+  titlePanel("Women's Role in the World Survey"),
 
   # Here you will add the interactivity to your app
   # Create a selectInput where the user can select either Men, Women, or Both. 
@@ -19,18 +19,28 @@ shinyUI(fluidPage(
     sidebarPanel(
       #selectInput for Men, Women, or Both
       #inputID = sex
-
+      selectInput(
+        inputId = "sex",
+        label = "sex:",
+        choices = c("Male", "Female", "Both"),
+        selected = "Both"
+      ),
 
       #selectInput for Agree or Disagree
       #inputID = thoughts
-
+      selectInput(
+        inputId = "thoughts",
+        label = "thoughts:",
+        choices = c("Agree", "Disagree"),
+        selected = "Agree"
+      )
 
     ),
 
     # Show a plot of the generated distribution
     mainPanel(
       #give your plot a descriptive name
-       plotOutput("plotNamehere")
+       plotOutput("plot.of.role")
     )
   )
 ))