Update

demo-1/server.R

@@ -19,4 +19,4 @@ shinyServer(function(input, output) {
     hist(x, breaks = bins, col = 'darkgray', border = 'white')
   })
 
-})
+})

demo-1/ui.R

@@ -22,4 +22,4 @@ shinyUI(fluidPage(
       plotOutput("distPlot")
     )
   )
-))
+))

exercise-1/exercise.R

@@ -1,9 +1,11 @@
 # Exercise 1: Loading functions
 
 # Set your directory
-
+setwd('~/OneDrive/Documents/INFO 201/m18-shiny/exercise-1')
 
 # Source your BuildScatter.r script, exposing your BuildScatter function
-
+source('scripts/BuildScatter.R')
 
 # Use your BuildScatter function to draw a well labeled ggplot scatterplot of the iris data
+plot <- scatterplot(iris, 'Sepal.Length', 'Petal.Length', 'Species', 'Iris Dataset', 'Sepal Length', 'Petal Length')
+plot

exercise-1/scripts/BuildScatter.R

@@ -8,3 +8,11 @@
 #   - Title of the plot (set a default of "Title")
 #   - Label for the x axis (set a default of "X Title")
 #   - Label for the y axis (set a default of "Y Title")
+
+scatterplot <- function(df, xaxis, yaxis, color, ptitle = "Title", xlabel = "X Title", ylabel = "Y Title") {
+  library(ggplot2)
+  plot <- ggplot(df) +
+    geom_point(mapping = aes(x = df[, xaxis], y = df[, yaxis], color = df[, color])) +
+    labs(x = xlabel, y = ylabel, title = ptitle, color = color)
+  return (plot)
+}

exercise-3/server.R

@@ -1,8 +1,10 @@
 # server.R
 library(dplyr)
+library(plotly)
+library(shiny)
 
 # Read in data
-setwd('~/Documents/info-201/m14-shiny/exercise-3/')
+#setwd('~/OneDrive/Documents/info-201/m14-shiny/exercise-3/')
 source('./scripts/buildMap.R')
 df <- read.csv('./data/electoral_college.csv', stringsAsFactors = FALSE)
 state.codes <- read.csv('./data/state_codes.csv', stringsAsFactors = FALSE)
@@ -18,6 +20,6 @@ shinyServer(function(input, output) {
 
   # Render a plotly object that returns your map
   output$map <- renderPlotly({ 
-      return(BuildMap(joined.data, 'population'))
+      return(BuildMap(joined.data, input$var))
   })
 })

exercise-3/ui.R

@@ -2,6 +2,8 @@
 shinyUI(fluidPage(
   mainPanel(
     # Add a selectInput (with a proper id) that allows you to select a variable to map
+    selectInput('var', label = h3('Variable'),
+                choices = list('Population' = 'population', 'Votes' = 'votes', 'Ratio' = '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/m14-shiny/exercise-4/')
 source('./scripts/buildMap.R')
 source('./scripts/buildScatter.R')
 df <- read.csv('./data/electoral_college.csv', stringsAsFactors = FALSE)
@@ -23,5 +23,7 @@ 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$scatter <- renderPlotly({
+    return(BuildScatter(joined.data, input$state))
+  })
 })

exercise-4/ui.R

@@ -20,22 +20,27 @@ shinyUI(navbarPage('Electoral College',
                                 plotlyOutput('map')
                               )
                             )
-                   ) 
+                   ), 
 
                    # Create a tabPanel to show your scatter plot
-
+                   tabPanel('ScatterPlot',
                             # Add a titlePanel to your tab
-
+                            titlePanel('State'),
 
                             # Create a sidebar layout for this tab (page)
-
+                            sidebarLayout(
 
                               # Create a sidebarPanel for your controls
-
+                              sidebarPanel(
 
                                 # Make a textInput widget for searching for a state in your scatter plot
-
+                                textInput('state', label = 'Select State')
+                              ),
 
                               # Create a main panel, in which you should display your plotly Scatter plot
-
+                              mainPanel(
+                                plotlyOutput('scatter')
+                              )
+                            )  
+                   )
 ))