Rebasing

demo-2/README.md

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+# Demo-2
+This is a demo of how a shiny app is structure, which uses a simple `TextInput` element to transfer information from the UI to R.

demo-2/server.R

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+### Use input to create a string    
+shinyServer(function(input, output) {
+
+  # You can access the value of the widget with input$select, e.g.
+  output$userText <- renderText({
+    return(paste0('The user typed: ', input$text))
+  })
+
+})

demo-2/ui.R

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+# Demo 2: Simple TextInput element
+shinyUI(fluidPage(
+
+  # Create a text input element
+  textInput("text", label = h3("Text input"), value = "Enter text..."),
+
+  # Show output$userText
+  textOutput('userText')
+
+))

demo-3/README.md

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+# Demo-3
+This is a demo of how a shiny app is structure, which uses a simple `RadioInput` element to transfer information from the UI to R.

demo-3/server.R

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+### Use input to create a string    
+
+### Use input to create a histogram    
+shinyServer(function(input, output) {
+
+  # Reder a histogram of a given color
+  output$histogram <- renderPlot({
+    x <- rnorm(1000)
+    return(hist(x, col = input$color))
+  })
+})

demo-3/ui.R

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+# Demo 3: Simple RadioInput element
+shinyUI(fluidPage(
+
+  # Radio buttons
+  radioButtons("color", label = "Color",
+               choices = list("Green" = 'green', "Blue" = 'blue'), 
+               selected = 'green'),
+  plotOutput('histogram')
+))

exercise-1/exercise.R

@@ -1,11 +1,12 @@
 # Exercise 1: Loading functions
 
 # Set your directory
-setwd('~/Documents/info-201/m14-shiny/exercise-1/')
+setwd('~/Documents/INFO201/m14-shiny/exercise-1/')
 df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_us_cities.csv')
 
 # Load your buildMap.R Script
-
+source('./scripts/buildMap.R')
 
 # Use your BuildMap function to draw a map of the data
+BuildMap(df)
 

exercise-1/scripts/buildMap.R

@@ -7,10 +7,30 @@ library(plotly)
 # Try parameterize a few options, such as the title
 # I suggest: https://plot.ly/r/bubble-maps/
 BuildMap <- function(data) {
+  library(plotly)
+  df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_us_cities.csv')
 
+  df$q <- with(df, cut(pop, quantile(pop)))
+  levels(df$q) <- paste(c("1st", "2nd", "3rd", "4th", "5th"), "Quantile")
+  df$q <- as.ordered(df$q)
 
+  g <- list(
+    scope = 'usa',
+    projection = list(type = 'albers usa'),
+    showland = TRUE,
+    landcolor = toRGB("gray85"),
+    subunitwidth = 1,
+    countrywidth = 1,
+    subunitcolor = toRGB("white"),
+    countrycolor = toRGB("white")
+  )
 
-
-
+  p <- plot_geo(df, locationmode = 'USA-states', sizes = c(1, 250)) %>%
+    add_markers(
+      x = ~lon, y = ~lat, size = ~pop, color = ~q, hoverinfo = "text",
+      text = ~paste(df$name, "<br />", df$pop/1e6, " million")
+    ) %>%
+    layout(title = '2014 US city populations<br>(Click legend to toggle)', geo = g)
 
+  return (p)
 }

exercise-3/README.md

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+# Exercise-3
+In this exercise, you'll practice building an interactive Plotly map in a Shiny application. 
+
+As in previous exercises, you should fork and clone this repository, then follow the instructions below.
+
+## server.R
+Your `server.R` file already loads the data you need, as well as scripts for building a map. Inside your `shinyServer`, you should do the following:
+
+- Replace the static input `'population'` with a dynamic value that comes from your UI
+
+## ui.R
+Your `ui.R` file already has a `tabPanel` built displaying your map. In this section, you should add another `tabPanel` for your scatter-plot by doing the following:
+
+- Add a `selectInput` (with a proper id) that allows you to select a variable to map (`population`, `votes`, or `ratio`)
+
+Also, make sure you look at the `BuildMap` file and **understand how it is using variables to make a dynamic application**.

exercise-3/data/electoral_college.csv

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+state,votes,populationAlabama,9,4858979Alaska,3,738432Arizona,11,6828065Arkansas,6,2978204California,55,39144818Colorado,9,5456574Connecticut,7,3590886Delaware,3,945934Florida,29,20271272Georgia,16,10214860Hawaii,4,1431603Idaho,4,1654930Illinois,20,12859995Indiana,11,6619680Iowa,6,3123899Kansas,6,2911641Kentucky,8,4425092Louisiana,8,4670724Maine,4,1329328Maryland,10,6006401Massachusetts,11,6794422Michigan,16,9922576Minnesota,10,5489594Mississippi,6,2992333Missouri,10,6083672Montana,3,1032949Nebraska,5,1896190Nevada,6,2890845New Hampshire,4,1330608New Jersey,14,8958013New Mexico,5,2085109New York,29,19795791North Carolina,15,10042802North Dakota,3,756927Ohio,18,11613423Oklahoma,7,3911338Oregon,7,4028977Pennsylvania,20,12802503Rhode Island,4,1056298South Carolina,9,4896146South Dakota,3,858469Tennessee,11,6600299Texas,38,27469114Utah,6,2995919Vermont,3,626042Virginia,13,8382993Washington,12,7170351 District of Columbia,3,672228West Virginia,5,1844128Wisconsin,10,5771337Wyoming,3,586107

exercise-3/data/state_codes.csv

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+code,stateAL,AlabamaAK,AlaskaAZ,ArizonaAR,ArkansasCA,CaliforniaCO,ColoradoCT,ConnecticutDE,DelawareFL,FloridaGA,GeorgiaHI,HawaiiID,IdahoIL,IllinoisIN,IndianaIA,IowaKS,KansasKY,KentuckyLA,LouisianaME,MaineMD,MarylandMA,MassachusettsMI,MichiganMN,MinnesotaMS,MississippiMO,MissouriMT,MontanaNE,NebraskaNV,NevadaNH,New HampshireNJ,New JerseyNM,New MexicoNY,New YorkNC,North CarolinaND,North DakotaOH,OhioOK,OklahomaOR,OregonPA,PennsylvaniaRI,Rhode IslandSC,South CarolinaSD,South DakotaTN,TennesseeTX,TexasUT,UtahVT,VermontVA,VirginiaWA,WashingtonWV,West VirginiaWI,WisconsinWY,Wyoming

exercise-3/scripts/buildMap.R

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+# BuildMap file: function that returns a plotly map
+library(plotly)
+library(stringr)
+
+# BuildMap function: fill this in with a function that returns a map:
+# Derived from: https://plot.ly/r/choropleth-maps/
+
+BuildMap <- function(data, map.var) {
+  # give state boundaries a white border
+  l <- list(color = toRGB("white"), width = 2)
+
+  # specify some map projection/options
+  g <- list(
+    scope = 'usa',
+    projection = list(type = 'albers usa'),
+    showlakes = TRUE,
+    lakecolor = toRGB('white')
+  )
+
+  # Make equation for map color / text
+  var.equation <- paste0('~', map.var)
+
+  # Plot
+  p <- plot_geo(data, locationmode = 'USA-states') %>%
+    add_trace(
+      z = eval(parse(text = var.equation)), text = ~state, locations = ~code,
+      color = eval(parse(text = var.equation)), colors = 'Purples'
+    ) %>%
+    colorbar(title = "Color Title") %>%
+    layout(
+      title = str_to_title(map.var),
+      geo = g
+    )
+   return(p)
+}

exercise-3/server.R

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+# server.R
+library(dplyr)
+
+# Read in data
+setwd('~/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)
+
+# Join together state.codes and df
+joined.data <- left_join(df, state.codes, by="state")
+
+# Compute the electoral votes per 100K people in each state
+joined.data <- joined.data %>% mutate(ratio = votes/population * 100000)
+
+# Start shinyServer
+shinyServer(function(input, output) { 
+
+  # Render a plotly object that returns your map
+  output$map <- renderPlotly({ 
+      return(BuildMap(joined.data, 'population'))
+  })
+})

exercise-3/ui.R

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+# ui.R
+shinyUI(fluidPage(
+  mainPanel(
+    # Add a selectInput (with a proper id) that allows you to select a variable to map
+
+    # Use plotlyOutput to show your map
+    plotlyOutput('map')
+  )
+))

exercise-4/README.md

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+# Exercise-4
+In this exercise, you'll practice building an a multi-tab Shiny application. The final product should look like this:
+
+![scatter plot in shiny app](imgs/scatter.png)
+
+The Map panel is already built for you to model. Your scatter panel should enable users to search for a state in the scatterplot.
+
+As in previous exercises, you should fork and clone this repository, then follow the instructions below.
+
+## server.R
+Your `server.R` file already loads the data you need, as well as scripts for building a map and a scatter plot. Inside your `shinyServer`, you should do the following:
+
+- Create a `scatter` property on your `output` object. That property should be a `renderPlotly` object that returns a scatterplot (`BuildScatter`)
+- Make sure to pass your data and search string (i.e., `input$search`) to your `BuildScatter` function.
+
+## ui.R
+Your `ui.R` file already has a `tabPanel` built displaying your map. In this section, you should add another `tabPanel` for your scatter-plot by doing the following:
+
+- Create a `tabPanel` to show your scatter plot
+- Add a `titlePanel` to your tab
+- Create a `sidebarLayout` for this tab (page)
+- Create a `sidebarPanel` for your controls
+- In your `sidebarPanel`, make a `textInput` widget for searching for a state in your scatter plot
+- Create a `mainPanel`, in which you should display your plotly Scatter plot

exercise-4/data/electoral_college.csv

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+state,votes,populationAlabama,9,4858979Alaska,3,738432Arizona,11,6828065Arkansas,6,2978204California,55,39144818Colorado,9,5456574Connecticut,7,3590886Delaware,3,945934Florida,29,20271272Georgia,16,10214860Hawaii,4,1431603Idaho,4,1654930Illinois,20,12859995Indiana,11,6619680Iowa,6,3123899Kansas,6,2911641Kentucky,8,4425092Louisiana,8,4670724Maine,4,1329328Maryland,10,6006401Massachusetts,11,6794422Michigan,16,9922576Minnesota,10,5489594Mississippi,6,2992333Missouri,10,6083672Montana,3,1032949Nebraska,5,1896190Nevada,6,2890845New Hampshire,4,1330608New Jersey,14,8958013New Mexico,5,2085109New York,29,19795791North Carolina,15,10042802North Dakota,3,756927Ohio,18,11613423Oklahoma,7,3911338Oregon,7,4028977Pennsylvania,20,12802503Rhode Island,4,1056298South Carolina,9,4896146South Dakota,3,858469Tennessee,11,6600299Texas,38,27469114Utah,6,2995919Vermont,3,626042Virginia,13,8382993Washington,12,7170351 District of Columbia,3,672228West Virginia,5,1844128Wisconsin,10,5771337Wyoming,3,586107

exercise-4/data/state_codes.csv

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+code,stateAL,AlabamaAK,AlaskaAZ,ArizonaAR,ArkansasCA,CaliforniaCO,ColoradoCT,ConnecticutDE,DelawareFL,FloridaGA,GeorgiaHI,HawaiiID,IdahoIL,IllinoisIN,IndianaIA,IowaKS,KansasKY,KentuckyLA,LouisianaME,MaineMD,MarylandMA,MassachusettsMI,MichiganMN,MinnesotaMS,MississippiMO,MissouriMT,MontanaNE,NebraskaNV,NevadaNH,New HampshireNJ,New JerseyNM,New MexicoNY,New YorkNC,North CarolinaND,North DakotaOH,OhioOK,OklahomaOR,OregonPA,PennsylvaniaRI,Rhode IslandSC,South CarolinaSD,South DakotaTN,TennesseeTX,TexasUT,UtahVT,VermontVA,VirginiaWA,WashingtonWV,West VirginiaWI,WisconsinWY,Wyoming

exercise-4/scripts/buildMap.R

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+# BuildMap file: function that returns a plotly map
+library(plotly)
+library(stringr)
+
+# BuildMap function: fill this in with a function that returns a map:
+# Derived from: https://plot.ly/r/choropleth-maps/
+
+BuildMap <- function(data, map.var) {
+  # give state boundaries a white border
+  l <- list(color = toRGB("white"), width = 2)
+
+  # specify some map projection/options
+  g <- list(
+    scope = 'usa',
+    projection = list(type = 'albers usa'),
+    showlakes = TRUE,
+    lakecolor = toRGB('white')
+  )
+
+  # Make equation for map color / text
+  var.equation <- paste0('~', map.var)
+
+  # Plot
+  p <- plot_geo(data, locationmode = 'USA-states') %>%
+    add_trace(
+      z = eval(parse(text = var.equation)), text = ~state, locations = ~code,
+      color = eval(parse(text = var.equation)), colors = 'Purples'
+    ) %>%
+    colorbar(title = "Color Title") %>%
+    layout(
+      title = str_to_title(map.var),
+      geo = g
+    )
+   return(p)
+}

exercise-4/scripts/buildScatter.R

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+# BuildMap file: function that returns a plotly map
+library(plotly)
+library(stringr)
+### Build Scatter ###
+BuildScatter <- function(data,  search = '', xvar = 'population', yvar = 'votes') {
+  # Filter down to state, then graph
+
+  # Get x and y max
+  xmax <- max(data[,xvar]) * 1.5
+  ymax <- max(data[,yvar]) * 1.5
+  x.equation <- paste0('~', xvar)
+  y.equation <- paste0('~', yvar)
+  data <- data %>% 
+    filter(grepl(search, state))
+
+    plot_ly(data=data, x = eval(parse(text = x.equation)), 
+            y = eval(parse(text = y.equation)), 
+            mode='markers', 
+            marker = list(
+              opacity = .4, 
+              size = 10
+            )) %>% 
+    layout(xaxis = list(range = c(0, xmax), title = xvar), 
+           yaxis = list(range = c(0, ymax), title = yvar)
+    ) %>% 
+    return()
+}

exercise-4/server.R

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+# server.R
+library(dplyr)
+library(plotly)
+library(shiny)
+
+# Read in data
+# 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)
+state.codes <- read.csv('./data/state_codes.csv', stringsAsFactors = FALSE)
+
+# Join together state.codes and df
+joined.data <- left_join(df, state.codes, by="state")
+
+# Compute the electoral votes per 100K people in each state
+joined.data <- joined.data %>% mutate(ratio = votes/population * 100000)
+
+# Start shinyServer
+shinyServer(function(input, output) { 
+
+  # Render a plotly object that returns your map
+  output$map <- renderPlotly({ 
+      return(BuildMap(joined.data, input$mapvar))
+  }) 
+
+  # Create a `scatter` property on your `output` object. That property shoudl be a `renderPlotly` object that returns a scatterplot (`BuildScatter`)
+  output$scatter <- renderPlotly({
+      return(BuildScatter(joined.data, input$text))
+  })
+
+})

exercise-4/ui.R

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+# ui.R
+library(shiny)
+library(plotly)
+shinyUI(navbarPage('Electoral College',
+                   # Create a tab panel for your map
+                   tabPanel('Map',
+                            titlePanel('Electoral College Votes'),
+                            # Create sidebar layout
+                            sidebarLayout(
+
+                              # Side panel for controls
+                              sidebarPanel(
+
+                                # Input to select variable to map
+                                selectInput('mapvar', label = 'Variable to Map', choices = list("Population" = 'population', 'Electoral Votes' = 'votes', 'Votes / Population' = 'ratio'))
+                              ),
+
+                              # Main panel: display plotly map
+                              mainPanel(
+                                plotlyOutput('map')
+                              )
+                            )
+                   ), 
+
+                   # Create a tabPanel to show your scatter plot
+                   tabPanel('Scatter',
+                            # Add a titlePanel to your tab
+                          titlePanel("Electoral College Votes"),
+
+                            # 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('text', label = "State to Map", value = "")
+
+                              ),
+
+                              # Create a main panel, in which you should display your plotly Scatter plot
+                              mainPanel(
+                                plotlyOutput('scatter')
+                              )
+
+                          )    
+                   ) 
+))