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zhengjxu · May 6, 2018 · 6b043e1 · 6b043e1
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diff --git a/data/ajmatrix.rda b/data/ajmatrix.rda
diff --git a/data/axis_allies.txt b/data/axis_allies.txt
@@ -0,0 +1 @@
+In the Wolrd War II, The Axis powers, also known as the Axis and the Rome–Berlin–Tokyo Axis, were the nations that fought in World War II against the Allied forces. The Axis powers agreed on their opposition to the Allies, but did not completely coordinate their activity. The Axis grew out of the diplomatic efforts of Germany, Italy, and Japan to secure their own specific expansionist interests in the mid-1930s.<br>The Allies of World War II, called the United Nations from the 1 January 1942 declaration, were the countries that together opposed the Axis powers.The leaders of the "Big Three"—the Soviet Union, the United Kingdom, and the United States—controlled Allied strategy.<br><br>In the following Chord Diagram, different colors indicate military alliances. Clicking on one country, the Barplot on the right side will show cities being attacked associated to (may not be in) that country's force.
diff --git a/flight_route.rda → data/flight_route.rda b/flight_route.rda → data/flight_route.rda
diff --git a/data/groupColors.rda b/data/groupColors.rda
diff --git a/monthly_obs_count.csv → data/monthly_obs_count.csv b/monthly_obs_count.csv → data/monthly_obs_count.csv
diff --git a/operations.csv → data/operations.csv b/operations.csv → data/operations.csv
diff --git a/simplified_data.csv → data/simplified_data.csv b/simplified_data.csv → data/simplified_data.csv
diff --git a/data_preprocessing.R b/data_preprocessing.R
@@ -0,0 +1,69 @@
+library(tidyverse)
+####Data Preprocessing####0
+setwd("/media/yiqiang/D/USF/622DataViz/final project/finalproject/dataviz/")
+## Part 1: parse data to get map data
+df <- read_csv("data/operations.csv")
+map_data <- df %>% filter(is.na(Country) == FALSE & is.na(`Target Longitude`) == FALSE & is.na(`Takeoff Longitude`) == FALSE) %>%
+        filter(`Takeoff Latitude` != '4248', `Takeoff Longitude` != 1355) %>%
+          filter(`Target Longitude` > 0, `Takeoff Longitude` > 0, `Target Latitude` > 0, `Target Longitude` <=360) %>%
+            mutate(id=1:n())
+map_data$`Mission Date` <- as.Date(anytime::anydate(map_data$`Mission Date`))
+map_data$start_week <- cut(map_data$`Mission Date`, "week")
+flight_route <- gcIntermediate(map_data[ , c("Takeoff Longitude", "Takeoff Latitude")],
+                               map_data[ , c("Target Longitude", "Target Latitude")],
+                               n=20,
+                               addStartEnd=TRUE,
+                               sp=TRUE)
+write.csv(map_data, file = "data/simplified_data.csv", row.names = FALSE)
+save(flight_route, file="data/flight_route.rda")
+
+## Part 2: parse data to get obs count ts data
+Mission <-  df %>% select(`Mission Date`, `Mission ID`) %>%
+  filter(is.na(`Mission Date`) == F)
+Mission$`Mission Date` <- as.Date(anytime::anydate(Mission$`Mission Date`))
+Mission$start_month <- cut(Mission$`Mission Date`, "month")
+Mission$start_month = as.Date(Mission$start_month)
+Mission <- Mission %>% arrange(`Mission Date`)
+monthly_ct <- Mission %>% group_by(start_month) %>% summarise('ct' = n())
+write.csv(monthly_ct, file = "data/monthly_obs_count.csv", row.names = FALSE)
+
+## Part 3: chorddiag data
+diag_data <- df %>% select(`Target Country`, Country) %>% group_by(., `Target Country`, Country) %>% 
+  count() %>% filter(., is.na(Country) == FALSE, is.na(`Target Country`) == FALSE, n>100, 
+                     `Target Country` != 'UNKNOWN OR NOT INDICATED')
+library(igraph)
+diag_data <- as.data.frame(diag_data)
+diag_data[, 1] <- as.character(diag_data[, 1])
+diag_data[, 2] <- as.character(diag_data[, 2])
+diag_data[, 3] <- as.numeric(diag_data[, 3])
+diag_data <- as.matrix(diag_data)
+diag_net <- igraph::graph.edgelist(diag_data[,1:2])
+E(diag_net)$weights <- as.numeric(diag_data[,3])
+ajmatrix <- get.adjacency(diag_net,attr='weights', sparse = FALSE)
+Occupied <- toupper(c("Albania", "Belgium", "Czechoslovakia", "Denmark", "Estonia", 
+                      "Ethiopia", "France", "Greece", "Luxemburg", "Netherlands",
+                      "Norway", "Philippine Islands", "Poland", "Yugoslavia"))
+Axis <- toupper(c("Bulgaria", "Finland", "Germany", "Hungary", "Italy", "Japan", "Romania"))
+Allies <- toupper(c("Argentina", "Australia", "Bolivia", "Brazil", "Canada", "China",
+                    "Chile", "Columbia", "Costa Rica", "Cuba", "France", "India", "Iraq", 
+                    "Lebanon", "Mexico", "New Zealand", "Paraguay", "South Africa", "Soviet Union",
+                    "Great Britain", "USA"))
+Neutral <- toupper(c("Andorra", "Ireland", "Liechtenstein", "Portugal", "Spain", "Sweden",
+                     "Switzerland", "Turkey", "Uruguay", "Vatican City"))
+groupColors = c()
+for(country in dimnames(ajmatrix)[[1]]){
+  if(country %in% Occupied){
+    groupColors = c(groupColors, "#636363")
+  }else if(country %in% Axis){
+    groupColors = c(groupColors, "#25338a")
+  }else if (country %in% Allies){
+    groupColors = c(groupColors, "#9ecae1")
+  }else if (country %in% Neutral){
+    groupColors = c(groupColors, "#bdbdbd")
+  }else{
+    groupColors = c(groupColors, "#bdbdbd")
+  }
+}
+save(ajmatrix, file = "data/ajmatrix.rda")
+save(groupColors, file="data/groupColors.rda")
+
diff --git a/server.R b/server.R
@@ -7,53 +7,26 @@ library(mapview)
 library(crosstalk)
 library(sf)
 library(plotly)
-####Data Preprocessing####
-
-## Part 1: parse data to get map data
-
-# df <- read_csv("operations.csv")
-# df <- df %>% filter(is.na(Country) == FALSE & is.na(`Target Longitude`) == FALSE & is.na(`Takeoff Longitude`) == FALSE) %>%
-#         filter(`Takeoff Latitude` != '4248', `Takeoff Longitude` != 1355) %>%
-#           filter(`Target Longitude` > 0, `Takeoff Longitude` > 0, `Target Latitude` > 0, `Target Longitude` <=360) %>% 
-#             mutate(id=1:n())
-# df$`Mission Date` <- as.Date(anytime::anydate(df$`Mission Date`))
-# df$start_week <- cut(df$`Mission Date`, "week")
-# flight_route <- gcIntermediate(df[ , c("Takeoff Longitude", "Takeoff Latitude")],
-#                                df[ , c("Target Longitude", "Target Latitude")],
-#                                n=20,
-#                                addStartEnd=TRUE,
-#                                sp=TRUE)
-# write.csv(df, file = "simplified_data.csv", row.names = FALSE)
-
-## Part 2: parse data to get obs count ts data
-
-# df <- read_csv("operations.csv")
-# Mission <-  df %>% select(`Mission Date`, `Mission ID`) %>% 
-#   filter(is.na(`Mission Date`) == F)
-# Mission$`Mission Date` <- as.Date(anytime::anydate(Mission$`Mission Date`))
-# Mission$start_month <- cut(Mission$`Mission Date`, "month") 
-# Mission$start_month = as.Date(Mission$start_month)
-# Mission <- Mission %>% arrange(`Mission Date`)
-# monthly_ct <- Mission %>% group_by(start_month) %>% summarise('ct' = n())
-# write.csv(monthly_ct, file = "monthly_obs_count.csv", row.names = FALSE)
-
-df <- read_csv("simplified_data.csv")
-load("flight_route.rda") # to accelerate the loading speed
+library(chorddiag)
+####Loading Data####
+raw_data <- read_csv("data/operations.csv")
+df <- read_csv("data/simplified_data.csv")
+load("data/flight_route.rda") # to accelerate the loading speed
 df_takeoff <- df %>% st_as_sf(., coords = c("Takeoff Longitude", "Takeoff Latitude"))
 df_target <- df %>% st_as_sf(., coords = c("Target Longitude", "Target Latitude"))
-
-ts_df <- read_csv("monthly_obs_count.csv")
-
-
+ts_df <- read_csv("data/monthly_obs_count.csv")
+load("data/groupColors.rda")
+load("data/ajmatrix.rda")
+allies_axis_text <- read_file("data/axis_allies.txt")
 ####Sever####
 shinyServer(function(input, output, session) {
   target_map <- SharedData$new(df_target, key = ~id, group = "grp1")
   takeoff_map <- SharedData$new(df_takeoff, key = ~id, group = "grp2")
   lf <-   leaflet(target_map) %>%
     addTiles(urlTemplate = "https://api.mapbox.com/styles/v1/yiqiang/cjglw67l500262tqmguz0efum/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoieWlxaWFuZyIsImEiOiJjamI2MjJ2aDgzZTJiMzdvMTEza25vN3czIn0.da7McqdO9XgggUE0LTCx3Q"
     ) %>%  addPolylines(data = flight_route,  opacity = 0.3, fillOpacity = 0.2, color = "black", stroke = TRUE, weight = 1) %>%
-    addCircleMarkers(fillOpacity = 0.1, color = "red", radius = 1, group = "grp1") %>%
-    addCircleMarkers(data = takeoff_map, fillOpacity = 0.1, color = "blue", radius = 1, group = "grp2") %>%
+    addCircleMarkers(fillOpacity = 0.1, color = "#08519c", radius = 1, group = "grp1") %>%
+    addCircleMarkers(data = takeoff_map, fillOpacity = 0.1, color = "#969696", radius = 1, group = "grp2") %>%
     fitBounds(lng1=65.298593, lat1 = -15.124991, lng2 = -7.286442, lat2 = -173.134400) %>%
     setView(lat=24.719341, lng=68.718978, zoom=3) %>% 
     addMiniMap(tiles = "https://api.mapbox.com/styles/v1/yiqiang/cjglw67l500262tqmguz0efum/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoieWlxaWFuZyIsImEiOiJjamI2MjJ2aDgzZTJiMzdvMTEza25vN3czIn0.da7McqdO9XgggUE0LTCx3Q",
@@ -71,12 +44,13 @@ shinyServer(function(input, output, session) {
   observe({
     tmp_selected_target <- target_map$data(withSelection = TRUE) %>% filter(selected_ == TRUE)
     tmp_selected_takeoff <- takeoff_map$data(withSelection = TRUE) %>% filter(selected_ == TRUE)
+
 
   output$barplot <- renderPlotly(({
     tmp_data <- tmp_selected_target %>% group_by(`Aircraft Series`) %>% count() %>% arrange(n)
     tmp_data$Aircraft_Series <- tmp_data$`Aircraft Series`
     p <- ggplot(tmp_data) + 
-      aes(x = `Aircraft_Series`, y = `n`, fill=`Aircraft_Series`,
+      aes(x = `Aircraft_Series`, y = `n`,
           text=sprintf("Aircraft Series: %s<br>Num: %s", `Aircraft_Series`, `n`)) + 
       geom_bar(stat = 'identity') + 
       ylab("Count") + xlab("")  + ggtitle("Aircraft Series Barplot") +
@@ -94,19 +68,25 @@ shinyServer(function(input, output, session) {
   }))
 
   output$piechart <- renderPlotly(({
-    tmp_data <- tmp_selected_target %>% group_by(`Target Country`) %>% count()
+    colors <- c(rev(c("#deebf7", "#c6dbef", "#9ecae1", "#6baed6", "#4292c6", "#2171b5", "#08519c")),
+                rep("#deebf7", 20))
+    tmp_data <- tmp_selected_target %>% group_by(`Target Country`) %>% count() %>% arrange(., desc(n))
     tmp_data <- as.data.frame(tmp_data)
     textpos <- ifelse(tmp_data$n/sum(tmp_data$n, na.rm = TRUE) < 0.04, "none", "auto")
     m <- list(l = 50, r = 50, b = 20, t = 55, pad = 2)
     p2 <- plot_ly(tmp_data, labels = ~`Target Country`, values = ~n, type = 'pie',
-                  textposition = textpos, textinfo = 'label+percent') %>%
+                  insidetextfont = list(color = '#FFFFFF'),
+                  textposition = textpos, textinfo = 'label+percent',
+                  marker = list(colors = colors,
+                                line = list(color = '#FFFFFF', width = 0.5)
+                                )) %>%
           layout(paper_bgcolor = "#f0f0f0", title = "<b>Attacked Country Pie Chart<b>",
                  margin = m, font = list(size = 14))
     p2$elementId <- NULL
     p2
   }))
   leafletProxy("mymap") %>% clearControls()
-  leafletProxy("mymap") %>% addLegend("topright", colors= c("blue", "red"), 
+  leafletProxy("mymap") %>% addLegend("topright", colors= c("#969696", "#08519c"), 
                                        labels=c(paste("Takeoff:", nrow(tmp_selected_takeoff)), paste("Target:", nrow(tmp_selected_target))),
                                        title="Num",
                                        opacity = 0.5)
@@ -121,6 +101,50 @@ shinyServer(function(input, output, session) {
     p3$elementId <- NULL
     p3
   })
+
+  output$chorddiag <- renderChorddiag(
+    chorddiag(ajmatrix, groupColors = groupColors, groupnamePadding = 40, 
+              showGroupnames = FALSE, tooltipGroupConnector = ' <- ',
+              clickAction = "Shiny.onInputChange('sourceIndex', d.source.index+1);
+                                 Shiny.onInputChange('targetIndex', d.target.index+1);",
+              margin = 35, width = 10)
+  )
+
+  groupNames <- dimnames(ajmatrix)[[1]]
+
+  city_data <- reactive({
+    if(is.null(input$sourceIndex)){
+      t <- raw_data %>% filter(., Country == "USA", 
+                         `Target Country` == "GERMANY") %>% 
+        group_by(., `Target City`) %>% count() %>% arrange(desc(n)) %>% head(10) %>% as.data.frame()
+      return(t)
+    }else{
+      t <- raw_data %>% filter(., Country == groupNames[input$targetIndex], 
+                         `Target Country` == groupNames[input$sourceIndex]) %>% 
+        group_by(., `Target City`) %>% count() %>% arrange(desc(n)) %>% head(10) %>% as.data.frame()
+      return(t)
+  }
+    })
+  observe({
+    tmp_city_data <- city_data()
+    output$barplot2 <- renderPlotly({p3 <- ggplot(tmp_city_data) + 
+                       aes(x = `Target City`, y = `n`,
+                           text=sprintf("Target City: %s<br>Num: %s", `Target City`, `n`)) + 
+                       geom_bar(stat = 'identity') + 
+                       ylab("Count") + xlab("")  + ggtitle("Target City Barplot") +
+                       theme(axis.text.x = element_text(angle = 20, hjust = 1, colour = "#4f4f4f"), 
+                             plot.title = element_text(size = 14, face = "bold", colour = "#4f4f4f"),
+                             plot.background = element_rect(fill = "white"), 
+                             plot.margin = unit(c(0.5,0.5, 0.5, 0.5), "cm"), 
+                             axis.title=element_text(size=12), 
+                             legend.position="none") 
+                     p3 <- ggplotly(p3, tooltip="text")
+                     p3$elementId <- NULL
+                     p3})
 
+})
+
+  output$allies_axis <- renderText(allies_axis_text)
+
 })
 
diff --git a/ui.R b/ui.R
@@ -7,12 +7,7 @@ library(mapview)
 library(crosstalk)
 library(plotly)
 library(shinydashboard)
-# df <- read_csv("operations.csv")
-# df <- st_as_sf(df) %>% filter(is.na(Country) == FALSE & is.na(`Target Longitude`) == FALSE &
-#                       is.na(`Takeoff Longitude`) == FALSE) %>% 
-#   filter(`Takeoff Latitude` != '4248', `Takeoff Longitude` != 1355) %>%
-#   filter(`Target Longitude` > 0, `Takeoff Longitude` > 0)
-# df <- SharedData$new(df)
+
 
 shinyUI(dashboardPage(
   dashboardHeader(title = "World War II Viz"),
@@ -56,11 +51,33 @@ shinyUI(dashboardPage(
       ),
       tabItem(
         tabName = "time",
+        # fluidRow(box(column(width=12,
+        #                 img(src="world-war-ii-facts.jpg", width=1000)))),
+
         fluidRow(
-          box(
-            plotlyOutput("timeseries")
-          )
-        )
+        box(title = tags$b("Military Allies in WW2"),
+            status = "primary",
+            solidHeader = F,
+            collapsible = F,
+            width = 12,
+            fluidRow(
+              tags$style("#allies_axis {font-size:15px;
+               display:block; }"),
+              column(width = 9, 
+                     htmlOutput("allies_axis")),
+              column(width = 3, align = "center",
+                     img(src = "allied powers.jpg", height = '170px', width = '220px'))
+              ))
+            ),
+        fluidRow(box(
+          splitLayout(
+            cellWidths = c("40%", "60%"),
+            cellArgs = list(style = "padding: 6px"),
+            chorddiagOutput("chorddiag", height = 450),
+            plotlyOutput("barplot2", height = 450)
+          ), width = 12
+        ))
+
       )
     )
     # fluidRow(

diff --git a/www/1280px-Yalta_Conference_(Churchill,_Roosevelt,_Stalin)_(B&W).jpg b/www/1280px-Yalta_Conference_(Churchill,_Roosevelt,_Stalin)_(B&W).jpg
diff --git a/www/allied powers.jpg b/www/allied powers.jpg
diff --git a/www/world-war-ii-facts.jpg b/www/world-war-ii-facts.jpg
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		In the Wolrd War II, The Axis powers, also known as the Axis and the Rome–Berlin–Tokyo Axis, were the nations that fought in World War II against the Allied forces. The Axis powers agreed on their opposition to the Allies, but did not completely coordinate their activity. The Axis grew out of the diplomatic efforts of Germany, Italy, and Japan to secure their own specific expansionist interests in the mid-1930s.<br>The Allies of World War II, called the United Nations from the 1 January 1942 declaration, were the countries that together opposed the Axis powers.The leaders of the "Big Three"—the Soviet Union, the United Kingdom, and the United States—controlled Allied strategy.<br><br>In the following Chord Diagram, different colors indicate military alliances. Clicking on one country, the Barplot on the right side will show cities being attacked associated to (may not be in) that country's force.