add landfall map to all storms

dashboard.Rmd

@@ -104,6 +104,11 @@ loss_storms <- get_all_loss_storms()
 
 latest_normalized_losses <- get_latest_aggregate_losses()
 
+all_storm_tracks <- get_all_hurdat_tracks()
+
+all_storm_landfalls <- all_storm_tracks %>% 
+  filter(record_identifier == "L")
+
 storm_selection <- reactiveValues(
   storm_year = NULL,
   storm_name = NULL,
@@ -621,103 +626,7 @@ fillCol(
 Storm Fatalities {data-navmenu="Storm Details"}
 ===
 
-Fatalities {data-navmenu="Fatalities"}
-===
 
-Column {data-width=500}
----
-
-### {data-height=500}
-```{r}
-fatality_years <- seq(1900, 2010, by = 10)
-direct_deaths <- c(6000, 275, 0, 408, 26, 654, 466, 213, 104, 228, 1136, 321)
-indirect_deaths <- c(0, 0, 0, 0, 0, 1, 8, 15, 40, 54, 1171, 368)
-
-yearly_fatalities <- data.frame(fatality_years, direct_deaths, indirect_deaths) %>% 
-  mutate(
-    fatality_years = as.Date(paste0(fatality_years, "-01-01"))
-  )
-
-yearly_fatalities_ts <- yearly_fatalities %>% 
-  select(-fatality_years) %>% 
-  xts(order.by = yearly_fatalities$fatality_years)
-
-output$decade_fatalities <- renderDygraph(
-  dygraph(yearly_fatalities_ts, main = "Fatalities By Decade") %>% 
-    dySeries("direct_deaths", label = "Direct Deaths") %>% 
-    dySeries("indirect_deaths", label = "Indirect Deaths") %>% 
-    dyRangeSelector()
-)
-
-dygraphOutput("decade_fatalities")
-```
-
-### {data-height=500}
-```{r}
-surge_yearly <- c(0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 410, 107)
-surf_yearly <- c(0, 0, 0, 0, 0, 0, 0, 14, 2, 12, 12, 17)
-rough_seas_yearly <- c(0, 0, 0, 0, 16, 0, 2, 0, 24, 17, 0, 14)
-rip_current_yearly <- c(0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 14, 3)
-freshwater_floods_yearly <- c(0, 0, 0, 0, 0, 200, 12, 151, 0, 117, 50, 284)
-wind_yearly <- c(0, 0, 0, 0, 0, 0, 0, 8, 14, 23, 11, 82)
-tree_fall_yearly <- c(0, 0, 0, 0, 1, 0, 0, 1, 0, 9, 24, 56)
-tornado_yearly <- c(0, 0, 0, 0, 1, 12, 43, 7, 0, 7, 11, 7)
-traffic_yearly <- c(0, 0, 0, 0, 0, 0, 0, 4, 0, 3, 2, 1)
-traffic_accident_yearly <- c(0, 0, 0, 0, 0, 0, 5, 0, 0, 8, 26, 11)
-electrocution_yearly <- c(0, 0, 0, 0, 0, 0, 2, 0, 0, 5, 2, 7)
-other_yearly <- c(0, 0, 0, 0, 5, 0, 5, 11, 15, 13, 37, 7)
-
-yearly_fatalities_type <- data.frame(fatality_years, surge_yearly, surf_yearly, rough_seas_yearly, rip_current_yearly, freshwater_floods_yearly, wind_yearly, tree_fall_yearly, tornado_yearly, traffic_yearly, traffic_accident_yearly, electrocution_yearly, other_yearly) %>% 
-  mutate(
-    fatality_years = as.Date(paste0(fatality_years, "-01-01"))
-  )
-
-yearly_fatalities_type_ts <- yearly_fatalities_type %>% 
-  select(-fatality_years) %>% 
-  xts(order.by = yearly_fatalities_type$fatality_years)
-
-output$decade_fatalities_type <- renderDygraph(
-  dygraph(yearly_fatalities_type_ts, main = "Fatality Types By Decade") %>% 
-    dySeries("surge_yearly", label = "Surge") %>% 
-    dySeries("surf_yearly", label = "Surf") %>% 
-    dySeries("rough_seas_yearly", label = "Rough Seas") %>% 
-    dySeries("rip_current_yearly", label = "Rip Current") %>% 
-    dySeries("freshwater_floods_yearly", label = "Freshwater Floods") %>% 
-    dySeries("wind_yearly", label = "Wind") %>% 
-    dySeries("tree_fall_yearly", label = "Tree Fall") %>% 
-    dySeries("tornado_yearly", label = "Tornado") %>% 
-    dySeries("traffic_yearly", label = "Traffic") %>% 
-    dySeries("traffic_accident_yearly", label = "Traffic Accident") %>% 
-    dySeries("electrocution_yearly", label = "Electrocution") %>% 
-    dySeries("other_yearly", label = "Other") %>% 
-    dyRangeSelector()
-)
-
-dygraphOutput("decade_fatalities_type")
-```
-
-Column {data-width=500}
----
-
-### {data-height=500}
-```{r}
-fatality_type <- c("Surge", "Surf", "Rough Seas", "Rip Current", "Floods", "Wind", "Tree Fall", "Tornado", "Traffic", "Traffic Accident", "Electrocution", "Other")
-fatality_totals <- c(520, 56, 77, 23, 826, 131, 91, 88, 10, 45, 16, 56)
-
-aggregate_fatality_types <- data.frame(fatality_type, fatality_totals)
-
-output$aggregate_fatalities <- renderBillboarder(
-  billboarder() %>% 
-    bb_piechart(aggregate_fatality_types) 
-    #%>% bb_legend(position = "right")
-)
-
-billboarderOutput("aggregate_fatalities")
-```
-
-### {data-height=500}
-```{r}
-```
 
 
 Normalization Calculator {data-navmenu="Compute"}
@@ -826,8 +735,13 @@ fillCol(
 Data Export {data-navmenu="Compute"}
 ===
 
-All Storms Table
+Tracked Storms {data-navmenu="All Storms"}
 ===
+
+Column {data-width=650}
+---
+
+### {}
 ```{r}
 
 #DT with storm, hurdatid, base damage, mmh, mmp, maybe multipliers?, sparkline?
@@ -856,5 +770,144 @@ DTOutput("normalized_storms_full_table")
 
 ```
 
+Column {data-width=350}
+---
+
+### {.no-padding}
+```{r}
+output$all_storms_map <- renderLeaflet({
+  leaflet() %>% 
+    addProviderTiles("CartoDB.Positron", option = providerTileOptions(minZoom = 2, maxZoom = 18)) %>% 
+    # %>% setView(lng = -89.8, lat = 29.6, zoom = 8)
+    #addPolylines(
+    #data = all_storm_tracks,
+    #lng = ~lon,
+    #lat = ~lat,
+    #weight = .5,
+    #color = "blue"
+  #) %>% 
+  addCircleMarkers(
+    data = all_storm_landfalls,
+    lng = ~lon,
+    lat = ~lat,
+    radius = 5,
+    weight = 0,
+    color = "red",
+    fillColor = "red",
+    fillOpacity = 0.8
+  ) %>% 
+  addCircles(
+    data = all_storm_landfalls,
+    lng = ~lon,
+    lat = ~lat,
+    radius = ~rmw_meters,
+    weight = 2,
+    color = "red",
+    fillColor = "red",
+    fillOpacity = 0.3
+  ) 
+})
+
+leafletOutput("all_storms_map")
+```
+
+Fatalities {data-navmenu="All Storms"}
+===
+
+Column {data-width=500}
+---
+
+### {data-height=500}
+```{r}
+fatality_years <- seq(1900, 2010, by = 10)
+direct_deaths <- c(6000, 275, 0, 408, 26, 654, 466, 213, 104, 228, 1136, 321)
+indirect_deaths <- c(0, 0, 0, 0, 0, 1, 8, 15, 40, 54, 1171, 368)
+
+yearly_fatalities <- data.frame(fatality_years, direct_deaths, indirect_deaths) %>% 
+  mutate(
+    fatality_years = as.Date(paste0(fatality_years, "-01-01"))
+  )
+
+yearly_fatalities_ts <- yearly_fatalities %>% 
+  select(-fatality_years) %>% 
+  xts(order.by = yearly_fatalities$fatality_years)
+
+output$decade_fatalities <- renderDygraph(
+  dygraph(yearly_fatalities_ts, main = "Fatalities By Decade") %>% 
+    dySeries("direct_deaths", label = "Direct Deaths") %>% 
+    dySeries("indirect_deaths", label = "Indirect Deaths") %>% 
+    dyRangeSelector()
+)
+
+dygraphOutput("decade_fatalities")
+```
+
+### {data-height=500}
+```{r}
+surge_yearly <- c(0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 410, 107)
+surf_yearly <- c(0, 0, 0, 0, 0, 0, 0, 14, 2, 12, 12, 17)
+rough_seas_yearly <- c(0, 0, 0, 0, 16, 0, 2, 0, 24, 17, 0, 14)
+rip_current_yearly <- c(0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 14, 3)
+freshwater_floods_yearly <- c(0, 0, 0, 0, 0, 200, 12, 151, 0, 117, 50, 284)
+wind_yearly <- c(0, 0, 0, 0, 0, 0, 0, 8, 14, 23, 11, 82)
+tree_fall_yearly <- c(0, 0, 0, 0, 1, 0, 0, 1, 0, 9, 24, 56)
+tornado_yearly <- c(0, 0, 0, 0, 1, 12, 43, 7, 0, 7, 11, 7)
+traffic_yearly <- c(0, 0, 0, 0, 0, 0, 0, 4, 0, 3, 2, 1)
+traffic_accident_yearly <- c(0, 0, 0, 0, 0, 0, 5, 0, 0, 8, 26, 11)
+electrocution_yearly <- c(0, 0, 0, 0, 0, 0, 2, 0, 0, 5, 2, 7)
+other_yearly <- c(0, 0, 0, 0, 5, 0, 5, 11, 15, 13, 37, 7)
+
+yearly_fatalities_type <- data.frame(fatality_years, surge_yearly, surf_yearly, rough_seas_yearly, rip_current_yearly, freshwater_floods_yearly, wind_yearly, tree_fall_yearly, tornado_yearly, traffic_yearly, traffic_accident_yearly, electrocution_yearly, other_yearly) %>% 
+  mutate(
+    fatality_years = as.Date(paste0(fatality_years, "-01-01"))
+  )
+
+yearly_fatalities_type_ts <- yearly_fatalities_type %>% 
+  select(-fatality_years) %>% 
+  xts(order.by = yearly_fatalities_type$fatality_years)
+
+output$decade_fatalities_type <- renderDygraph(
+  dygraph(yearly_fatalities_type_ts, main = "Fatality Types By Decade") %>% 
+    dySeries("surge_yearly", label = "Surge") %>% 
+    dySeries("surf_yearly", label = "Surf") %>% 
+    dySeries("rough_seas_yearly", label = "Rough Seas") %>% 
+    dySeries("rip_current_yearly", label = "Rip Current") %>% 
+    dySeries("freshwater_floods_yearly", label = "Freshwater Floods") %>% 
+    dySeries("wind_yearly", label = "Wind") %>% 
+    dySeries("tree_fall_yearly", label = "Tree Fall") %>% 
+    dySeries("tornado_yearly", label = "Tornado") %>% 
+    dySeries("traffic_yearly", label = "Traffic") %>% 
+    dySeries("traffic_accident_yearly", label = "Traffic Accident") %>% 
+    dySeries("electrocution_yearly", label = "Electrocution") %>% 
+    dySeries("other_yearly", label = "Other") %>% 
+    dyRangeSelector()
+)
+
+dygraphOutput("decade_fatalities_type")
+```
+
+Column {data-width=500}
+---
+
+### {data-height=500}
+```{r}
+fatality_type <- c("Surge", "Surf", "Rough Seas", "Rip Current", "Floods", "Wind", "Tree Fall", "Tornado", "Traffic", "Traffic Accident", "Electrocution", "Other")
+fatality_totals <- c(520, 56, 77, 23, 826, 131, 91, 88, 10, 45, 16, 56)
+
+aggregate_fatality_types <- data.frame(fatality_type, fatality_totals)
+
+output$aggregate_fatalities <- renderBillboarder(
+  billboarder() %>% 
+    bb_piechart(aggregate_fatality_types) 
+    #%>% bb_legend(position = "right")
+)
+
+billboarderOutput("aggregate_fatalities")
+```
+
+### {data-height=500}
+```{r}
+```
+
 About 
 ===

queries.R

@@ -50,6 +50,12 @@ view.all_loss_storms <- tbl(con, "all_loss_storms")
 view.all_loss_landfalls <- tbl(con, "all_loss_landfalls")
 view.yearly_normalized_losses <- tbl(con, "yearly_normalized_losses")
 view.simplified_county_geom <- tbl(con, "simplified_county_geom")
+view.all_loss_storms_tracks <- tbl(con, "all_loss_storms_tracks")
+
+#qry <- econ.storm_base_loss %>% 
+#  left_join(view.hurdat_track, by = c("storm_basin", "storm_year", "storm_name"))
+
+#show_query(qry)
 
 # test storm
 #katrina <- list(
@@ -175,6 +181,15 @@ get_hurdat_landfalls <- function(storm) {
   return(result)
 }
 
+# returns all storm tracks from HURDAT
+get_all_hurdat_tracks <- function() {
+  query <- view.all_loss_storms_tracks
+  
+  result <- query %>% collect()
+  
+  return(result)
+}
+
 # returns storm track from HURDAT
 get_hurdat_track <- function(storm) {
   query <- view.hurdat_track %>%