update db queries

dashboard.Rmd

@@ -41,18 +41,6 @@ baseDir <- linuxdir
 
 config <- config::get(file = paste0(baseDir, "R/dataScripts/restructured/app/config.yml"))
 
-
-
-# LOCAL CON
-#con <- dbConnect(
-#  RPostgres::Postgres(),
-#  user = "postgres",
-#  password = "oiuqBub8s9n65sgan09",
-#  host = "192.168.0.6",
-#  port = 5432,
-#  dbname = "hurricanedb"
-#)
-
 # SUPABASE CON
 con <- dbConnect(
   RPostgres::Postgres(),
@@ -69,36 +57,9 @@ selected_storm_basin <- "AL"
 selected_lf_type = "LF"
 selected_lf_id = "2"
 
-
-
-bestTrackQry <- paste0("SELECT * FROM hurdat.best_track WHERE storm_basin = '", selected_storm_basin, 
-                       "' AND storm_name = '", selected_storm_name,
-                       "' AND storm_year = ", selected_storm_year
-                       )
-
-qry <- "SELECT *, ST_X(ST_Transform(location::geometry, 4326)) as lon, ST_Y(ST_Transform(location::geometry, 4326)) as lat FROM hurdat.best_track WHERE storm_basin = 'AL' AND storm_name = 'KATRINA' AND storm_year = 2005"
-
 xlallLandfallsNormalized <- read.csv(paste0(baseDir, "R/dataScripts/restructured/normalization/all-landfalls-normalized.csv"), header = T) %>% 
   select(-X)
 
-katrinaTrack <- dbGetQuery(con, qry)
-katrinaTrack <- katrinaTrack %>% 
-  mutate(
-    date = make_datetime(datetime)
-  ) %>% 
-  select(
-    Date = date,
-    Latitude = lat,
-    Longitude = lon,
-    Pressure = pressure,
-    Windspeed = windspeed,
-    RMW = rmw,
-    record_identifier
-  )
-
-katrinaLandfalls <- katrinaTrack %>% 
-  filter(record_identifier == 'L') %>% 
-  select(-record_identifier)
   
 
 normalized2024 <- read.csv(paste0(baseDir, "R/dataScripts/restructured/normalization/2024-normalized.csv"), header = T) %>% 
@@ -150,8 +111,6 @@ housing <- read.csv(paste0(baseDir, "Data/housing_units.csv"), stringsAsFactors
 metrics.pop_and_housing <- pop %>% 
   left_join(housing, by = c("state_fips", "county_fips", "year"))
 
-#counties <- counties(state = "LA", cb = T)
-
 weightedCounties <- read.csv(paste0(baseDir, "R/dataScripts/weighted-counties.csv"), header = T) %>% 
   mutate(
     weight = (PERCENTAGE/100),
@@ -208,18 +167,9 @@ storm_selection <- reactiveValues(
   is_selected = FALSE
 )
 
-growth_trends <- reactiveValues(
-  lf_id = NULL
-)
-
 ######
 
 ###### SUPABASE PORT
-
-hurdat.hurdat_storms <- dbGetQuery(con, "SELECT *, CONCAT(storm_basin, storm_number, storm_year) AS hurdatId FROM hurdat.hurdat_storms")
-
-#hurdat.best_track <- dbGetQuery(con, "SELECT *, ST_X(ST_Transform(location::geometry, 4326)) as lon, ST_Y(ST_Transform(location::geometry, 4326)) as lat FROM hurdat.best_track")
-
 econ.normalized_landfalls <- dbGetQuery(con, "SELECT * FROM econ.normalized_landfalls")
 
 econ.storm_base_loss <- reactive({
@@ -248,16 +198,27 @@ econ.storm_base_loss <- reactive({
   dbGetQuery(con, query)
 })
 
+# LAZY LOAD DB TABLES
+
+econ.normalized_landfalls <- tbl(con, I("econ.normalized_landfalls"))
+econ.storm_base_loss <- tbl(con, I("econ.storm_base_loss"))
+econ.usa_yearly <- tbl(con, I("econ.usa_yearly"))
+
+fatal.storm_fatalities_type <- tbl(con, I("fatal.storm_fatalities_type"))
+fatal.storm_total_fatalities <- tbl(con, I("fatal.storm_total_fatalities"))
+
+fips.counties <- tbl(con, I("fips.counties"))
+fips.states <- tbl(con, I("fips.states"))
+
 gis.affected_area_landfalls <- tbl(con, I("gis.affected_area_landfalls"))
+
+hurdat.best_track <- tbl(con, I("hurdat.best_track"))
+hurdat.hurdat_storms <- tbl(con, I("hurdat.hurdat_storms"))
+
+metrics.geo_attributes <- tbl(con, I("metrics.geo_attributes"))
+#metrics.pop_and_housing <- tbl(con, I("metrics.pop_and_housing"))
+
 public.counties <- tbl(con, I("public.counties"))
-
-
-#allLandfallsNormalized <- econ.normalized_landfalls %>% 
-#  left_join(econ.storm_base_loss, by = c("storm_basin", "storm_year", "storm_name", "lf_type", "lf_id")) %>% 
-#  mutate(
-#    mmh = gdp_deflator * rwhu * affected_housing,
-#    mmp = gdp_deflator * rwpc * affected_population
-#  )
 ```
 
 ```{r}
@@ -391,27 +352,54 @@ Col {data-width=500}
 
 ### Storm Selector {data-height=500}
 ```{r}
-h5("Select Storm Name and Year")
+
+loss_storms <- econ.storm_base_loss %>% 
+  select(
+    storm_basin, storm_year, storm_name
+  ) %>% 
+  distinct(
+    storm_basin, storm_year, storm_name
+  ) %>% 
+  left_join(
+    hurdat.hurdat_storms %>%
+    mutate(hurdatId = paste0(storm_basin, storm_number, storm_year)), 
+    by = c("storm_basin", "storm_year", "storm_name")) %>% 
+  select(
+    hurdatId, storm_name, storm_year
+  ) %>% 
+  collect()
 
 dbStormYears <- dbGetQuery(con, "SELECT DISTINCT storm_year, storm_name FROM econ.storm_base_loss ORDER BY storm_year")
 
 fluidRow(
   column(6, 
-    selectInput("stormYear", "Select Year", choices = dbStormYears$storm_year)
+         h5("Select Storm Name and Year"),
+         selectInput("stormYear", "Select Year", choices = dbStormYears$storm_year),
+         selectInput("stormName", "Select Storm", choices = NULL),
+         actionButton("selectStorm", "Submit", class = "btn-primary")
   ),
   column(6,
-    selectInput("stormName", "Select Storm", choices = NULL)
+         #TODO: ADD TABLE
+      
+         #DTOutput("storm_selector_table")
   )
 )
 
-fluidRow(
+output$storm_selector_table <- renderDT({
-  column(12,
+  datatable(
-         actionButton("selectStorm", "Submit", class = "btn-primary"))
+    loss_storms,
-)
+    rownames = F,
-
+    options = list(
-#h5("Search")
+      pageLength = 1000,
-
+      order = list(2, 'desc'),
-#textInput("stormSearch", "Search by hurricane name, year")
+      searching = F,
+      paging = F,
+      info = F,
+      lengthChange = F,
+      server = T
+    )
+  )
+})
 
 observeEvent(input$stormYear, {
   stormsByChosenYear <- dbStormYears[dbStormYears$storm_year == input$stormYear, ]
@@ -500,17 +488,6 @@ dbUniq <- reactive({
   
   dbNormalizedLandfalls() %>% 
     distinct(lfid)
-  
-  #re <- unique(res$lfid)
-  
-  #cat(str(res))
-  #cat(str(re))
-  
-  #cat("hi2")
-  
-  #cat(str(res))
-  
-  #return(res)
 })
 
 lfNormalized <- reactive({
@@ -550,7 +527,6 @@ fillCol(
            #checkboxInput("mmpSelect", "Display MMP", value = T)
     )
   ),
-  #dygraphOutput("katrinaCostIndex")
   dygraphOutput("costIndex")
 )
 
@@ -558,10 +534,6 @@ fillCol(
 observe({
   req(dbUniq(), nrow(dbUniq()) > 0)
   
-  #cat("hi")
-  #cat(nrow(dbUniq()))
-  #cat(str(dbUniq()))
-  
   updateSelectInput(
     session,
     "lfSelect", 
@@ -689,6 +661,12 @@ Column {data-width=550}
 ### {data-height=1000 .no-padding}
 
 ```{r}
+growth_trends <- reactiveValues(
+  lf_id = NULL
+)
+
+
+
 dbStormCounties <- reactive({
   req(storm_selection$is_selected)
   
@@ -828,7 +806,7 @@ output$popHu <- renderDygraph({
 })
 
 
-dygraphOutput("popHu")
+#dygraphOutput("popHu")
 ```
 
 ### County Data {data-height=450 .no-padding}
@@ -852,7 +830,7 @@ output$katrinaCounties <- renderDT({
   ) 
 })
 
-DTOutput("katrinaCounties")
+#DTOutput("katrinaCounties")
 
 ```
 
@@ -890,6 +868,12 @@ Data {data-navmenu="Compute"}
 
 Top 50 Storms 
 ===
+```{r}
+
+#DT with storm, hurdatid, base damage, mmh, mmp, maybe multipliers?, sparkline?
+
+
+```
 
 About 
 ===