hurricane_normalization_app/queries.R

# DB queries for shiny app

library(tidyverse)
library(dplyr)
library(DBI)

linuxdir <- "/home/dylan/Personal/Projects/Hurricane Normalization/"
macdir <- "~/Desktop/Personal/Projects/Hurricane Normalization/"
#baseDir <- macdir
baseDir <- linuxdir

config <- config::get(file = paste0(baseDir, "R/dataScripts/restructured/app/config.yml"))

# SUPABASE CON
con <- dbConnect(
  RPostgres::Postgres(),
  host = config$db_host,
  port = config$db_port,
  dbname = config$db_dbname,
  user = config$db_user,
  password = config$db_password
)

# 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"))

# returns a list of loss storms we have data on
get_all_loss_storms <- function() {
  query <- 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_basin, storm_name, storm_year
    ) 
  
  result <- query %>% collect()
  
  return(result)
}