finishing cruise and air tourism indicator

.gitignore

@@ -1,6 +1,10 @@
-
 .Rproj.user
-
 /.quarto/
-
-.Rhistory
+.Rhistory
+index.aux
+index.lof
+index.log
+index.lot
+index.pdf
+index.tex
+index.toc

indicator_processing/automated_download/EPA_water_quality.R

@@ -0,0 +1,31 @@
+# Water quality indicator from the EPA water quality data portal: https://www.epa.gov/waterdata/TADA
+
+if(!"remotes"%in%installed.packages()){
+  install.packages("remotes")
+}
+
+remotes::install_github("USEPA/EPATADA", ref = "develop", dependencies = TRUE, force = TRUE)
+
+getwd() # find your working directory
+TADA::TADA_GetTemplate() # download template to working directory
+
+# uncomment below to review example dataset
+# Data_Nutrients_UT <- TADA::Data_Nutrients_UT
+
+EPATADA::TADA_GetTemplate()
+
+dataset_0 = EPATADA::TADA_DataRetrieval(
+     startDate = "2020-06-22",
+     endDate = "null",
+     countycode = "null",
+     huc = "null",
+     siteid = "null",
+     siteType = "null",
+     characteristicName = "null",
+     characteristicType = "null",
+     sampleMedia = "null",
+     statecode = "PR",
+     organization = "null",
+     project = "null",
+     applyautoclean = TRUE
+   )

indicator_processing/automated_download/cruise_air_visitors.R

@@ -126,31 +126,36 @@ print(USVI_air)
 
 
 
+
 ##########
 
 all_years <- data.frame(Year = min(PR_cruise$Year, USVI_cruise$Year) : max(PR_cruise$Year, USVI_cruise$Year))
 
 # Merge the data frames with the complete data frame to fill in missing years with NA
 combined_df <- merge(all_years, PR_cruise, by = "Year", all.x = TRUE)
 combined_df <- merge(combined_df, USVI_cruise, by = "Year", all.x = TRUE)
+combined_df <- merge(combined_df, PR_air, by = "Year", all.x = TRUE)
+combined_df <- merge(combined_df, USVI_air, by = "Year", all.x = TRUE)
 
 
 
 
 # save as indicator object ----------------------
 datdata <- all_years$Year
-inddata <- data.frame(cbind(combined_df$Cruise_passengers.x, combined_df$Cruise_passengers.y))
+inddata <- data.frame(cbind(combined_df$Cruise_passengers.x, combined_df$Cruise_passengers.y, combined_df$Air_passengers.x, combined_df$Air_passengers.y))
 labs <- c("Cruise passengers" , "thousands of people", "Puerto Rico",
-          "Cruise passengers" , "thousands of people", "USVI")
+          "Cruise passengers" , "thousands of people", "USVI",
+          "Air passengers" , "thousands of people", "Puerto Rico",
+          "Air passengers" , "thousands of people", "USVI")
 indnames <- data.frame(matrix(labs, nrow = 3, byrow = F))
 inddata <- list(labels = indnames, indicators = inddata, datelist = datdata)
 class(inddata) <- "indicatordata"
 
 # plot and save ----------------------------------
 
 ind <- inddata
-plotIndicatorTimeSeries(ind, coltoplot = 1:2, plotrownum = 2, plotcolnum = 1, trendAnalysis = TRUE, dateformat = "%b%Y", sublabel = TRUE, widadj = 1, hgtadj = 0.7, anom = "none", yposadj = 1)
+plotIndicatorTimeSeries(ind, coltoplot = 1:4, plotrownum = 2, plotcolnum = 2, trendAnalysis = TRUE, dateformat = "%b%Y", sublabel = TRUE, widadj = 1, hgtadj = 0.7, anom = "none", yposadj = 1)
 
-save(ind, file = "indicator_objects/cruise.RData")
+save(ind, file = "indicator_objects/cruise_air_visitors.RData")
 
 ###############################  END  #############################