default year in app changed to 2022

jforbes14 · Apr 25, 2023 · d4cdb50 · d4cdb50
1 parent e580dd1
commit d4cdb50
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Showing 16 changed files with 49 additions and 43 deletions.
diff --git a/R/app.R b/R/app.R
@@ -1,6 +1,6 @@
 #' Shiny app for exploring census and electorate data
 #'
-#' @param election_year Year of Federal election to be explored (2001, 2004, 2007, 2010, 2013, 2016 or 2019)
+#' @param election_year Year of Federal election to be explored (2001, 2004, 2007, 2010, 2013, 2016, 2019, 2022)
 #' @param age Age variables to show. Variable(s) should match column names from
 #' \link{abs2016}. By default, all variables are shown.
 #' @param religion Religion variables to show. Variable(s) should match column
@@ -17,15 +17,15 @@
 #' library(tidyverse)
 #' # for comparing labor/liberal
 #' launch_app(
-#' election_year = 2019,
+#' election_year = 2022,
 #' age = c("Age20_24", "Age25_34", "Age55_64"),
 #' religion = c("Christianity", "Catholic", "NoReligion"),
 #' other = c("AusCitizen", "MedianPersonalIncome", "Unemployed")
 #' )
 #'
 #' # for inspecting highly contested areas
 #' launch_app(
-#' election_year = 2019,
+#' election_year = 2022,
 #' age = c("Age25_34", "Age35_44", "Age55_64"),
 #' religion = c("Christianity", "Catholic", "NoReligion"),
 #' other = c("Owned", "Indigenous", "AusCitizen")
@@ -48,8 +48,8 @@ launch_app <- function(
 ) {
  election_year = as.numeric(election_year)
 
- if (!as.numeric(election_year) %in% c(2001, 2004, 2007, 2010, 2013, 2016, 2019)) {
- warning("Election year enter is not valid. Year must be one of 2001, 2004, 2007, 2010, 2013 and 2016.
+ if (!as.numeric(election_year) %in% c(2001, 2004, 2007, 2010, 2013, 2016, 2019, 2022)) {
+ warning("Election year enter is not valid. Year must be one of 2001, 2004, 2007, 2010, 2013, 2016, 2019 and 2022.
  Using 2016 by default.")
  election_year = 2016
  }
@@ -98,6 +98,13 @@ launch_app <- function(
  nat_map <- nat_map_download(2019)
  abs_data <- as.data.frame(eechidna::abs2019)
  }
+ else if (election_year == 2022) {
+ fp_data <- as.data.frame(eechidna::fp22)
+ tcp_data <- as.data.frame(eechidna::tcp22)
+ nat_data <- nat_data_download(2019)
+ nat_map <- nat_map_download(2019)
+ abs_data <- as.data.frame(eechidna::abs2019)
+ }
 
  # by default, we show parties that won at least 1 electorate
  relevantParties <- fp_data %>%

diff --git a/man/launch_app.Rd b/man/launch_app.Rd
diff --git a/man/nat_data01.Rd b/man/nat_data01.Rd
diff --git a/man/nat_data04.Rd b/man/nat_data04.Rd
diff --git a/man/nat_data07.Rd b/man/nat_data07.Rd
diff --git a/man/nat_data10.Rd b/man/nat_data10.Rd
diff --git a/man/nat_data13.Rd b/man/nat_data13.Rd
diff --git a/man/nat_data16.Rd b/man/nat_data16.Rd
diff --git a/man/nat_data19.Rd b/man/nat_data19.Rd
diff --git a/man/nat_map01.Rd b/man/nat_map01.Rd
diff --git a/man/nat_map04.Rd b/man/nat_map04.Rd
diff --git a/man/nat_map07.Rd b/man/nat_map07.Rd
diff --git a/man/nat_map10.Rd b/man/nat_map10.Rd
diff --git a/man/nat_map13.Rd b/man/nat_map13.Rd
diff --git a/man/nat_map16.Rd b/man/nat_map16.Rd
diff --git a/man/nat_map19.Rd b/man/nat_map19.Rd