Shiny app for exploring census and electorate data

launch_app(
  election_year = 2016,
  age = c("Age00_04", "Age05_14", "Age15_19", "Age20_24", "Age25_34", "Age35_44",
    "Age45_54", "Age55_64", "Age65_74", "Age75_84", "Age85plus"),
  religion = c("Christianity", "Catholic", "Buddhism", "Islam", "Judaism", "NoReligion"),
  other = c("AusCitizen", "MedianPersonalIncome", "Unemployed", "BachelorAbv",
    "Indigenous", "EnglishOnly", "OtherLanguageHome", "Married", "DeFacto",
    "FamilyRatio", "Owned"),
  palette = c("#1B9E77", "#F0027F", "#E6AB02", "#66A61E", "#7570B3", "#D95F02",
    "#3690C0")
)

Arguments

election_year: Year of Federal election to be explored (2001, 2004, 2007, 2010, 2013, 2016, 2019, 2022)
age: Age variables to show. Variable(s) should match column names from abs2016. By default, all variables are shown.
religion: Religion variables to show. Variable(s) should match column names from abs2016. By default, all variables are shown.
other: Other census variables to show. Variable(s) should match column names from abs2016. By default, all variables are shown.
palette: a named character vector of selection colors. The vector names are used as the display in the drop-down control.

Author

Carson Sievert

Examples

if (FALSE) {
library(shiny)
library(plotly)
library(tidyverse)
# for comparing labor/liberal
launch_app(
  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 = 2022,
  age = c("Age25_34", "Age35_44", "Age55_64"),
  religion = c("Christianity", "Catholic", "NoReligion"),
  other = c("Owned", "Indigenous", "AusCitizen")
)

launch_app()

}