launch_app | R Documentation |
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")
)
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. |
Carson Sievert
## Not run:
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()
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.