## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval = nzchar(Sys.getenv("COMPILE_VIG_CANPUMF")) ) ## ----setup-------------------------------------------------------------------- library(canpumf) library(dplyr) library(ggplot2) options(canpumf.cache_path = Sys.getenv("COMPILE_VIG_CANPUMF")) ## ----------------------------------------------------------------------------- census_2021 <- get_pumf("Census",version="2021") ## ----------------------------------------------------------------------------- census_2021 |> filter(CMA %in% c("Vancouver","Toronto","Montréal","Québec")) |> filter(PRIHM!="Not applicable") |> filter(AGEGRP!="Not available") |> summarise(across(matches("WEIGHT|WT\\d+"),sum), .by=c(CMA,AGEGRP,PRIHM)) |> mutate(Share=WEIGHT/sum(WEIGHT),.by=c(CMA,AGEGRP)) |> filter(PRIHM=="Person is primary maintainer") |> ggplot(aes(y=AGEGRP,x=Share,fill=CMA)) + geom_bar(stat="identity",position="dodge") + scale_x_continuous(labels=scales::percent) + labs(title="Age-specifc household maintainer rates", y="Age group", x="Household maintainer rate", caption="StatCan Census 2021 PUMF") ## ----------------------------------------------------------------------------- census_2021 |> filter(CMA %in% c("Vancouver","Toronto","Montréal","Québec")) |> filter(PRIHM!="Not applicable") |> filter(AGEGRP!="Not available") |> summarise(across(matches("WEIGHT|WT\\d+"),sum), .by=c(CMA,AGEGRP,PRIHM)) |> collect() |> tidyr::pivot_longer(matches("WT\\d+"),names_to="Weights") |> mutate(Share=WEIGHT/sum(WEIGHT), Share_bsw=value/sum(value), .by=c(CMA,AGEGRP,Weights)) |> filter(PRIHM=="Person is primary maintainer") |> ggplot(aes(y=AGEGRP,fill=CMA)) + geom_bar(aes(x=Share),stat="identity",position="dodge") + geom_boxplot(aes(x=Share_bsw, group=interaction(CMA,AGEGRP)), fill=NA,shape=1, position="dodge") + scale_x_continuous(labels=scales::percent) + labs(title="Age-specifc household maintainer rates", y="Age group", x="Household maintainer rate (and replication weight ranges)", caption="StatCan Census 2021 PUMF") ## ----------------------------------------------------------------------------- census_2021 |> filter(CMA %in% c("Vancouver","Toronto","Montréal","Québec")) |> filter(PRIHM!="Not applicable") |> filter(AGEGRP!="Not available") |> add_bootstrap_weights("WEIGHT") |> summarise(across(matches("WEIGHT|WT\\d+|CPBSW\\d+"),sum), .by=c(CMA,AGEGRP,PRIHM)) |> collect() |> tidyr::pivot_longer(matches("CPBSW\\d+"),names_to="Weights") |> mutate(Share=WEIGHT/sum(WEIGHT), Share_bsw=value/sum(value), .by=c(CMA,AGEGRP,Weights)) |> filter(PRIHM=="Person is primary maintainer") |> ggplot(aes(y=AGEGRP,fill=CMA)) + geom_bar(aes(x=Share),stat="identity",position="dodge") + geom_boxplot(aes(x=Share_bsw, group=interaction(CMA,AGEGRP)), fill=NA,shape=1, position="dodge") + scale_x_continuous(labels=scales::percent) + labs(title="Age-specifc household maintainer rates", y="Age group", x="Household maintainer rate (and bootstrap weight ranges)", caption="StatCan Census 2021 PUMF") ## ----------------------------------------------------------------------------- census_2021 |> close_pumf()