/
pyramid-plot.R
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pyramid-plot.R
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# clean environment
remove(list = ls())
# required packages
library(ggplot2)
library(ggrepel)
library(zoo)
library(lme4)
library(plyr)
library(dplyr)
library(scales)
library(ggpubr)
library(grid)
library(gridExtra)
library(magrittr)
library(ggpol)
library(reshape2)
library(XML)
library(patchwork)
# import data
dat_all <- read.csv("https://epistat.sciensano.be/Data/COVID19BE_CASES_AGESEX.csv",
stringsAsFactors = TRUE
)
dat_all$DATE <- as.Date(dat_all$DATE, "%Y-%m-%d")
## Recoding dat_all$SEX into dat_all$SEX_rec
dat_all$SEX <- recode_factor(dat_all$SEX,
"F" = "Female",
"M" = "Male"
)
# subset for period
start <- as.Date("2020-03-01")
end <- as.Date("2020-05-31")
dat <- subset(dat_all, DATE >= start & DATE <= end)
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# Create plots in engl
p1 <- ggplot(data = dat) +
geom_bar(aes(AGEGROUP, CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Female")
) +
geom_bar(aes(AGEGROUP, -CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Male")
) +
scale_y_continuous(
breaks = seq(-round_any(max(dat$CASES), 1000, f = ceiling), round_any(max(dat$CASES), 1000, f = ceiling), 2000),
labels = abs(seq(-round_any(max(dat$CASES), 1000, f = ceiling), round_any(max(dat$CASES), 1000, f = ceiling), 2000))
) +
coord_flip() +
theme_minimal() +
labs(
title = "COVID-19 cases in Belgium",
subtitle = paste0(format(start, format = "%d/%m/%Y"), " - ", format(end, format = "%d/%m/%Y")),
# caption = "Niko Speybroeck (@NikoSpeybroeck), Antoine Soetewey (@statsandr) \n Data: https://epistat.wiv-isp.be/covid/",
x = "Age group",
y = "Number of cases"
) +
theme(
legend.position = c(.95, .15),
legend.justification = c("right", "top"),
legend.box.just = "right",
legend.margin = margin(6, 6, 6, 6),
legend.title = element_blank(),
plot.title = element_text(face = "bold"),
plot.subtitle = element_text(face = "bold")
)
p1
# subset for period
start <- as.Date("2020-06-01")
end <- as.Date("2020-08-31")
dat <- subset(dat_all, DATE >= start & DATE <= end)
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# Create plots in engl
p2 <- ggplot(data = dat) +
geom_bar(aes(AGEGROUP, CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Female")
) +
geom_bar(aes(AGEGROUP, -CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Male")
) +
scale_y_continuous(
breaks = seq(-round_any(max(dat$CASES), 1000, f = ceiling), round_any(max(dat$CASES), 1000, f = ceiling), 1000),
labels = abs(seq(-round_any(max(dat$CASES), 1000, f = ceiling), round_any(max(dat$CASES), 1000, f = ceiling), 1000))
) +
coord_flip() +
theme_minimal() +
labs( # title = "COVID-19 cases in Belgium",
subtitle = paste0(format(start, format = "%d/%m/%Y"), " - ", format(end, format = "%d/%m/%Y")),
# caption = "Niko Speybroeck (@NikoSpeybroeck), Antoine Soetewey (@statsandr) \n Data: https://epistat.wiv-isp.be/covid/",
x = "",
y = "Number of cases"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
p2
# subset for period
start <- as.Date("2020-09-01")
end <- as.Date(max(dat_all$DATE, na.rm = TRUE))
dat <- subset(dat_all, DATE >= start & DATE <= end)
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# Create plots in engl
p3 <- ggplot(data = dat) +
geom_bar(aes(AGEGROUP, CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Female")
) +
geom_bar(aes(AGEGROUP, -CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Male")
) +
scale_y_continuous(
breaks = seq(-round_any(max(dat$CASES), 100, f = ceiling), round_any(max(dat$CASES), 100, f = ceiling), 1000),
labels = abs(seq(-round_any(max(dat$CASES), 100, f = ceiling), round_any(max(dat$CASES), 100, f = ceiling), 1000))
) +
coord_flip() +
theme_minimal() +
labs( # title = "COVID-19 cases in Belgium",
subtitle = paste0(format(start, format = "%d/%m/%Y"), " - ", format(end, format = "%d/%m/%Y")),
caption = "Niko Speybroeck (@NikoSpeybroeck), Antoine Soetewey (@statsandr) \n Data: https://epistat.wiv-isp.be/covid/",
x = "",
y = "Number of cases"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
p3
p1 + p2 + p3
# save plot
ggsave("pyramid-plot.png")
# ggsave("pyramid-plot.pdf")