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pyramid-plot-week-divid.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)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# create limits for number of cases for all periods
limit <- 8000
lower_limit <- -limit
upper_limit <- limit
breaks <- 2000
# 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(
limits = c(lower_limit, upper_limit),
breaks = seq(lower_limit, upper_limit, breaks),
labels = abs(seq(lower_limit, upper_limit, breaks))
) +
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 per week"
) +
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)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# 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(
limits = c(lower_limit, upper_limit),
breaks = seq(lower_limit, upper_limit, breaks),
labels = abs(seq(lower_limit, upper_limit, breaks))
) +
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 per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
p2
# subset for period
start <- as.Date("2020-09-01")
end <- as.Date("2020-09-30")
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# 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(
limits = c(lower_limit, upper_limit),
breaks = seq(lower_limit, upper_limit, breaks),
labels = abs(seq(lower_limit, upper_limit, breaks))
) +
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 per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
p3
# subset for period
start <- as.Date("2020-10-01")
end <- as.Date("2020-10-31")
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# Create plots in engl
p4 <- 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(
limits = c(lower_limit, upper_limit),
breaks = seq(lower_limit, upper_limit, breaks),
labels = abs(seq(lower_limit, upper_limit, breaks))
) +
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 per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
p4
# subset for period
start <- as.Date("2020-11-01")
end <- as.Date("2020-12-31")
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# Create plots in engl
p5 <- 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(
limits = c(lower_limit, upper_limit),
breaks = seq(lower_limit, upper_limit, breaks),
labels = abs(seq(lower_limit, upper_limit, breaks))
) +
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 per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
p5
# subset for period
start <- as.Date("2021-01-01")
end <- as.Date(max(dat_all$DATE, na.rm = TRUE))
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# Create plots in engl
p6 <- 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(
limits = c(lower_limit, upper_limit),
breaks = seq(lower_limit, upper_limit, breaks),
labels = abs(seq(lower_limit, upper_limit, breaks))
) +
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 per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
p6
p <- p6 + p4 / p5
p
# save plot
png(file = "pyramid-plot-week-limit2.png", width = 15 * 360, heigh = 7 * 360, units = "px", pointsize = 7, res = 300)
p
dev.off()
# subset for period
start <- as.Date("2020-03-01")
end <- as.Date("2020-05-31")
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# 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(
# limits = c(lower_limit, upper_limit),
# breaks = seq(lower_limit, upper_limit, breaks),
# labels = abs(seq(lower_limit, upper_limit, breaks))
# ) +
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 per week"
) +
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")
)
# subset for period
start <- as.Date("2020-06-01")
end <- as.Date("2020-08-31")
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# Create plots in engl
p2 <- ggplot(data = dat) +
geom_bar(aes(AGEGROUP, CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Female")
) +
geom_bar(aes(AGEGROUP, -CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Male")
) +
# scale_y_continuous(
# limits = c(lower_limit, upper_limit),
# breaks = seq(lower_limit, upper_limit, breaks),
# labels = abs(seq(lower_limit, upper_limit, breaks))
# ) +
coord_flip() +
theme_minimal() +
labs( # title = "COVID-19 cases in Belgium",
subtitle = paste0(format(start, format = "%d/%m/%Y"), " - ", format(end, format = "%d/%m/%Y")),
# caption = "Niko Speybroeck (@NikoSpeybroeck), Antoine Soetewey (@statsandr) \n Data: https://epistat.wiv-isp.be/covid/",
x = "Age group",
y = "Number of cases per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
# subset for period
start <- as.Date("2020-09-01")
end <- as.Date("2020-09-30")
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# Create plots in engl
p3 <- ggplot(data = dat) +
geom_bar(aes(AGEGROUP, CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Female")
) +
geom_bar(aes(AGEGROUP, -CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Male")
) +
# scale_y_continuous(
# limits = c(lower_limit, upper_limit),
# breaks = seq(lower_limit, upper_limit, breaks),
# labels = abs(seq(lower_limit, upper_limit, breaks))
# ) +
coord_flip() +
theme_minimal() +
labs( # title = "COVID-19 cases in Belgium",
subtitle = paste0(format(start, format = "%d/%m/%Y"), " - ", format(end, format = "%d/%m/%Y")),
# caption = "Niko Speybroeck (@NikoSpeybroeck), Antoine Soetewey (@statsandr) \n Data: https://epistat.wiv-isp.be/covid/",
x = "Age group",
y = "Number of cases per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
# subset for period
start <- as.Date("2020-10-01")
end <- as.Date("2020-10-31")
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# Create plots in engl
p4 <- ggplot(data = dat) +
geom_bar(aes(AGEGROUP, CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Female")
) +
geom_bar(aes(AGEGROUP, -CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Male")
) +
# scale_y_continuous(
# limits = c(lower_limit, upper_limit),
# breaks = seq(lower_limit, upper_limit, breaks),
# labels = abs(seq(lower_limit, upper_limit, breaks))
# ) +
coord_flip() +
theme_minimal() +
labs( # title = "COVID-19 cases in Belgium",
subtitle = paste0(format(start, format = "%d/%m/%Y"), " - ", format(end, format = "%d/%m/%Y")),
# caption = "Niko Speybroeck (@NikoSpeybroeck), Antoine Soetewey (@statsandr) \n Data: https://epistat.wiv-isp.be/covid/",
x = "Age group",
y = "Number of cases per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
# subset for period
start <- as.Date("2020-11-01")
end <- as.Date("2020-12-31")
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# Create plots in engl
p5 <- ggplot(data = dat) +
geom_bar(aes(AGEGROUP, CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Female")
) +
geom_bar(aes(AGEGROUP, -CASES, group = SEX, fill = SEX),
stat = "identity",
subset(dat, SEX == "Male")
) +
# scale_y_continuous(
# limits = c(lower_limit, upper_limit),
# breaks = seq(lower_limit, upper_limit, breaks),
# labels = abs(seq(lower_limit, upper_limit, breaks))
# ) +
coord_flip() +
theme_minimal() +
labs( # title = "COVID-19 cases in Belgium",
subtitle = paste0(format(start, format = "%d/%m/%Y"), " - ", format(end, format = "%d/%m/%Y")),
# caption = "Niko Speybroeck (@NikoSpeybroeck), Antoine Soetewey (@statsandr) \n Data: https://epistat.wiv-isp.be/covid/",
x = "Age group",
y = "Number of cases per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
# subset for period
start <- as.Date("2021-01-01")
end <- as.Date(max(dat_all$DATE, na.rm = TRUE))
dat <- subset(dat_all, DATE >= start & DATE <= end)
nweeks <- as.numeric(end - start) / 7
# aggregate new cases by province and date
dat <- aggregate(CASES ~ AGEGROUP + SEX, dat, sum)
# cases per week
dat$CASES <- dat$CASES / nweeks
# Create plots in engl
p6 <- 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(
# limits = c(lower_limit, upper_limit),
# breaks = seq(lower_limit, upper_limit, breaks),
# labels = abs(seq(lower_limit, upper_limit, breaks))
# ) +
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 per week"
) +
theme(
legend.position = "none",
plot.subtitle = element_text(face = "bold")
)
p <- p6 + p4 / p5
p
# save plot
png(file = "pyramid-plot-week-limit2bis.png", width = 15 * 360, heigh = 7 * 360, units = "px", pointsize = 7, res = 300)
p
dev.off()