dev/journee_scientifique_graphics.R
In epicentre-msf/covid19: Epidemiological covid-19 analysis and visualisation
library(tidyverse)
library(gt)
library(sf)
pkgload::load_all()
# setup =========================================================================================
Sys.setlocale("LC_TIME", "fr_FR.UTF-8")
font <- "IBM Plex Sans" # change this to a font you have on your system
caption <- "Data source: European Centre for Disease Prevention and Control | Graphic: Epicentre"
ggplot2::theme_set(theme_light(base_size = 21, base_family = font))
export_dir <- "~/Downloads"
frmt_num <- function(x, accuracy = 1) {
scales::label_number_si(accuracy = accuracy)(x)
}
# data =========================================================================================
df_covid <- df_ecdc %>%
filter(date <= epivis::get_prev_sunday(Sys.Date()-1)) %>%
filter(country %in% c("Burkina Faso", "Niger", "Mauritania", "Chad", "Mali")) %>%
mutate(country = recode(country, "Mauritania" = "Mauritanie", "Chad" = "Tchad"))
df_events <- df_interventions %>% filter(country %in% c("Burkina Faso", "Niger", "Mauritania", "Chad", "Mali"))
sf_sahel <- sf_world %>%
filter(country %in% c("Burkina Faso", "Niger", "Mauritania", "Chad", "Mali")) %>%
mutate(country = recode(country, "Mauritania" = "Mauritanie", "Chad" = "Tchad"))
# Table ==============================================================================
df_covid %>%
group_by(country) %>%
summarise(cases = sum(cases), deaths = sum(deaths)) %>%
mutate(cfr = deaths / cases) %>%
left_join(st_drop_geometry(sf_sahel) %>% select(country, pop_est)) %>%
mutate(cas_100k = (cases / pop_est) * 100000) %>%
select(-pop_est) %>%
gather(key = "key", value = "value", cases:cas_100k) %>%
spread(country, value) %>%
mutate(key = factor(key, levels = c("cases", "deaths", "cfr", "cas_100k"), labels = c("Cas", "Décès", "Mortalité", "Cas par 100 000"))) %>%
arrange(key) %>%
gt::gt(rowname_col = "key") %>%
fmt_number(columns = 2:6, rows = c(1, 2), sep_mark = " ", decimals = 0) %>%
fmt_number(columns = 2:6, rows = c(4), sep_mark = " ", decimals = 1) %>%
fmt_percent(columns = 2:6, rows = c(3), decimals = 1)
# Map ==============================================================================
df_map <- df_covid %>%
group_by(country) %>%
summarise(cases = sum(cases, na.rm = TRUE), deaths = sum(deaths, na.rm = TRUE)) %>%
ungroup() %>%
inner_join(sf_sahel) %>%
sf::st_as_sf()
p_map_cases <- ggplot(df_map) +
geom_sf(fill = "#BED2C0", alpha = 0.7) +
geom_point(aes(lon, lat, size = cases), fill = "steelblue", alpha = 0.8, shape = 21, colour = "black") +
scale_size_area(max_size = 50) +
geom_sf_label(aes(label = country), nudge_y = 2, fontface = "bold", family = font) +
geom_text(aes(lon, lat, label = frmt_num(cases, .1)), colour = "white", fontface = "bold", family = font, size = 7) +
coord_sf(datum = NA) +
theme_minimal(base_size = 16, base_family = font) +
labs(x = NULL, y = NULL, size = "Cas") + #, caption = caption
theme(legend.position = "none", plot.caption = element_text(face = "italic", size = 10)) +
#theme(legend.position = c(0.55, .9)) +
guides(
size = guide_legend(nrow = 1, label.position = "bottom", title.position = "left")
)
ggsave(fs::path(export_dir, "map_cases", ext = "png"),
plot = p_map_cases,
width = 10,
height = 6,
dpi = 320)
p_map_deaths <- ggplot(df_map) +
geom_sf(fill = "#DFA599", alpha = 0.7) +
geom_point(aes(lon, lat, size = deaths), fill = "steelblue", alpha = 0.8, shape = 21, colour = "black") +
scale_size_area(max_size = 30) +
geom_sf_label(aes(label = country), nudge_y = 2, fontface = "bold", family = font) +
geom_text(aes(lon, lat, label = frmt_num(deaths)), colour = "white", fontface = "bold", family = font, size = 8) +
coord_sf(datum = NA) +
theme_minimal(base_size = 16, base_family = font) +
labs(x = NULL, y = NULL, size = "Décès", title = "") + #caption = caption,
theme(legend.position = "none", plot.caption = element_text(face = "italic", size = 10), ) +
#theme(legend.position = c(0.55, .9)) +
guides(
size = guide_legend(nrow = 1, label.position = "bottom", title.position = "left")
)
ggsave(fs::path(export_dir, "map_deaths", ext = "png"),
plot = p_map_deaths,
width = 10,
height = 6,
dpi = 320)
# Epicurves ==============================================================================
df_weekly <- df_covid %>%
mutate(week_date = lubridate::floor_date(date, "week", week_start = 1)) %>%
group_by(week_date, country) %>%
summarise(cases = sum(cases, na.rm = TRUE), deaths = sum(deaths, na.rm = TRUE)) %>%
ungroup()
df_totals <- df_covid %>%
summarise(cases = sum(cases, na.rm = TRUE), deaths = sum(deaths, na.rm = TRUE))
date_weeks <- epivis::floor_week(df_covid$date)
date_breaks <- seq.Date(range(df_covid$date)[1], range(date_weeks)[2], length.out = 5)
p_weekly_cases <- ggplot(df_weekly, aes(week_date, cases, group = country)) +
geom_col(aes(fill = country), colour = "white", size = 0.3) +
annotate(
"text",
x = min(df_weekly$week_date) + 32,
y = 1175,
label = glue::glue("Cas Total: {scales::number(df_totals$cases)}"),
fontface = "bold", family = font, size = 7
) +
ggthemes::scale_fill_tableau(name = NULL) +
scale_x_date("Semaine", date_breaks = "2 weeks", date_labels = "%V",
sec.axis = sec_axis(trans = ~ ., breaks = date_breaks, labels = scales::date_format("%d-%b")),
expand = expansion(mult = c(0.02, 0.02))) +
scale_y_continuous("Cas", labels = scales::number_format(accuracy = 1), expand = expansion(mult = c(0, 0.02))) +
#labs(title = "Cas") +
theme(
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
strip.text = element_text(colour = "black", face = "bold"),
plot.caption = element_text(face = "italic", size = 10),
legend.position = "top",
axis.text = element_text(size = 18, face = "bold", family = font),
legend.text = element_text(size = 25, face = "bold", family = font)
)
p_weekly_deaths <- ggplot(df_weekly, aes(week_date, deaths, group = country)) +
geom_col(aes(fill = country), colour = "white", size = 0.3) +
annotate(
"text",
x = min(df_weekly$week_date) + 32,
y = 53,
label = glue::glue("Décès Total: {scales::number(df_totals$deaths)}"),
fontface = "bold", family = font, size = 7
) +
ggthemes::scale_fill_tableau(name = NULL) +
scale_x_date("Semaine", date_breaks = "2 weeks", date_labels = "%V",
sec.axis = sec_axis(trans = ~ ., breaks = date_breaks, labels = scales::date_format("%d-%b")),
expand = expansion(mult = c(0.02, 0.02))) +
scale_y_continuous("Décès", labels = scales::number_format(accuracy = 1), expand = expansion(mult = c(0, 0.05))) +
#labs(title = "Décès") +
theme(
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
strip.text = element_text(colour = "black", face = "bold"),
plot.caption = element_text(face = "italic", size = 10),
legend.position = "top",
axis.text = element_text(size = 18, face = "bold", family = font),
legend.text = element_text(size = 25, face = "bold", family = font)
)
library(patchwork)
combined_curves <- p_weekly_cases + p_weekly_deaths + plot_layout(guides = 'collect', ncol = 2)
combined_all <- p_weekly_cases +
p_weekly_deaths +
p_map_cases +
p_map_deaths +
plot_layout(guides = 'collect', ncol = 2, heights = c(.4, .6)) +
plot_annotation(theme = theme(legend.position = "top", legend.direction = "horizontal"))
ggsave(fs::path(export_dir, "epicurves", ext = "svg"),
plot = combined_curves,
width = 18,
height = 5,
scale = 1.1,
dpi = 320)
ggsave(fs::path(export_dir, "weekly_cases", ext = "png"),
plot = p_weekly_cases,
width = 10,
height = 6,
scale = 1.1,
dpi = 320)
ggsave(fs::path(export_dir, "weekly_deaths", ext = "png"),
plot = p_weekly_deaths,
width = 10,
height = 6,
scale = 1.1,
dpi = 320)
# Cumulative ==============================================================================
df_cumulative <- df_covid %>%
dplyr::group_by(country) %>%
dplyr::arrange(date) %>%
dplyr::mutate_at(dplyr::vars(cases, deaths), cumsum) %>%
dplyr::ungroup()
df_cumulative_cases <- df_cumulative %>%
select(country, cases) %>%
dplyr::group_by(country) %>%
tidyr::drop_na(cases) %>%
dplyr::filter(cases >= 100) %>%
dplyr::mutate(days_100_cases = seq_along(cases)-1) %>%
mutate(label = if_else(days_100_cases == max(days_100_cases), country, NA_character_)) %>%
dplyr::ungroup()
p_cumulative_cases <- ggplot(df_cumulative_cases, aes(days_100_cases, cases, group = country, colour = country)) +
geom_line(aes(colour = country), size = .8, show.legend = FALSE) +
ggthemes::scale_colour_tableau() +
scale_y_continuous("Cas (log scale)", trans = "log10") +
ggrepel::geom_label_repel(aes(label = label), nudge_x = 1, na.rm = TRUE) +
theme(legend.position = "none", plot.caption = element_text(face = "italic", size = 10)) +
labs(x = "Jours depuis les 100 premiers cas", caption = caption)
ggsave(fs::path(export_dir, "cumulative_cases", ext = "png"),
plot = p_cumulative_cases,
width = 10,
height = 6,
scale = 1.1,
dpi = 320)
df_cumulative_deaths <- df_cumulative %>%
select(country, deaths) %>%
dplyr::group_by(country) %>%
tidyr::drop_na(deaths) %>%
dplyr::filter(deaths >= 10) %>%
dplyr::mutate(days_10_death = seq_along(deaths)-1) %>%
mutate(label = if_else(days_10_death == max(days_10_death), country, NA_character_)) %>%
dplyr::ungroup()
p_cumulative_deaths <- ggplot(df_cumulative_deaths, aes(days_10_death, deaths, group = country, colour = country)) +
geom_line(aes(colour = country), size = .8, show.legend = FALSE) +
ggthemes::scale_colour_tableau() +
scale_y_continuous("Décès (log scale)", trans = "log10") +
ggrepel::geom_label_repel(aes(label = label), nudge_x = 1, na.rm = TRUE, ) +
theme(legend.position = "none", plot.caption = element_text(face = "italic", size = 10)) +
labs(x = "Jours depuis les 10 premiers décès", caption = caption)
ggsave(fs::path(export_dir, "cumulative_deaths", ext = "png"),
plot = p_cumulative_deaths,
width = 10,
height = 6,
scale = 1.1,
dpi = 320)
# Experimental cumulative cases chart with events ===========================================
df_measures <- df_events %>%
select(date = date_implemented, country, category, measure) %>%
left_join(select(df_cumulative, date, country, cases)) %>%
replace_na(list(cases = 0))
ggplot(df_cumulative, aes(date, cases, group = country)) + #
geom_line(aes(colour = country)) +
geom_point(data = df_measures, aes(date, cases, shape = category))
#scale_y_continuous("Cas (log scale)", trans = "log10")
#ggrepel::geom_text_repel(data = df_measures %>% filter(country == "Mali"), aes(label = measure))
# facet plots - not being used ================================================
ggplot(df_covid, aes(week_date, cases)) +
facet_wrap(~country, scales = "free_y", ncol = 1, strip.position = "right") +
geom_col(aes(fill = country), show.legend = FALSE) +
ggthemes::scale_fill_tableau() +
scale_x_date("Semaine", date_breaks = "2 weeks", date_labels = "%V", sec.axis = sec_axis(trans = ~ .)) +
scale_y_continuous("Deaths", labels = scales::number_format(accuracy = 1)) +
theme(panel.grid.major.x = element_blank(), panel.grid.minor.x = element_blank(), strip.text = element_text(colour = "black", face = "bold")) +
labs(caption = "Note free y scales")
ggplot(df_covid, aes(week_date, deaths)) +
facet_wrap(~country, scales = "free_y", ncol = 1, strip.position = "right") +
geom_col(aes(fill = country), show.legend = FALSE) +
ggthemes::scale_fill_tableau() +
scale_x_date("Semaine", date_breaks = "2 weeks", date_labels = "%V", sec.axis = sec_axis(trans = ~ .)) +
scale_y_continuous("Deaths", labels = scales::number_format(accuracy = 1)) +
theme(panel.grid.major.x = element_blank(), panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
strip.text = element_text(colour = "black", face = "bold")) +
labs(caption = "Note free y scales")
epicentre-msf/covid19 documentation built on April 5, 2023, 10:24 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
library(tidyverse)
library(gt)
library(sf)
pkgload::load_all()
# setup =========================================================================================
Sys.setlocale("LC_TIME", "fr_FR.UTF-8")
font <- "IBM Plex Sans" # change this to a font you have on your system
caption <- "Data source: European Centre for Disease Prevention and Control | Graphic: Epicentre"
ggplot2::theme_set(theme_light(base_size = 21, base_family = font))
export_dir <- "~/Downloads"
frmt_num <- function(x, accuracy = 1) {
scales::label_number_si(accuracy = accuracy)(x)
}
# data =========================================================================================
df_covid <- df_ecdc %>%
filter(date <= epivis::get_prev_sunday(Sys.Date()-1)) %>%
filter(country %in% c("Burkina Faso", "Niger", "Mauritania", "Chad", "Mali")) %>%
mutate(country = recode(country, "Mauritania" = "Mauritanie", "Chad" = "Tchad"))
df_events <- df_interventions %>% filter(country %in% c("Burkina Faso", "Niger", "Mauritania", "Chad", "Mali"))
sf_sahel <- sf_world %>%
filter(country %in% c("Burkina Faso", "Niger", "Mauritania", "Chad", "Mali")) %>%
mutate(country = recode(country, "Mauritania" = "Mauritanie", "Chad" = "Tchad"))
# Table ==============================================================================
df_covid %>%
group_by(country) %>%
summarise(cases = sum(cases), deaths = sum(deaths)) %>%
mutate(cfr = deaths / cases) %>%
left_join(st_drop_geometry(sf_sahel) %>% select(country, pop_est)) %>%
mutate(cas_100k = (cases / pop_est) * 100000) %>%
select(-pop_est) %>%
gather(key = "key", value = "value", cases:cas_100k) %>%
spread(country, value) %>%
mutate(key = factor(key, levels = c("cases", "deaths", "cfr", "cas_100k"), labels = c("Cas", "Décès", "Mortalité", "Cas par 100 000"))) %>%
arrange(key) %>%
gt::gt(rowname_col = "key") %>%
fmt_number(columns = 2:6, rows = c(1, 2), sep_mark = " ", decimals = 0) %>%
fmt_number(columns = 2:6, rows = c(4), sep_mark = " ", decimals = 1) %>%
fmt_percent(columns = 2:6, rows = c(3), decimals = 1)
# Map ==============================================================================
df_map <- df_covid %>%
group_by(country) %>%
summarise(cases = sum(cases, na.rm = TRUE), deaths = sum(deaths, na.rm = TRUE)) %>%
ungroup() %>%
inner_join(sf_sahel) %>%
sf::st_as_sf()
p_map_cases <- ggplot(df_map) +
geom_sf(fill = "#BED2C0", alpha = 0.7) +
geom_point(aes(lon, lat, size = cases), fill = "steelblue", alpha = 0.8, shape = 21, colour = "black") +
scale_size_area(max_size = 50) +
geom_sf_label(aes(label = country), nudge_y = 2, fontface = "bold", family = font) +
geom_text(aes(lon, lat, label = frmt_num(cases, .1)), colour = "white", fontface = "bold", family = font, size = 7) +
coord_sf(datum = NA) +
theme_minimal(base_size = 16, base_family = font) +
labs(x = NULL, y = NULL, size = "Cas") + #, caption = caption
theme(legend.position = "none", plot.caption = element_text(face = "italic", size = 10)) +
#theme(legend.position = c(0.55, .9)) +
guides(
size = guide_legend(nrow = 1, label.position = "bottom", title.position = "left")
)
ggsave(fs::path(export_dir, "map_cases", ext = "png"),
plot = p_map_cases,
width = 10,
height = 6,
dpi = 320)
p_map_deaths <- ggplot(df_map) +
geom_sf(fill = "#DFA599", alpha = 0.7) +
geom_point(aes(lon, lat, size = deaths), fill = "steelblue", alpha = 0.8, shape = 21, colour = "black") +
scale_size_area(max_size = 30) +
geom_sf_label(aes(label = country), nudge_y = 2, fontface = "bold", family = font) +
geom_text(aes(lon, lat, label = frmt_num(deaths)), colour = "white", fontface = "bold", family = font, size = 8) +
coord_sf(datum = NA) +
theme_minimal(base_size = 16, base_family = font) +
labs(x = NULL, y = NULL, size = "Décès", title = "") + #caption = caption,
theme(legend.position = "none", plot.caption = element_text(face = "italic", size = 10), ) +
#theme(legend.position = c(0.55, .9)) +
guides(
size = guide_legend(nrow = 1, label.position = "bottom", title.position = "left")
)
ggsave(fs::path(export_dir, "map_deaths", ext = "png"),
plot = p_map_deaths,
width = 10,
height = 6,
dpi = 320)
# Epicurves ==============================================================================
df_weekly <- df_covid %>%
mutate(week_date = lubridate::floor_date(date, "week", week_start = 1)) %>%
group_by(week_date, country) %>%
summarise(cases = sum(cases, na.rm = TRUE), deaths = sum(deaths, na.rm = TRUE)) %>%
ungroup()
df_totals <- df_covid %>%
summarise(cases = sum(cases, na.rm = TRUE), deaths = sum(deaths, na.rm = TRUE))
date_weeks <- epivis::floor_week(df_covid$date)
date_breaks <- seq.Date(range(df_covid$date)[1], range(date_weeks)[2], length.out = 5)
p_weekly_cases <- ggplot(df_weekly, aes(week_date, cases, group = country)) +
geom_col(aes(fill = country), colour = "white", size = 0.3) +
annotate(
"text",
x = min(df_weekly$week_date) + 32,
y = 1175,
label = glue::glue("Cas Total: {scales::number(df_totals$cases)}"),
fontface = "bold", family = font, size = 7
) +
ggthemes::scale_fill_tableau(name = NULL) +
scale_x_date("Semaine", date_breaks = "2 weeks", date_labels = "%V",
sec.axis = sec_axis(trans = ~ ., breaks = date_breaks, labels = scales::date_format("%d-%b")),
expand = expansion(mult = c(0.02, 0.02))) +
scale_y_continuous("Cas", labels = scales::number_format(accuracy = 1), expand = expansion(mult = c(0, 0.02))) +
#labs(title = "Cas") +
theme(
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
strip.text = element_text(colour = "black", face = "bold"),
plot.caption = element_text(face = "italic", size = 10),
legend.position = "top",
axis.text = element_text(size = 18, face = "bold", family = font),
legend.text = element_text(size = 25, face = "bold", family = font)
)
p_weekly_deaths <- ggplot(df_weekly, aes(week_date, deaths, group = country)) +
geom_col(aes(fill = country), colour = "white", size = 0.3) +
annotate(
"text",
x = min(df_weekly$week_date) + 32,
y = 53,
label = glue::glue("Décès Total: {scales::number(df_totals$deaths)}"),
fontface = "bold", family = font, size = 7
) +
ggthemes::scale_fill_tableau(name = NULL) +
scale_x_date("Semaine", date_breaks = "2 weeks", date_labels = "%V",
sec.axis = sec_axis(trans = ~ ., breaks = date_breaks, labels = scales::date_format("%d-%b")),
expand = expansion(mult = c(0.02, 0.02))) +
scale_y_continuous("Décès", labels = scales::number_format(accuracy = 1), expand = expansion(mult = c(0, 0.05))) +
#labs(title = "Décès") +
theme(
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
strip.text = element_text(colour = "black", face = "bold"),
plot.caption = element_text(face = "italic", size = 10),
legend.position = "top",
axis.text = element_text(size = 18, face = "bold", family = font),
legend.text = element_text(size = 25, face = "bold", family = font)
)
library(patchwork)
combined_curves <- p_weekly_cases + p_weekly_deaths + plot_layout(guides = 'collect', ncol = 2)
combined_all <- p_weekly_cases +
p_weekly_deaths +
p_map_cases +
p_map_deaths +
plot_layout(guides = 'collect', ncol = 2, heights = c(.4, .6)) +
plot_annotation(theme = theme(legend.position = "top", legend.direction = "horizontal"))
ggsave(fs::path(export_dir, "epicurves", ext = "svg"),
plot = combined_curves,
width = 18,
height = 5,
scale = 1.1,
dpi = 320)
ggsave(fs::path(export_dir, "weekly_cases", ext = "png"),
plot = p_weekly_cases,
width = 10,
height = 6,
scale = 1.1,
dpi = 320)
ggsave(fs::path(export_dir, "weekly_deaths", ext = "png"),
plot = p_weekly_deaths,
width = 10,
height = 6,
scale = 1.1,
dpi = 320)
# Cumulative ==============================================================================
df_cumulative <- df_covid %>%
dplyr::group_by(country) %>%
dplyr::arrange(date) %>%
dplyr::mutate_at(dplyr::vars(cases, deaths), cumsum) %>%
dplyr::ungroup()
df_cumulative_cases <- df_cumulative %>%
select(country, cases) %>%
dplyr::group_by(country) %>%
tidyr::drop_na(cases) %>%
dplyr::filter(cases >= 100) %>%
dplyr::mutate(days_100_cases = seq_along(cases)-1) %>%
mutate(label = if_else(days_100_cases == max(days_100_cases), country, NA_character_)) %>%
dplyr::ungroup()
p_cumulative_cases <- ggplot(df_cumulative_cases, aes(days_100_cases, cases, group = country, colour = country)) +
geom_line(aes(colour = country), size = .8, show.legend = FALSE) +
ggthemes::scale_colour_tableau() +
scale_y_continuous("Cas (log scale)", trans = "log10") +
ggrepel::geom_label_repel(aes(label = label), nudge_x = 1, na.rm = TRUE) +
theme(legend.position = "none", plot.caption = element_text(face = "italic", size = 10)) +
labs(x = "Jours depuis les 100 premiers cas", caption = caption)
ggsave(fs::path(export_dir, "cumulative_cases", ext = "png"),
plot = p_cumulative_cases,
width = 10,
height = 6,
scale = 1.1,
dpi = 320)
df_cumulative_deaths <- df_cumulative %>%
select(country, deaths) %>%
dplyr::group_by(country) %>%
tidyr::drop_na(deaths) %>%
dplyr::filter(deaths >= 10) %>%
dplyr::mutate(days_10_death = seq_along(deaths)-1) %>%
mutate(label = if_else(days_10_death == max(days_10_death), country, NA_character_)) %>%
dplyr::ungroup()
p_cumulative_deaths <- ggplot(df_cumulative_deaths, aes(days_10_death, deaths, group = country, colour = country)) +
geom_line(aes(colour = country), size = .8, show.legend = FALSE) +
ggthemes::scale_colour_tableau() +
scale_y_continuous("Décès (log scale)", trans = "log10") +
ggrepel::geom_label_repel(aes(label = label), nudge_x = 1, na.rm = TRUE, ) +
theme(legend.position = "none", plot.caption = element_text(face = "italic", size = 10)) +
labs(x = "Jours depuis les 10 premiers décès", caption = caption)
ggsave(fs::path(export_dir, "cumulative_deaths", ext = "png"),
plot = p_cumulative_deaths,
width = 10,
height = 6,
scale = 1.1,
dpi = 320)
# Experimental cumulative cases chart with events ===========================================
df_measures <- df_events %>%
select(date = date_implemented, country, category, measure) %>%
left_join(select(df_cumulative, date, country, cases)) %>%
replace_na(list(cases = 0))
ggplot(df_cumulative, aes(date, cases, group = country)) + #
geom_line(aes(colour = country)) +
geom_point(data = df_measures, aes(date, cases, shape = category))
#scale_y_continuous("Cas (log scale)", trans = "log10")
#ggrepel::geom_text_repel(data = df_measures %>% filter(country == "Mali"), aes(label = measure))
# facet plots - not being used ================================================
ggplot(df_covid, aes(week_date, cases)) +
facet_wrap(~country, scales = "free_y", ncol = 1, strip.position = "right") +
geom_col(aes(fill = country), show.legend = FALSE) +
ggthemes::scale_fill_tableau() +
scale_x_date("Semaine", date_breaks = "2 weeks", date_labels = "%V", sec.axis = sec_axis(trans = ~ .)) +
scale_y_continuous("Deaths", labels = scales::number_format(accuracy = 1)) +
theme(panel.grid.major.x = element_blank(), panel.grid.minor.x = element_blank(), strip.text = element_text(colour = "black", face = "bold")) +
labs(caption = "Note free y scales")
ggplot(df_covid, aes(week_date, deaths)) +
facet_wrap(~country, scales = "free_y", ncol = 1, strip.position = "right") +
geom_col(aes(fill = country), show.legend = FALSE) +
ggthemes::scale_fill_tableau() +
scale_x_date("Semaine", date_breaks = "2 weeks", date_labels = "%V", sec.axis = sec_axis(trans = ~ .)) +
scale_y_continuous("Deaths", labels = scales::number_format(accuracy = 1)) +
theme(panel.grid.major.x = element_blank(), panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
strip.text = element_text(colour = "black", face = "bold")) +
labs(caption = "Note free y scales")
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