Resultados

library(tidyverse)
library(covdata)
library(ggrepel)
library(paletteer)
Sys.setlocale(category = "LC_ALL", locale = "English_United States.1252")
## [1] "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252"
## Countries to highlight
#focus_cn <- c("CHN", "DEU", "GBR", "USA", "JPN", "KOR", "ITA", "FRA", "ESP", "CHE", "BRA")
focus_cn <- c("CHN", "DEU", "GBR", "USA",  "ITA", "ESP", "BRA")

## Colors
cgroup_cols <- c(prismatic::clr_darken(paletteer_d("ggsci::category20_d3"), 0.2)[1:length(focus_cn)], "gray70")

covnat %>%
  filter(cu_cases > 100) %>%
  mutate(days_elapsed = date - min(date),
         end_label = ifelse(date == max(date), cname, NA),
         end_label = recode(end_label, `United States` = "USA",
                            `Iran, Islamic Republic of` = "Iran",
                            `Korea, Republic of` = "South Korea",
                            `United Kingdom` = "UK"),
         cname = recode(cname, `United States` = "USA",
                        `Iran, Islamic Republic of` = "Iran",
                        `Korea, Republic of` = "South Korea",
                        `United Kingdom` = "UK"),
         end_label = case_when(iso3 %in% focus_cn ~ end_label,
                               TRUE ~ NA_character_),
         cgroup = case_when(iso3 %in% focus_cn ~ iso3,
                            FALSE ~ "ZZOTHER")) %>%
  ggplot(mapping = aes(x = days_elapsed, y = cu_cases,
                       color = cgroup, label = end_label,
                       group = cname)) +
  geom_line(size = 0.5) +
  geom_text_repel(nudge_x = 0.75,
                  segment.color = NA) +
  guides(color = FALSE) +
  scale_color_manual(values = cgroup_cols) +
  scale_y_continuous(labels = scales::comma_format(accuracy = 1),
                     breaks = 2^seq(4, 19, 1),
                     trans = "log2") +
  labs(x = "Days Since 100th Confirmed Case",
       y = "Cumulative Number of Reported Cases (log2 scale)",
       title = "Cumulative Reported Cases of COVID-19",
       subtitle = paste("ECDC data as of", format(max(covnat$date), "%A, %B %e, %Y")),
       caption = "Cid PĆ³voas / Data: https://www.ecdc.europa.eu/") +
  theme_classic()

covnat %>%
  filter(cu_cases > 100) %>%
  mutate(days_elapsed = date - min(date),
         end_label = ifelse(date == max(date), cname, NA),
         end_label = recode(end_label, `United States` = "USA",
                            `Iran, Islamic Republic of` = "Iran",
                            `Korea, Republic of` = "South Korea",
                            `United Kingdom` = "UK"),
         cname = recode(cname, `United States` = "USA",
                        `Iran, Islamic Republic of` = "Iran",
                        `Korea, Republic of` = "South Korea",
                        `United Kingdom` = "UK"),
         end_label = case_when(iso3 %in% focus_cn ~ end_label,
                               TRUE ~ NA_character_),
         cgroup = case_when(iso3 %in% focus_cn ~ iso3,
                            TRUE ~ "ZZOTHER")) %>%
  ggplot(mapping = aes(x = days_elapsed, y = cu_cases,
                       color = cgroup, label = end_label,
                       group = cname)) +
  geom_line(size = 0.5) +
  geom_text_repel(nudge_x = 0.75,
                  segment.color = NA) +
  guides(color = FALSE) +
  scale_color_manual(values = cgroup_cols) +
  scale_y_continuous(labels = scales::comma_format(accuracy = 1),
                     breaks = 2^seq(4, 19, 1),
                     trans = "log2") +
  labs(x = "Days Since 100th Confirmed Case",
       y = "Cumulative Number of Reported Cases (log2 scale)",
       title = "Cumulative Reported Cases of COVID-19",
       subtitle = paste("ECDC data as of", format(max(covnat$date), "%A, %B %e, %Y")),
       caption = "Cid PĆ³voas / Data: https://www.ecdc.europa.eu/") +
  theme_classic()