Plot range of Rt for continents

aa_plot_continent.r

library(data.table)
library(ggplot2)

cases <- fread('_nowcasts/covid-global/national-summary/cases.csv')
df <- fread('_nowcasts/covid-global/national-summary/rt.csv')
continents <- fread('_nowcasts/covid-global/data/continents_cnty.csv')
cases <- cases[, .(country, date, cases = median)]

dfcont <- merge(df, continents, by.x = "country", by.y = "country_name", all.x = TRUE)
dfcont <- merge(dfcont, cases, by = c("country", "date"), all.x = TRUE)

## Count cases by week remove if less than 50 in a week
dfcont$date <- as.Date(dfcont$date, format = "%Y-%m-%d")
dfcont[, week := week(dfcont$date)]
dfcont[, weekcases := sum(cases, na.rm = T), by = .(week, country) ]
dfcont <- dfcont[weekcases >=50,]

# Get min and max for each continent by date
range_cont <- dfcont[type == "nowcast", .(min = min(lower_90, na.rm = T), max = max(upper_90, na.rm = T)), by = .(Continent_Name, date)]

# PLot range
ggplot(range_cont) +
  geom_hline(yintercept = 1, linetype = "dashed") +
  geom_ribbon(aes(x = date, ymin = min, ymax = max,  group = Continent_Name), alpha = 0.5) +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 90), 
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.line = element_line(colour = "black")
        )  +
  facet_wrap(. ~ Continent_Name, scales = "free_x") +
  scale_y_continuous(breaks = c(0, 1,5,10,15)) +
  scale_x_date(date_breaks = "2 week", limits = c(min(range_cont$date), max(range_cont$date)),
               date_labels = "%b %d") +
  ylab("Effective reproduction no") +
  xlab("Date")
  

continents_cnty.csv