tidycovid19 (version 0.0.0.9000)

plot_covid19_stripes: Plot Covid-19 Stripes

Description

Provides a flexible visualization of the country-level Covid-19 spread, plotted by colored daily lines to generate a stripes display. Uses data from the Johns Hopkins University CSSE team (https://github.com/CSSEGISandData/COVID-19) and the World Bank (https://data.worldbank.org).

Usage

plot_covid19_stripes(
  data = download_merged_data(cached = TRUE, silent = TRUE),
  type = "deaths",
  min_cases = ifelse(per_capita, ifelse(type == "deaths", 5, 50), ifelse(type ==
    "deaths", 1000, 10000)),
  cumulative = FALSE,
  change_ave = 7,
  per_capita = FALSE,
  population_cutoff = 0,
  diverging_color_scale = FALSE,
  countries = NULL,
  sort_countries = NULL,
  data_date_str = format(lubridate::as_date(data$timestamp[1]), "%B %d, %Y")
)

Arguments

data

The data frame to base the plot on. Should be a merged data frame obtained by download_merged_data and defaults to download_merged_data(cached = TRUE, silent = TRUE).

type

The statistic that you want to plot. Needs to be either "confirmed", "deaths", "recovered" or "active", defined as the difference of "confirmed", "deaths" and "recovered".

min_cases

Only countries that have a maximum of type cases higher than min_cases during the data period are included in the plot. Uses reasonable defaults depending on type and per_capita.

cumulative

If TRUE, data is being plotted as cumulative (showing the total figures). If FALSE, (the default) (averaged) daily changes are plotted instead. See change_ave to set the averaging window.

change_ave

Number of days to average over when you plot daily changes.

per_capita

If TRUE data is being plotted as per capita measure based on World Bank data. Defaults to FALSE.

population_cutoff

Do you want to restrict the plot to countries that exceed a certain population cutoff? Takes a value in millions and defaults to 0. Useful for per capita displays.

diverging_color_scale

Should be set to TRUE when a type is chosen that can have meaningful negative values (this is the case for "active" cases). Defaults to FALSE.

countries

A character vector of ISO3c (ISO 3166-1 alpha-3) codes that you want to include. Note that including many countries can lead to long plotting times and might cause the plot to fail rendering when the display is to small.

sort_countries

By default, countries are sorted alphabetically by ISO3c code. "start" will sort countries by when they first exceeded min_cases. "magnitude" will sort by decreasing maximum value for type. "countries" requires countries to be set and sorts the display in the order of the ISO3c codes provided. Alternatively, you can recode the iso3c in your data to a factor in the ordering that you prefer. See examples below.

data_date_str

A date string to include in the annotation of the plot giving the time when the data was pulled. Defaults to the timestamp of the data. Note that you might run into issues with the default when running this in a non-english locale. Consider setting it by hand then.

Value

A ggplot2 oobject.

Examples

# NOT RUN {
plot_covid19_stripes()

merged <- download_merged_data(cached = TRUE, silent = TRUE)
plot_covid19_stripes(merged, per_capita = TRUE, population_cutoff = 10)

plot_covid19_stripes(merged,
  countries = c("ITA", "ESP", "FRA", "DEU", "USA"),
  sort_countries = "countries"
)

sortdf <- dplyr::tibble(
  iso3c = unique(merged$iso3c),
  continent = countrycode::countrycode(iso3c, "iso3c", "continent")
) %>% dplyr::arrange(continent, iso3c)
df <- merged
df$iso3c <- factor(merged$iso3c, sortdf$iso3c)
plot_covid19_stripes(df, type = "confirmed")

# }