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| library(tidyverse) | |
| library(gghighlight) | |
| library(ggrepel) | |
| library(scales) | |
| fix_name_comma <- function(x) { | |
| name_split <- strsplit(x, ",\\s?") | |
| vapply(name_split, function(x) { | |
| if (length(x) == 1L) return(x) | |
| paste(x[2], x[1]) | |
| }, FUN.VALUE = character(1)) | |
| } | |
| data <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv") | |
| data_long <- pivot_longer(data, `1/22/20`:last_col(), names_to = "date", values_to = "cases") %>% | |
| filter(!is.na(cases), | |
| (!grepl("[Pp]rincess|[Rr]ecovered", `Province/State`) | is.na(`Province/State`)), | |
| `Country/Region` != "Cruise Ship", `Country/Region` != "Diamond Princess") %>% | |
| mutate(date = as.Date(date, format = "%m/%d/%y"), | |
| `Country/Region` = fix_name_comma(`Country/Region`)) | |
| max_date <- max(data_long$date) | |
| cap <- glue::glue("Data from https://github.com/CSSEGISandData/COVID-19, {max_date}") | |
| data_by_country <- group_by(data_long, country = `Country/Region`, date) %>% | |
| summarise(cases = sum(cases, na.rm = TRUE)) | |
| highlight_countries <- c("Canada", "US", "Italy", "United Kingdom", "Spain", "Australia") | |
| (plot_countries_by_date <- filter(data_by_country, country != "China") %>% | |
| ggplot(aes(x = date, y = cases, colour = country)) + | |
| scale_x_date(date_breaks = "1 week", date_labels = "%b %d") + | |
| scale_y_log10(expand = c(0,0.5), | |
| labels = label_comma(accuracy = 1)) + | |
| geom_line(size = 1.5) + | |
| gghighlight(country %in% highlight_countries, | |
| use_direct_label = FALSE, | |
| unhighlighted_params = list(size = 0.5)) + | |
| geom_text_repel(aes(label = paste0(country, " (", cases, ")")), | |
| data = filter(data_by_country, | |
| country %in% highlight_countries, | |
| date == max(date)), | |
| nudge_x = 1, direction = "y", | |
| segment.size = 0, | |
| xlim = c(max(data_by_country$date), | |
| max(data_by_country$date) + 21)) + | |
| scale_color_brewer(palette = 2, type = "qual", guide = "none") + | |
| coord_cartesian(clip = "off") + | |
| theme_minimal() + | |
| theme(plot.margin = unit(c(0.5,4,0.5,0.5), "cm")) + | |
| labs(x = "Date", | |
| y = "Total number of cases (log scale)", | |
| title = "COVID-19 Confirmed Cases", | |
| caption = cap)) | |
| n_cases <- 100 | |
| data_by_country_n_days <- data_by_country %>% | |
| filter(cases >= n_cases) %>% | |
| group_by(country) %>% | |
| arrange(country, date) %>% | |
| mutate(days_since_nth_case = as.numeric(date - min(date, na.rm = TRUE))) %>% | |
| ungroup() | |
| (plot_100_cases <- filter(data_by_country_n_days, country != "China") %>% | |
| ggplot(aes(x = days_since_nth_case, y = cases, colour = country)) + | |
| scale_y_log10(labels = label_comma(accuracy = 1)) + | |
| geom_line(size = 1.5) + | |
| gghighlight(country %in% c(highlight_countries, "South Korea", "Singapore", "Japan", "Iran"), | |
| use_direct_label = FALSE, | |
| unhighlighted_params = list(size = 0.5)) + | |
| geom_text_repel(aes(label = paste0(country, " (", cases, ")")), | |
| data = filter(data_by_country_n_days, | |
| country %in% c(highlight_countries, "South Korea", "Singapore", "Japan", "Iran"), | |
| date == max(date)), | |
| nudge_x = 2, direction = "both", | |
| segment.size = 0) + | |
| coord_cartesian(clip = "off") + | |
| scale_color_brewer(palette = 3, type = "qual", guide = "none") + | |
| theme_minimal() + | |
| theme(plot.margin = unit(c(0.5,0.5,0.5,0.5), "cm")) + | |
| labs(x = glue::glue("Days since reaching {n_cases} confirmed cases"), | |
| y = "Total number of cases (log scale)", | |
| title = glue::glue("COVID-19 confirmed cases since reaching {n_cases} confirmed cases"), | |
| caption = cap)) | |
| data_by_country_1st_case <- data_by_country %>% | |
| filter(cases >= 1) %>% | |
| group_by(country) %>% | |
| arrange(country, date) %>% | |
| mutate(days_since_nth_case = as.numeric(date - min(date, na.rm = TRUE))) %>% | |
| ungroup() | |
| (plot_1st_cases <- filter(data_by_country_1st_case, country != "China") %>% | |
| ggplot(aes(x = days_since_nth_case, y = cases, colour = country)) + | |
| scale_y_log10(labels = label_comma(accuracy = 1)) + | |
| geom_line(size = 1.5) + | |
| gghighlight(country %in% c(highlight_countries, "South Korea", "Singapore", "Japan", "Iran"), | |
| use_direct_label = FALSE, | |
| unhighlighted_params = list(size = 0.5)) + | |
| geom_text_repel(aes(label = paste0(country, " (", cases, ")")), | |
| data = filter(data_by_country_1st_case, | |
| country %in% c(highlight_countries, "South Korea", "Singapore", "Japan", "Iran"), | |
| date == max(date)) , | |
| nudge_x = 6, direction = "both", | |
| segment.size = 0, | |
| xlim = c(min(data_by_country_1st_case$days_since_nth_case), | |
| max(data_by_country_1st_case$days_since_nth_case) + 20)) + | |
| scale_color_brewer(palette = 3, type = "qual", guide = "none") + | |
| coord_cartesian(clip = "off") + | |
| theme_minimal() + | |
| theme(plot.margin = unit(c(0.5,4,0.5,0.5), "cm")) + | |
| labs(x = glue::glue("Days since first confirmed case"), | |
| y = "Total number of cases (log scale)", | |
| title = "COVID-19 confirmed cases since first confirmed case", | |
| caption = cap)) | |
| canada <- rename(data_long, | |
| country = `Country/Region`, | |
| province = `Province/State`) %>% | |
| filter(country == "Canada") | |
| (plot_canada <- ggplot(canada, aes(x = date, y = cases, colour = province)) + | |
| geom_line(size = 1) + | |
| scale_x_date(date_breaks = "1 week", date_labels = "%b %d") + | |
| scale_y_log10(expand = c(0,1), | |
| labels = label_comma(accuracy = 1)) + | |
| scale_color_brewer(palette = 3, type = "qual", guide = FALSE) + | |
| coord_cartesian(clip = "off") + | |
| geom_text_repel(aes(label = paste0(province, " (", cases, ")")), | |
| segment.size = 0, | |
| data = filter(canada, date == max(date)), | |
| nudge_x = 1, direction = "y", | |
| xlim = c(max(canada$date) + 1, max(canada$date) + 30) | |
| ) + | |
| theme_minimal() + | |
| theme(plot.margin = unit(c(0.5,6,0.5,0.5), "cm")) + | |
| labs(x = "Date", | |
| y = "Total number of cases (log scale)", | |
| title = "COVID-19 Confirmed Cases in Canada", | |
| caption = cap)) | |
| ggsave(glue::glue("countries_by_date-{max_date}.png"), plot_countries_by_date, width = 9, height = 6) | |
| ggsave(glue::glue("100_cases-{max_date}.png"), plot_100_cases, width = 9, height = 6) | |
| ggsave(glue::glue("1st_cases-{max_date}.png"), plot_1st_cases, width = 9, height = 6) | |
| ggsave(glue::glue("canada-{max_date}.png"), plot_canada, width = 9, height = 6) |
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Thanks for sharing - I just downloaded it and it runs fine. I see you changed a couple of hardwired things - thanks. Just tried the log-axis for provinces - looking like exponential growth (though noisy).