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#' Getting real-time monitoring map of the 2019-nCoV virus
#'
#' @return a ggplot2 object which shows the real-time monitoring map of the 2019-nCoV virus
#' @export
#' @import dplyr
#' @import ggplot2
#' @import pinyin
#' @import maps
#' @param x a R2019-nCoV object, i.e. the result of function get_2019nCoV
#' @examples
#'
#' x <- get_2019nCoV()
#' map <- getMap(x)
getMap <- function(x) {
world_map <- map_data("world")
df <- getDataFrame(x)
df$province <- pinyin::py(df$name, sep = "", dic = pinyin::pydic(method = "toneless",
dic = "pinyin2"))
df <- df %>% dplyr::arrange(df$name)
df$province[24] <- "shannxi"
china_line_data <- china_line_data
china_map_data <- china_map_data
china_data <- dplyr::full_join(china_map_data, df, by = "province")
china_data <- china_data %>% dplyr::mutate(value = china_data$total$confirm)
temp <- cut(china_data$value, c(0, 10, 100, 500, 1000, 10000, Inf))
levels(temp) <- c("0-10", "11-100", "101-500", "501-1000", "1001-10000", "> 10000 ")
china_data <- china_data %>% dplyr::mutate(value_factor = temp)
p <- ggplot() +
geom_polygon(data=world_map,
aes(x = world_map$long, y = world_map$lat, group = world_map$group),
colour = "grey20",
fill = "#EAEAEA",
size = .1) +
geom_path(data = china_line_data,
aes(x = china_line_data$long, y = china_line_data$lat, group = china_line_data$group),
colour = "black", size = 0.5) +
geom_polygon(data = china_data,
aes(x = china_data$long, y = china_data$lat, group = china_data$group, fill = china_data$value_factor),
colour = "grey10", size = 0.3) +
scale_fill_manual(breaks = levels(temp),
labels = levels(temp),
values = c("#F8E2CF", "#E3B1AB", "#D58877", "#B53E3C", "#622E2F", "#360D0E"),
na.value = "#FEFFE8") +
coord_quickmap() +
theme_void() +
theme(legend.title = element_blank(), legend.box.just = "left",
legend.key.height = unit(0.6, "cm"), legend.key.width = unit(0.4, "cm"),
plot.background = element_rect(fill = "lightskyblue")) +
xlim(70, 140) + ylim(5, 55)
return(p)
}
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