72 lines
2.1 KiB
R
72 lines
2.1 KiB
R
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library(dplyr)
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library(highcharter)
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library(xts)
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#install.packages("rworldmap")
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library(rworldmap)
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#install.packages("countrycode")
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#library(countrycode)
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#install.packages("rgeos")
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library(rgeos)
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library(ggplot2)
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#install.packages("rgdal")
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library(rgdal)
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#install.packages("devtools")
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#library(devtools)
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library(dplyr)
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library(viridis)
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##install_github("dgrtwo/gganimate", ref = "26ec501")
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#install.packages("hms")
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library(hms)
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#install.packages("gganimate")
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library(gganimate)
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library(zoo)
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library(scales)
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cov <- read.csv("proj2/max-covid.csv", header = TRUE)
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#df <- data.frame(as.Date(cov$date, format="%Y-%m-%d"), cov$iso_code, cov$total_cases)
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df <- data.frame(as.Date(cov$date), cov$iso_code, cov$total_cases)
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#colnames(df) <- c('date', 'iso', 'total_cases')
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#df$date = format(df$date, "%Y-%m")
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#dd <- df %>% group_by(iso, date)
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#df %>% mutate(date2 = format(cov.date, "%Y-%m")) %>% group_by(cov.iso_code, date2) %>% summarise(total = sum(cov.total_cases))
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#df = df[order(as.Date(df$cov.date, format="%Y-%m-%d")),]
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casesmax = max(df$total_cases, na.rm=T)
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casesmin = min(df$total_cases, na.rm=T)
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wmap <- getMap(resolution="low")
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#wmap <- spTransform(wmap, CRS("+proj=robin")) # reproject
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wmap_df <- fortify(wmap, region = "ISO3")
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wmap_df <- left_join(wmap_df, df, by = c('id'='cov.iso_code'))
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ggplot(data=wmap_df, frame = date) +
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geom_polygon(aes(x = long, y = lat, group = group, fill=cov.total_cases), color="gray90") +
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scale_fill_viridis(name="Zachorowania", na.value="white", labels = comma) +
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theme_void() +
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guides(fill = guide_colorbar(title.position = "top")) +
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labs(title = "Liczba zachorowań w dniu 31.05.2021")
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#+
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# theme( legend.position = c(.5, .08),
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# legend.direction = "horizontal",
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# legend.title.align = 0,
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# legend.key.size = unit(1.3, "cm"),
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# legend.title=element_text(size=17),
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# legend.text=element_text(size=13) )
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#+
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# transition_time(date)
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#gganimate(o)
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#gg_animate(o, "output4020_old.gif", title_frame =T,
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# ani.width=1600, ani.height=820, dpi=800, interval = .4)
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