library(dplyr)
library(highcharter)
library(xts)
#install.packages("rworldmap")
library(rworldmap)
#install.packages("countrycode")
#library(countrycode)
#install.packages("rgeos")
library(rgeos)
library(ggplot2)
#install.packages("rgdal")
library(rgdal)
#install.packages("devtools")
#library(devtools)
library(dplyr)
library(viridis)
##install_github("dgrtwo/gganimate", ref = "26ec501")
#install.packages("hms")
library(hms)
#install.packages("gganimate")
library(gganimate)

library(zoo)

cov <- read.csv("proj2/max-covid.csv", header = TRUE)

#df <- data.frame(as.Date(cov$date, format="%Y-%m-%d"), cov$iso_code, cov$total_cases)
df <- data.frame(as.Date(cov$date), cov$iso_code, cov$total_cases)
#colnames(df) <- c('date', 'iso', 'total_cases')

#df$date = format(df$date, "%Y-%m") 

#dd <- df %>% group_by(iso, date)




#df %>% mutate(date2 = format(cov.date, "%Y-%m")) %>% group_by(cov.iso_code, date2) %>% summarise(total = sum(cov.total_cases))


#df = df[order(as.Date(df$cov.date, format="%Y-%m-%d")),]

casesmax = max(df$total_cases, na.rm=T)
casesmin = min(df$total_cases, na.rm=T)

wmap <- getMap(resolution="low")

#wmap <- spTransform(wmap, CRS("+proj=robin")) # reproject
wmap_df <- fortify(wmap, region = "ISO3")
wmap_df <- left_join(wmap_df, df, by = c('id'='cov.iso_code'))

ggplot(data=wmap_df, frame = date) +
  geom_polygon(aes(x = long, y = lat, group = group, fill=cov.total_cases), color="gray90") +
  scale_fill_viridis(name="Zachorowania", na.value="white") +
  theme_void() +
  guides(fill = guide_colorbar(title.position = "top")) +
  labs(title = "Liczba zachorowań w dniu 31.05.2021") 
#+
#  theme( legend.position = c(.5, .08), 
#         legend.direction = "horizontal", 
#         legend.title.align = 0,
#         legend.key.size = unit(1.3, "cm"),
#         legend.title=element_text(size=17), 
#         legend.text=element_text(size=13) )
#+
#  transition_time(date)

#gganimate(o)

#gg_animate(o, "output4020_old.gif", title_frame =T, 
#           ani.width=1600, ani.height=820, dpi=800, interval = .4)