Datos y grafico

#devtools::install_github("avallecam/covid19viz")
#devtools::install_github('cttobin/ggthemr')

library(colorspace)
library(ggthemr)

paises <- c("Peru", "Brazil", "Colombia", "Ecuador", "Chile", "Argentina", "Uruguay", "Paraguay", "Bolivia")

library(JLutils)
library(rio)
library(lubridate)
library(tidyverse)

dat <- rio::import("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv") %>%
  filter(`Country/Region` %in% paises) %>%
  gather(dates,cases,-`Province/State`,-`Country/Region`,-Lat,-Long) %>%
  filter(cases>0) %>%
  group_by(`Country/Region`) %>%
  mutate(dates = mdy(dates),
         start = first(dates),
         d_start = as.numeric(dates-start),
         per = ifelse(`Country/Region` =="Peru","Per","Otros"),
         max_cases = max(cases)) %>%
  filter(max_cases>30)

ggthemr('dust')

dat %>%
  filter(per =="Otros") %>%
  ggplot(aes(x = d_start, y = cases, group=`Country/Region`)) +
  geom_line(aes(col = `Country/Region`)) +
  geom_point(aes(col = `Country/Region`, shape = `Country/Region`)) +
  geom_text(data = dat %>% slice(n()) %>% filter(`Country/Region`!="Peru"),
            aes(y = cases, label = `Country/Region`, col = `Country/Region`), vjust=-.5, show.legend = F) +
  geom_line(dat = dat %>% filter(per=="Per"), col = "red") +
  geom_point(dat = dat %>% filter(per=="Per"), col = "red") +
  geom_text(data = dat %>% slice(n()) %>% filter(`Country/Region`=="Peru"),
            aes(y = cases, label = `Country/Region`), col = "red", vjust=-.5, show.legend = F) +
  scale_color_discrete_sequential(palette = "Teal", nmax = 14, order = 5:14) +
  labs(color = "Paises", x = "Dias desde primer reporte", y = "Numero de casos", shape = "Paises",
       title = paste0("Actualizado hasta: ", max(dat$dates))) +
  scale_y_log10() + 
  theme(legend.position = "bottom")