Covid-19.R

library(yaml)
library(httr)
library(tidyverse)
library(magrittr)
library(lubridate)
library(ggthemes)

GET("https://raw.githubusercontent.com/opencovid19-fr/data/master/sante-publique-france/2020-03-04.yaml") %>%
  content() %>%
  yaml.load() %>%
  names()

GET("https://raw.githubusercontent.com/opencovid19-fr/data/master/sante-publique-france/2020-03-04.yaml") %>%
  content() %>%
  yaml.load() %>%
  extract2("donneesRegionales") %>%
  extract2(4) %>%
  as_tibble()

GET("https://raw.githubusercontent.com/opencovid19-fr/data/master/sante-publique-france/2020-03-04.yaml") %>%
  content() %>%
  yaml.load() %>%
  extract2("donneesRegionales") %>%
  map_df(.f = function(x) {extract(x)})

get_regionaldata <- function(date) {
  paste0(
    "https://raw.githubusercontent.com/opencovid19-fr/data/master/sante-publique-france/", 
    as.character(ymd(date)), 
    ".yaml") %>%
    GET() %>%
    content() %>%
    yaml.load() %>%
    extract2("donneesRegionales") %>%
    map_df(.f = function(x) {extract(x)}) %>%
    mutate(date = ymd(date))
}
get_regionaldata(date = today())
tbl_regionaldata <- seq(ymd("2020-03-04"), today(), by = "day") %>%
  map_df(get_regionaldata) 
tbl_regionaldata

tbl_regionaldata %>%
  ggplot() +
  geom_col(mapping = aes(x = date, y = casConfirmes)) + 
  facet_wrap(ncol = 4, ~ nom)




GET("https://raw.githubusercontent.com/opencovid19-fr/data/master/sante-publique-france/2020-03-04.yaml") %>%
  content() %>%
  yaml.load() %>%
  extract2("donneesNationales") %>%
  as_tibble()

get_nationaldata <- function(date) {
  paste0(
    "https://raw.githubusercontent.com/opencovid19-fr/data/master/sante-publique-france/", 
    as.character(ymd(date)), 
    ".yaml") %>%
    GET() %>%
    content() %>%
    yaml.load() %>%
    extract2("donneesNationales") %>%
    as_tibble() %>%
    mutate(date = ymd(date))
  }

get_nationaldata(date = "2020-03-04")

tbl_nationaldata <- seq(ymd("2020-03-04"), today(), by = "day") %>%
  map_df(get_nationaldata) %>%
  mutate(
    growth_casConfirmes = casConfirmes / lag(casConfirmes) - 1, 
    growth_deces = deces / lag(deces) - 1
    )

tbl_nationaldata

tbl_nationaldata %>%
  ggplot() + 
  geom_col(mapping = aes(x = date, y = growth_casConfirmes)) +
  theme_fivethirtyeight() +
  labs(title = "Taux de croissance du nombre de cas confirmés", caption = "Données nationales")