data_raw/italy_region_refresh.R

In Covid19R/covid19italy: The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Italy Dataset

# Pulling raw data
update_italy_region <- function(){
`%>%` <- magrittr::`%>%`

italy_region <- read.csv("https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-regioni/dpc-covid19-ita-regioni.csv",
                         stringsAsFactors = FALSE) %>%
  stats::setNames(c("date_temp", "state",
                    "region_code", "region_name",
                    "lat", "long",
                    "hospitalized_with_symptoms", "intensive_care",
                    "total_hospitalized", "home_confinement",
                    "cumulative_positive_cases", "daily_positive_cases",
                    "daily_cases", "recovered",
                    "death", "cumulative_cases",
                    "total_tests", "total_people_tested",
                    "notes_it", "notes_en")) %>%
  dplyr::mutate(date = lubridate::ymd(substr(date_temp, 1, 10))) %>%
  dplyr::select(-date_temp, - state, -notes_it, -notes_en, -daily_cases) %>%
  dplyr::select(date, dplyr::everything()) %>%
  dplyr::mutate(region_spatial = region_name) %>%
  dplyr::arrange(date)

italy_region$region_spatial <- ifelse(italy_region$region_spatial == "Emilia Romagna",
                                      "Emilia-Romagna",
                                      italy_region$region_spatial)


italy_region$region_spatial <- ifelse(italy_region$region_spatial == "Friuli Venezia Giulia",
                                      "Friuli-Venezia Giulia",
                                      italy_region$region_spatial)


italy_region$region_spatial <- ifelse(italy_region$region_spatial == "Sicilia",
                                      "Sicily",
                                      italy_region$region_spatial)

italy_region$region_spatial <- ifelse(italy_region$region_spatial == "Puglia",
                                      "Apulia",
                                      italy_region$region_spatial)


italy_region$region_spatial <- ifelse(italy_region$region_spatial == "P.A. Bolzano" |
                                        italy_region$region_spatial == "P.A. Trento",
                                      "Trentino-Alto Adige",
                                      italy_region$region_spatial)


if(ncol(italy_region) != 17){
  stop("The number of columns is invalid")
} else if(nrow(italy_region)< 1130){
  stop("The number of raws does not match the minimum number of rows")
} else if(min(italy_region$date) != as.Date("2020-02-24")){
  stop("The starting date is invalid")
}

italy_region_csv <- read.csv("https://raw.githubusercontent.com/Covid19R/covid19italy/master/csv/italy_region.csv", stringsAsFactors = FALSE) %>%
  dplyr::mutate(date = as.Date(date))

if(ncol(italy_region_csv) != 17){
  stop("The number of columns is invalid")
} else if(nrow(italy_region_csv)< 1130){
  stop("The number of raws does not match the minimum number of rows")
} else if(min(italy_region_csv$date) != as.Date("2020-02-24")){
  stop("The starting date is invalid")
}


if(nrow(italy_region) > nrow(italy_region_csv)){
  print("Updates available")
  usethis::use_data(italy_region, overwrite = TRUE)
  write.csv(italy_region, "csv/italy_region.csv", row.names = FALSE)
  print("The region dataset was updated")
} else {
  print("Updates are not available")
}

return(print("Done..."))

}


update_italy_region()