US data

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: COVID19
 Type: Package
 Title: Coronavirus COVID-19 (2019-nCoV) Data Acquisition and Visualization
-Version: 0.2.3.2
+Version: 0.2.3.3
 Authors@R: person(given = "Emanuele", family = "Guidotti", email = "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8961-6623"))
 Description: Collects unified and curated datasets of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic across several trusted sources. The latest data are downloaded in real-time, processed and merged with demographic indicators. The package implements advanced data visualization across the space and the time dimensions by means of animated mapping. Besides worldwide data, the package includes granular data for Italy, Switzerland and the Diamond Princess.
 License: GPL-3

NAMESPACE

@@ -6,6 +6,7 @@ export(geomap)
 export(italy)
 export(liechtenstein)
 export(switzerland)
+export(us)
 export(world)
 import(ggplot2)
 importFrom(dplyr,"%>%")

R/diamond.R

@@ -46,7 +46,10 @@
 diamond <- function(){
 
   # download
-  x <- jhuCSSE()
+  x <- jhuCSSE("global")
+
+  # bindings
+  country <- state <- NULL
 
   # subset
   x         <- x[x$country=="Diamond Princess",]

R/jhuCSSE.R

@@ -1,4 +1,4 @@
-jhuCSSE <- function(){
+jhuCSSE <- function(type = "global"){
 
   # data source
   repo <- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/"
@@ -17,17 +17,28 @@ jhuCSSE <- function(){
     colnames(x)[cn %in% c("Longitude", "Long")] <- "lng"
     colnames(x)[cn=="Province_State"]           <- "state"
     colnames(x)[cn=="Country_Region"]           <- "country"
+    colnames(x)[cn=="Population"]               <- "pop"
 
     return(x)
 
   }
 
-  # files
-  files = c(
-    "confirmed" = "time_series_covid19_confirmed_global.csv",
-    "deaths"    = "time_series_covid19_deaths_global.csv",
-    "tests"     = "time_series_covid19_testing_global.csv"
-  )
+  # global
+  if(type=="global"){
+    files = c(
+      "confirmed" = "time_series_covid19_confirmed_global.csv",
+      "deaths"    = "time_series_covid19_deaths_global.csv"
+    )
+  }
+
+  # US
+  if(type=="US"){
+    files = c(
+      "confirmed" = "time_series_covid19_confirmed_US.csv",
+      "deaths"    = "time_series_covid19_deaths_US.csv"
+    )
+  }
+
 
   # download data
   data <- NULL
@@ -40,13 +51,23 @@ jhuCSSE <- function(){
       next
 
     x      <- clean_colnames(x)
-    x      <- reshape2::melt(x, id = c("state", "country", "lat", "lng"), value.name = names(files[i]), variable.name = "date")
+    cn     <- colnames(x)
+    id     <- c("Combined_Key", "state", "country", "lat", "lng", "pop")
+    id     <- id[id %in% cn]
+    cn     <- (cn %in% id) | !is.na(as.Date(cn, format = "X%m_%d_%y"))
+
+    x      <- reshape2::melt(x[,cn], id = id, value.name = names(files[i]), variable.name = "date")
     x$date <- as.Date(x$date, format = "X%m_%d_%y")
 
-    if(!is.null(data))
-      data <- merge(data, x, all = TRUE, by = c("state", "country", "lat", "lng", "date"))
-    else
+    if(!is.null(data)){
+      if(type=="global")
+        data <- merge(data, x, all = TRUE, by = c("state", "country", "date"), suffixes = c("",".y"))
+      if(type=="US")
+        data <- merge(data, x, all = TRUE, by = c("Combined_Key", "date"), suffixes = c("",".y"))
+    }
+    else {
       data <- x
+    }
 
   }
 

R/us.R

@@ -0,0 +1,93 @@
+#' Coronavirus COVID-19 data - United States
+#'
+#' Tidy format dataset of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic.
+#' US data by state.
+#' The data are downloaded in real-time.
+#'
+#' @seealso \code{\link{world}}, \code{\link{diamond}}, \code{\link{italy}}, \code{\link{switzerland}}, \code{\link{liechtenstein}}
+#'
+#' @param type one of \code{country} (data by country) or \code{state} (data by state). Default \code{state}, data by state.
+#'
+#' @details
+#' Data pulled from the repository for the 2019 Novel Coronavirus
+#' Visual Dashboard operated by the Johns Hopkins University Center for Systems
+#' Science and Engineering (JHU CSSE). Also, Supported by ESRI Living Atlas Team
+#' and the Johns Hopkins University Applied Physics Lab (JHU APL).
+#' This \href{https://github.com/CSSEGISandData/COVID-19}{repository} and its contents herein, including all data, mapping, and analysis,
+#' copyright 2020 Johns Hopkins University, all rights reserved, is provided to the
+#' public strictly for educational and academic research purposes.
+#' The Website relies upon publicly available data from multiple sources,
+#' that do not always agree. The Johns Hopkins University hereby disclaims any and
+#' all representations and warranties with respect to the Website, including accuracy,
+#' fitness for use, and merchantability. Reliance on the Website for medical guidance or
+#' use of the Website in commerce is strictly prohibited. Data Sources:
+#' \itemize{
+#'  \item \href{https://www.who.int/}{World Health Organization (WHO)}
+#'  \item \href{http://3g.dxy.cn/newh5/view/pneumonia}{DXY.cn. Pneumonia. 2020}
+#'  \item \href{https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/}{BNO News}
+#'  \item \href{http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml}{National Health Commission of the People’s Republic of China (NHC)}
+#'  \item \href{http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm}{China CDC (CCDC)}
+#'  \item \href{https://www.chp.gov.hk/en/features/102465.html}{Hong Kong Department of Health}
+#'  \item \href{https://www.ssm.gov.mo/portal/}{Macau Government}
+#'  \item \href{https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0}{Taiwan CDC}
+#'  \item \href{https://www.cdc.gov/coronavirus/2019-ncov/index.html}{US CDC}
+#'  \item \href{https://www.canada.ca/en/public-health/services/diseases/coronavirus.html}{Government of Canada}
+#'  \item \href{https://www.health.gov.au/news/coronavirus-update-at-a-glance}{Australia Government Department of Health}
+#'  \item \href{https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases}{European Centre for Disease Prevention and Control (ECDC)}
+#'  \item \href{https://www.moh.gov.sg/covid-19}{Ministry of Health Singapore (MOH)}
+#'  \item \href{http://www.salute.gov.it/nuovocoronavirus}{Italy Ministry of Health}
+#' }
+#'
+#' @return Return of the internal function \code{\link{covid19}}
+#'
+#' @examples
+#' # data by country
+#' x <- us("country")
+#'
+#' # data by state
+#' x <- us("state")
+#'
+#' @export
+#'
+us <- function(type = "state"){
+
+  # check
+  if(!(type %in% c("country","state")))
+    stop("type must be one of 'country', 'state'")
+
+  # download data
+  x <- jhuCSSE("US")
+
+  # drop "Grand Princess" and "Diamond Princess"
+  x <- x[!(x$state %in% c("Grand Princess","Diamond Princess")),]
+
+  # bindings
+  Combined_Key <- country <- state <- date <- lat <- lng <- confirmed <- deaths <- tests <- pop <- NULL
+
+  # group by
+  if(type=="country"){
+    x <- x %>%
+      dplyr::group_by(country, date)
+  }
+  if(type=="state"){
+    x <- x %>%
+      dplyr::group_by(Combined_Key, state, country, date)
+  }
+
+  # aggregate
+  x <- x %>%
+    dplyr::summarize(lat = mean(lat, na.rm = TRUE),
+                     lng = mean(lng, na.rm = TRUE),
+                     confirmed = sum(confirmed, na.rm = TRUE),
+                     deaths = sum(deaths, na.rm = TRUE),
+                     tests = sum(tests, na.rm = TRUE),
+                     pop = sum(pop, na.rm = TRUE))
+
+
+  # population info
+  # x <- merge(x, COVID19::US, by.x = "country", by.y = "id", all.x = TRUE)
+
+  # return
+  return(covid19(x))
+
+}

R/world.R

@@ -56,7 +56,7 @@ world <- function(type = "state"){
     stop("type must be one of 'country', 'state'")
 
   # download data
-  x <- jhuCSSE()
+  x <- jhuCSSE("global")
 
   # drop "Taiwan*" and "Holy See"
   x <- x[!(x$country %in% c("Taiwan*","Holy See")),]