release preps 1.1.3 (#54)

* release preps 1.1.3

- Integrate population data for map (#29)

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Covid19
 Title: Covid-19 Data Analysis
-Version: 1.1.2
+Version: 1.1.3
 Authors@R: 
     c(person("Francesca", "Vitalini", role = c("cre", "aut"),
              email = 'francesca.vitalini@mirai-solutions.com'),

NAMESPACE

@@ -20,6 +20,7 @@ export(getTableOptions)
 export(get_Covid19_version)
 export(get_daily_data)
 export(get_date_data)
+export(get_pop_data)
 export(get_timeseries_by_contagion_day_data)
 export(get_timeseries_country_data)
 export(get_timeseries_data)

NEWS.md

@@ -1,3 +1,7 @@
+### Covid19 1.1.3 (2020-03-30)
+
+- Integrate population data for map (#29)
+
 ### Covid19 1.1.2 (2020-03-26)
 
 - JHU data source currently deprecated: switch (temporarily) to https://github.com/bumbeishvili/covid19-daily-data (#48). Users are alerted on app launch.

R/get_data.R

@@ -265,3 +265,62 @@ get_date_data <- function(data, date){
     mutate(death_rate = 100*new_deaths / lag(deaths)) %>%
     ungroup()
 }
+
+
+#' population data
+#' @rdname get_pop_data
+#'
+#' @param data data.frame
+#'
+#' @import dplyr
+#' @import tidyr
+#'
+#' @return global tibble of confirmed, deaths, active and recovered for each day by population
+#'
+#' @examples
+#' \dontrun{
+#' orig_data <- get_timeseries_full_data() %>%
+#'               get_timeseries_by_contagion_day_data() %>%
+#'               select(-ends_with("rate"))
+#' data <- orig_data %>% align_country_names()
+#'
+#'}
+#'
+#' @export
+get_pop_data <- function(data){
+  #Reference: https://en.wikipedia.org/wiki/List_of_countries_and_dependencies_by_population
+  # pop_url <- "https://raw.githubusercontent.com/DrFabach/Corona/master/pop.csv"
+  # pop_raw <- readLines(pop_url)
+  # pop <- data.frame(pop_raw[2:length(pop_raw)], stringsAsFactors = FALSE) %>%
+  #   setNames(pop_raw[1])
+  # pop <- pop %>%
+  #   separate(col = "Country;Population", into = c("Country.Region", "population"), sep = ";")
+  # write.csv2(pop, "./inst/population_data/pop.csv")
+  population <- read.csv2(system.file("population_data/pop.csv", package = "Covid19"),stringsAsFactors = F) %>%
+    select(-X)
+  population$Country.Region <- population$Country.Region %>%
+    recode(
+      "Ivory Coast" = "C\\u00f4te d'Ivoire",
+      "DR Congo" = "Republic of the Congo",
+      "United Arab Emirates" = "UAE",
+      "East Timor" = "Timor-Leste" ,
+      "Saint Vincent and the Grenadines" = "St. Vincent Grenadines",
+      "Puerto Rico(US)" = "Puerto Rico",
+      "Comoros" = "Mayotte",
+      "Guam(US)" = "Guam",
+      "Greenland(Denmark)" = "Greenland",
+      "Eswatini" = "eSwatini",
+      "Isle of Man(UK)" = "Channel Islands",
+      "Central African Republic" = "CAR",
+      "Cape Verde" = "Cabo Verde",
+      "Antigua and Barbuda" = "Antigua and Barb.",
+      "United States" = "United States of America"
+    )
+
+  data_pop <- data %>%
+    mutate(Country.Region = country_name) %>%
+    left_join(population) %>%
+    select(-Country.Region)
+
+  data_pop
+}

R/mod_map.R

@@ -20,6 +20,7 @@ mod_map_ui <- function(id){
       top = 10, left = 10, draggable = F,
       div(style = "margin:10px;",
           radioButtons(inputId = ns("radio_choices"), label = "", choices = c("confirmed", "deaths", "recovered", "active"), selected = "confirmed", inline = T),
+          radioButtons(inputId = ns("radio_pop"), label = "", choices = c("total", "per 1M pop"), selected = "total", inline = T),
           uiOutput(ns("slider_ui")),
           helpText("The detail of each country can be obtained by clicking on it.")
       )
@@ -47,14 +48,16 @@ mod_map_server <- function(input, output, session, data){
   countries_data <- load_countries_data(destpath = system.file("./countries_data", package = "Covid19"))
 
   data_clean <- reactive({
-    data <- data() %>% align_country_names()
+    data <- data() %>%
+      aggregate_province_timeseries_data() %>%
+      align_country_names()
 
     data$country_name <- as.character(unique(as.character(countries_data$NAME))[charmatch(data$Country.Region, unique(as.character(countries_data$NAME)))])
 
-    data <- data %>%
+    data_clean <- data %>%
       filter(!is.na(country_name))
 
-    data
+    data_clean
   })
 
   # UI controls ----
@@ -66,17 +69,28 @@ mod_map_server <- function(input, output, session, data){
 
   # Data for a given date
   data_date <- reactive({
-    data_clean() %>%
+    data_date <- data_clean() %>%
       filter(date == req(input$slider_day)) %>%
-      select(-c(Country.Region, Province.State, Lat, Long, date, contagion_day)) %>%
+      select(-c(Country.Region, date, contagion_day)) %>%
       group_by(country_name) %>%
-      summarise_each(sum)
+      summarise_each(sum) %>%
+      ungroup() %>%
+      get_pop_data()
+    data_date
   })
 
   data_plot <- reactive({
     data_selected <- data_date() %>%
       bind_cols(data_date()[,input$radio_choices] %>%
-                  setNames("indicator")) %>%
+                  setNames("indicator"))
+
+    if (req(input$radio_pop) == "per 1M pop") {
+      data_selected <- data_selected %>%
+        # percentage of indicator per 1M population
+        mutate(indicator = round(1000000 * .$indicator / .$population))
+    }
+
+    data_selected <- data_selected %>%
       select(country_name, indicator)
 
     data_plot <-  sp::merge(countries_data,
@@ -151,7 +165,7 @@ mod_map_server <- function(input, output, session, data){
                 bins = log(10^(seq(0,log10(roundUp(max_value())),1))),
                 values = log(1:roundUp(max_value())),
                 data = log(1:roundUp(max_value())),
-                labFormat = labelFormat(transform = function(x) roundUp(exp(x)), suffix = " cases")
+                labFormat = labelFormat(transform = function(x) roundUp(exp(x)), suffix = paste0(" cases ", input$radio_pop))
       )
   })